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abort(WriterCommitMessage[]) - Method in interface org.apache.spark.sql.sources.v2.writer.DataSourceWriter
Aborts this writing job because some data writers are failed and keep failing when retry, or the Spark job fails with some unknown reasons, or DataSourceWriter.onDataWriterCommit(WriterCommitMessage) fails, or DataSourceWriter.commit(WriterCommitMessage[]) fails.
abort() - Method in interface org.apache.spark.sql.sources.v2.writer.DataWriter
Aborts this writer if it is failed.
abort(long, WriterCommitMessage[]) - Method in interface org.apache.spark.sql.sources.v2.writer.streaming.StreamWriter
Aborts this writing job because some data writers are failed and keep failing when retried, or the Spark job fails with some unknown reasons, or StreamWriter.commit(WriterCommitMessage[]) fails.
abort(WriterCommitMessage[]) - Method in interface org.apache.spark.sql.sources.v2.writer.streaming.StreamWriter
 
abortJob(JobContext) - Method in class org.apache.spark.internal.io.FileCommitProtocol
Aborts a job after the writes fail.
abortJob(JobContext) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
 
abortTask(TaskAttemptContext) - Method in class org.apache.spark.internal.io.FileCommitProtocol
Aborts a task after the writes have failed.
abortTask(TaskAttemptContext) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
 
abs(Column) - Static method in class org.apache.spark.sql.functions
Computes the absolute value of a numeric value.
abs() - Method in class org.apache.spark.sql.types.Decimal
 
absent() - Static method in class org.apache.spark.api.java.Optional
 
AbsoluteError - Class in org.apache.spark.mllib.tree.loss
:: DeveloperApi :: Class for absolute error loss calculation (for regression).
AbsoluteError() - Constructor for class org.apache.spark.mllib.tree.loss.AbsoluteError
 
AbstractLauncher<T extends AbstractLauncher<T>> - Class in org.apache.spark.launcher
Base class for launcher implementations.
accept(Parsers) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
accept(ES, Function1<ES, List<Object>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
accept(String, PartialFunction<Object, U>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
accept(Path) - Method in class org.apache.spark.ml.image.SamplePathFilter
 
acceptIf(Function1<Object, Object>, Function1<Object, String>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
acceptMatch(String, PartialFunction<Object, U>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
acceptSeq(ES, Function1<ES, Iterable<Object>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
acceptsType(DataType) - Method in class org.apache.spark.sql.types.ObjectType
 
accId() - Method in class org.apache.spark.CleanAccum
 
accumCleaned(long) - Method in interface org.apache.spark.CleanerListener
 
Accumulable<R,T> - Class in org.apache.spark
Deprecated.
use AccumulatorV2. Since 2.0.0.
Accumulable(R, AccumulableParam<R, T>) - Constructor for class org.apache.spark.Accumulable
Deprecated.
 
accumulable(T, AccumulableParam<T, R>) - Method in class org.apache.spark.api.java.JavaSparkContext
Deprecated.
use AccumulatorV2. Since 2.0.0.
accumulable(T, String, AccumulableParam<T, R>) - Method in class org.apache.spark.api.java.JavaSparkContext
Deprecated.
use AccumulatorV2. Since 2.0.0.
accumulable(R, AccumulableParam<R, T>) - Method in class org.apache.spark.SparkContext
Deprecated.
use AccumulatorV2. Since 2.0.0.
accumulable(R, String, AccumulableParam<R, T>) - Method in class org.apache.spark.SparkContext
Deprecated.
use AccumulatorV2. Since 2.0.0.
accumulableCollection(R, Function1<R, Growable<T>>, ClassTag<R>) - Method in class org.apache.spark.SparkContext
Deprecated.
use AccumulatorV2. Since 2.0.0.
AccumulableInfo - Class in org.apache.spark.scheduler
:: DeveloperApi :: Information about an Accumulable modified during a task or stage.
AccumulableInfo - Class in org.apache.spark.status.api.v1
 
accumulableInfoFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
accumulableInfoToJson(AccumulableInfo) - Static method in class org.apache.spark.util.JsonProtocol
 
AccumulableParam<R,T> - Interface in org.apache.spark
Deprecated.
use AccumulatorV2. Since 2.0.0.
accumulables() - Method in class org.apache.spark.scheduler.StageInfo
Terminal values of accumulables updated during this stage, including all the user-defined accumulators.
accumulables() - Method in class org.apache.spark.scheduler.TaskInfo
Intermediate updates to accumulables during this task.
accumulablesToJson(Traversable<AccumulableInfo>) - Static method in class org.apache.spark.util.JsonProtocol
 
Accumulator<T> - Class in org.apache.spark
Deprecated.
use AccumulatorV2. Since 2.0.0.
accumulator(int) - Method in class org.apache.spark.api.java.JavaSparkContext
Deprecated.
use sc().longAccumulator(). Since 2.0.0.
accumulator(int, String) - Method in class org.apache.spark.api.java.JavaSparkContext
Deprecated.
use sc().longAccumulator(String). Since 2.0.0.
accumulator(double) - Method in class org.apache.spark.api.java.JavaSparkContext
Deprecated.
use sc().doubleAccumulator(). Since 2.0.0.
accumulator(double, String) - Method in class org.apache.spark.api.java.JavaSparkContext
Deprecated.
use sc().doubleAccumulator(String). Since 2.0.0.
accumulator(T, AccumulatorParam<T>) - Method in class org.apache.spark.api.java.JavaSparkContext
Deprecated.
use AccumulatorV2. Since 2.0.0.
accumulator(T, String, AccumulatorParam<T>) - Method in class org.apache.spark.api.java.JavaSparkContext
Deprecated.
use AccumulatorV2. Since 2.0.0.
accumulator(T, AccumulatorParam<T>) - Method in class org.apache.spark.SparkContext
Deprecated.
use AccumulatorV2. Since 2.0.0.
accumulator(T, String, AccumulatorParam<T>) - Method in class org.apache.spark.SparkContext
Deprecated.
use AccumulatorV2. Since 2.0.0.
AccumulatorContext - Class in org.apache.spark.util
An internal class used to track accumulators by Spark itself.
AccumulatorContext() - Constructor for class org.apache.spark.util.AccumulatorContext
 
AccumulatorParam<T> - Interface in org.apache.spark
Deprecated.
use AccumulatorV2. Since 2.0.0.
AccumulatorParam.DoubleAccumulatorParam$ - Class in org.apache.spark
Deprecated.
use AccumulatorV2. Since 2.0.0.
AccumulatorParam.FloatAccumulatorParam$ - Class in org.apache.spark
Deprecated.
use AccumulatorV2. Since 2.0.0.
AccumulatorParam.IntAccumulatorParam$ - Class in org.apache.spark
Deprecated.
use AccumulatorV2. Since 2.0.0.
AccumulatorParam.LongAccumulatorParam$ - Class in org.apache.spark
Deprecated.
use AccumulatorV2. Since 2.0.0.
AccumulatorParam.StringAccumulatorParam$ - Class in org.apache.spark
Deprecated.
use AccumulatorV2. Since 2.0.0.
ACCUMULATORS() - Static method in class org.apache.spark.status.TaskIndexNames
 
accumulatorUpdates() - Method in class org.apache.spark.status.api.v1.StageData
 
accumulatorUpdates() - Method in class org.apache.spark.status.api.v1.TaskData
 
AccumulatorV2<IN,OUT> - Class in org.apache.spark.util
The base class for accumulators, that can accumulate inputs of type IN, and produce output of type OUT.
AccumulatorV2() - Constructor for class org.apache.spark.util.AccumulatorV2
 
accumUpdates() - Method in class org.apache.spark.ExceptionFailure
 
accumUpdates() - Method in class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
 
accumUpdates() - Method in class org.apache.spark.TaskKilled
 
accuracy() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns accuracy.
accuracy() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns accuracy (equals to the total number of correctly classified instances out of the total number of instances.)
accuracy() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
Returns accuracy
acos(Column) - Static method in class org.apache.spark.sql.functions
 
acos(String) - Static method in class org.apache.spark.sql.functions
 
ActivationFunction - Interface in org.apache.spark.ml.ann
Trait for functions and their derivatives for functional layers
active() - Static method in class org.apache.spark.sql.SparkSession
Returns the currently active SparkSession, otherwise the default one.
active() - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
Returns a list of active queries associated with this SQLContext
active() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
 
ACTIVE() - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
 
activeStages() - Method in class org.apache.spark.status.LiveJob
 
activeTasks() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
activeTasks() - Method in class org.apache.spark.status.LiveExecutor
 
activeTasks() - Method in class org.apache.spark.status.LiveJob
 
activeTasks() - Method in class org.apache.spark.status.LiveStage
 
activeTasksPerExecutor() - Method in class org.apache.spark.status.LiveStage
 
add(T) - Method in class org.apache.spark.Accumulable
Deprecated.
Add more data to this accumulator / accumulable
add(Vector) - Method in class org.apache.spark.ml.clustering.ExpectationAggregator
Add a new training instance to this ExpectationAggregator, update the weights, means and covariances for each distributions, and update the log likelihood.
add(Datum) - Method in interface org.apache.spark.ml.optim.aggregator.DifferentiableLossAggregator
Add a single data point to this aggregator.
add(AFTPoint) - Method in class org.apache.spark.ml.regression.AFTAggregator
Add a new training data to this AFTAggregator, and update the loss and gradient of the objective function.
add(double[], MultivariateGaussian[], ExpectationSum, Vector<Object>) - Static method in class org.apache.spark.mllib.clustering.ExpectationSum
 
add(Vector) - Method in class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
Adds a new document.
add(BlockMatrix) - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
Adds the given block matrix other to this block matrix: this + other.
add(Vector) - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
Add a new sample to this summarizer, and update the statistical summary.
add(StructField) - Method in class org.apache.spark.sql.types.StructType
Creates a new StructType by adding a new field.
add(String, DataType) - Method in class org.apache.spark.sql.types.StructType
Creates a new StructType by adding a new nullable field with no metadata.
add(String, DataType, boolean) - Method in class org.apache.spark.sql.types.StructType
Creates a new StructType by adding a new field with no metadata.
add(String, DataType, boolean, Metadata) - Method in class org.apache.spark.sql.types.StructType
Creates a new StructType by adding a new field and specifying metadata.
add(String, DataType, boolean, String) - Method in class org.apache.spark.sql.types.StructType
Creates a new StructType by adding a new field and specifying metadata.
add(String, String) - Method in class org.apache.spark.sql.types.StructType
Creates a new StructType by adding a new nullable field with no metadata where the dataType is specified as a String.
add(String, String, boolean) - Method in class org.apache.spark.sql.types.StructType
Creates a new StructType by adding a new field with no metadata where the dataType is specified as a String.
add(String, String, boolean, Metadata) - Method in class org.apache.spark.sql.types.StructType
Creates a new StructType by adding a new field and specifying metadata where the dataType is specified as a String.
add(String, String, boolean, String) - Method in class org.apache.spark.sql.types.StructType
Creates a new StructType by adding a new field and specifying metadata where the dataType is specified as a String.
add(long, long) - Static method in class org.apache.spark.streaming.util.RawTextHelper
 
add(IN) - Method in class org.apache.spark.util.AccumulatorV2
Takes the inputs and accumulates.
add(T) - Method in class org.apache.spark.util.CollectionAccumulator
 
add(Double) - Method in class org.apache.spark.util.DoubleAccumulator
Adds v to the accumulator, i.e.
add(double) - Method in class org.apache.spark.util.DoubleAccumulator
Adds v to the accumulator, i.e.
add(T) - Method in class org.apache.spark.util.LegacyAccumulatorWrapper
 
add(Long) - Method in class org.apache.spark.util.LongAccumulator
Adds v to the accumulator, i.e.
add(long) - Method in class org.apache.spark.util.LongAccumulator
Adds v to the accumulator, i.e.
add(Object) - Method in class org.apache.spark.util.sketch.CountMinSketch
Increments item's count by one.
add(Object, long) - Method in class org.apache.spark.util.sketch.CountMinSketch
Increments item's count by count.
add_months(Column, int) - Static method in class org.apache.spark.sql.functions
Returns the date that is numMonths after startDate.
addAccumulator(R, T) - Method in interface org.apache.spark.AccumulableParam
Deprecated.
Add additional data to the accumulator value.
addAccumulator(T, T) - Method in interface org.apache.spark.AccumulatorParam
Deprecated.
 
addAppArgs(String...) - Method in class org.apache.spark.launcher.AbstractLauncher
Adds command line arguments for the application.
addAppArgs(String...) - Method in class org.apache.spark.launcher.SparkLauncher
 
addBinary(byte[]) - Method in class org.apache.spark.util.sketch.CountMinSketch
Increments item's count by one.
addBinary(byte[], long) - Method in class org.apache.spark.util.sketch.CountMinSketch
Increments item's count by count.
addDirectory(String, File) - Method in interface org.apache.spark.rpc.RpcEnvFileServer
Adds a local directory to be served via this file server.
addFile(String) - Method in class org.apache.spark.api.java.JavaSparkContext
Add a file to be downloaded with this Spark job on every node.
addFile(String, boolean) - Method in class org.apache.spark.api.java.JavaSparkContext
Add a file to be downloaded with this Spark job on every node.
addFile(String) - Method in class org.apache.spark.launcher.AbstractLauncher
Adds a file to be submitted with the application.
addFile(String) - Method in class org.apache.spark.launcher.SparkLauncher
 
addFile(File) - Method in interface org.apache.spark.rpc.RpcEnvFileServer
Adds a file to be served by this RpcEnv.
addFile(String) - Method in class org.apache.spark.SparkContext
Add a file to be downloaded with this Spark job on every node.
addFile(String, boolean) - Method in class org.apache.spark.SparkContext
Add a file to be downloaded with this Spark job on every node.
addFilters(Seq<ServletContextHandler>, SparkConf) - Static method in class org.apache.spark.ui.JettyUtils
Add filters, if any, to the given list of ServletContextHandlers
addGrid(Param<T>, Iterable<T>) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
Adds a param with multiple values (overwrites if the input param exists).
addGrid(DoubleParam, double[]) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
Adds a double param with multiple values.
addGrid(IntParam, int[]) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
Adds an int param with multiple values.
addGrid(FloatParam, float[]) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
Adds a float param with multiple values.
addGrid(LongParam, long[]) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
Adds a long param with multiple values.
addGrid(BooleanParam) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
Adds a boolean param with true and false.
addInPlace(R, R) - Method in interface org.apache.spark.AccumulableParam
Deprecated.
Merge two accumulated values together.
addInPlace(double, double) - Method in class org.apache.spark.AccumulatorParam.DoubleAccumulatorParam$
Deprecated.
 
addInPlace(float, float) - Method in class org.apache.spark.AccumulatorParam.FloatAccumulatorParam$
Deprecated.
 
addInPlace(int, int) - Method in class org.apache.spark.AccumulatorParam.IntAccumulatorParam$
Deprecated.
 
addInPlace(long, long) - Method in class org.apache.spark.AccumulatorParam.LongAccumulatorParam$
Deprecated.
 
addInPlace(String, String) - Method in class org.apache.spark.AccumulatorParam.StringAccumulatorParam$
Deprecated.
 
addJar(String) - Method in class org.apache.spark.api.java.JavaSparkContext
Adds a JAR dependency for all tasks to be executed on this SparkContext in the future.
addJar(String) - Method in class org.apache.spark.launcher.AbstractLauncher
Adds a jar file to be submitted with the application.
addJar(String) - Method in class org.apache.spark.launcher.SparkLauncher
 
addJar(File) - Method in interface org.apache.spark.rpc.RpcEnvFileServer
Adds a jar to be served by this RpcEnv.
addJar(String) - Method in class org.apache.spark.SparkContext
Adds a JAR dependency for all tasks to be executed on this SparkContext in the future.
addJar(String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Add a jar into class loader
addJar(String) - Method in class org.apache.spark.sql.hive.HiveSessionResourceLoader
 
addListener(SparkAppHandle.Listener) - Method in interface org.apache.spark.launcher.SparkAppHandle
Adds a listener to be notified of changes to the handle's information.
addListener(StreamingQueryListener) - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
Register a StreamingQueryListener to receive up-calls for life cycle events of StreamingQuery.
addListener(L) - Method in interface org.apache.spark.util.ListenerBus
Add a listener to listen events.
addLocalConfiguration(String, int, int, int, JobConf) - Static method in class org.apache.spark.rdd.HadoopRDD
Add Hadoop configuration specific to a single partition and attempt.
addLong(long) - Method in class org.apache.spark.util.sketch.CountMinSketch
Increments item's count by one.
addLong(long, long) - Method in class org.apache.spark.util.sketch.CountMinSketch
Increments item's count by count.
addMapOutput(int, MapStatus) - Method in class org.apache.spark.ShuffleStatus
Register a map output.
addMetrics(TaskMetrics, TaskMetrics) - Static method in class org.apache.spark.status.LiveEntityHelpers
Add m2 values to m1.
addPartition(LiveRDDPartition) - Method in class org.apache.spark.status.RDDPartitionSeq
 
addPartToPGroup(Partition, PartitionGroup) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
 
addPyFile(String) - Method in class org.apache.spark.launcher.AbstractLauncher
Adds a python file / zip / egg to be submitted with the application.
addPyFile(String) - Method in class org.apache.spark.launcher.SparkLauncher
 
address() - Method in class org.apache.spark.BarrierTaskInfo
 
address() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
 
addSchedulable(Schedulable) - Method in interface org.apache.spark.scheduler.Schedulable
 
addShutdownHook(Function0<BoxedUnit>) - Static method in class org.apache.spark.util.ShutdownHookManager
Adds a shutdown hook with default priority.
addShutdownHook(int, Function0<BoxedUnit>) - Static method in class org.apache.spark.util.ShutdownHookManager
Adds a shutdown hook with the given priority.
addSparkArg(String) - Method in class org.apache.spark.launcher.AbstractLauncher
Adds a no-value argument to the Spark invocation.
addSparkArg(String, String) - Method in class org.apache.spark.launcher.AbstractLauncher
Adds an argument with a value to the Spark invocation.
addSparkArg(String) - Method in class org.apache.spark.launcher.SparkLauncher
 
addSparkArg(String, String) - Method in class org.apache.spark.launcher.SparkLauncher
 
addSparkListener(SparkListenerInterface) - Method in class org.apache.spark.SparkContext
:: DeveloperApi :: Register a listener to receive up-calls from events that happen during execution.
addStreamingListener(StreamingListener) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Add a StreamingListener object for receiving system events related to streaming.
addStreamingListener(StreamingListener) - Method in class org.apache.spark.streaming.StreamingContext
Add a StreamingListener object for receiving system events related to streaming.
addString(String) - Method in class org.apache.spark.util.sketch.CountMinSketch
Increments item's count by one.
addString(String, long) - Method in class org.apache.spark.util.sketch.CountMinSketch
Increments item's count by count.
addTaskCompletionListener(TaskCompletionListener) - Method in class org.apache.spark.BarrierTaskContext
 
addTaskCompletionListener(TaskCompletionListener) - Method in class org.apache.spark.TaskContext
Adds a (Java friendly) listener to be executed on task completion.
addTaskCompletionListener(Function1<TaskContext, U>) - Method in class org.apache.spark.TaskContext
Adds a listener in the form of a Scala closure to be executed on task completion.
addTaskFailureListener(TaskFailureListener) - Method in class org.apache.spark.BarrierTaskContext
 
addTaskFailureListener(TaskFailureListener) - Method in class org.apache.spark.TaskContext
Adds a listener to be executed on task failure.
addTaskFailureListener(Function2<TaskContext, Throwable, BoxedUnit>) - Method in class org.apache.spark.TaskContext
Adds a listener to be executed on task failure.
addTaskSetManager(Schedulable, Properties) - Method in interface org.apache.spark.scheduler.SchedulableBuilder
 
addTime() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
addTime() - Method in class org.apache.spark.status.LiveExecutor
 
addURL(URL) - Method in class org.apache.spark.util.MutableURLClassLoader
 
AddWebUIFilter(String, Map<String, String>, String) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
 
AddWebUIFilter$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter$
 
AFTAggregator - Class in org.apache.spark.ml.regression
AFTAggregator computes the gradient and loss for a AFT loss function, as used in AFT survival regression for samples in sparse or dense vector in an online fashion.
AFTAggregator(Broadcast<DenseVector<Object>>, boolean, Broadcast<double[]>) - Constructor for class org.apache.spark.ml.regression.AFTAggregator
 
AFTCostFun - Class in org.apache.spark.ml.regression
AFTCostFun implements Breeze's DiffFunction[T] for AFT cost.
AFTCostFun(RDD<AFTPoint>, boolean, Broadcast<double[]>, int) - Constructor for class org.apache.spark.ml.regression.AFTCostFun
 
AFTSurvivalRegression - Class in org.apache.spark.ml.regression
:: Experimental :: Fit a parametric survival regression model named accelerated failure time (AFT) model (see Accelerated failure time model (Wikipedia)) based on the Weibull distribution of the survival time.
AFTSurvivalRegression(String) - Constructor for class org.apache.spark.ml.regression.AFTSurvivalRegression
 
AFTSurvivalRegression() - Constructor for class org.apache.spark.ml.regression.AFTSurvivalRegression
 
AFTSurvivalRegressionModel - Class in org.apache.spark.ml.regression
:: Experimental :: Model produced by AFTSurvivalRegression.
AFTSurvivalRegressionParams - Interface in org.apache.spark.ml.regression
Params for accelerated failure time (AFT) regression.
agg(Column, Column...) - Method in class org.apache.spark.sql.Dataset
Aggregates on the entire Dataset without groups.
agg(Tuple2<String, String>, Seq<Tuple2<String, String>>) - Method in class org.apache.spark.sql.Dataset
(Scala-specific) Aggregates on the entire Dataset without groups.
agg(Map<String, String>) - Method in class org.apache.spark.sql.Dataset
(Scala-specific) Aggregates on the entire Dataset without groups.
agg(Map<String, String>) - Method in class org.apache.spark.sql.Dataset
(Java-specific) Aggregates on the entire Dataset without groups.
agg(Column, Seq<Column>) - Method in class org.apache.spark.sql.Dataset
Aggregates on the entire Dataset without groups.
agg(TypedColumn<V, U1>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
Computes the given aggregation, returning a Dataset of tuples for each unique key and the result of computing this aggregation over all elements in the group.
agg(TypedColumn<V, U1>, TypedColumn<V, U2>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
Computes the given aggregations, returning a Dataset of tuples for each unique key and the result of computing these aggregations over all elements in the group.
agg(TypedColumn<V, U1>, TypedColumn<V, U2>, TypedColumn<V, U3>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
Computes the given aggregations, returning a Dataset of tuples for each unique key and the result of computing these aggregations over all elements in the group.
agg(TypedColumn<V, U1>, TypedColumn<V, U2>, TypedColumn<V, U3>, TypedColumn<V, U4>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
Computes the given aggregations, returning a Dataset of tuples for each unique key and the result of computing these aggregations over all elements in the group.
agg(Column, Column...) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Compute aggregates by specifying a series of aggregate columns.
agg(Tuple2<String, String>, Seq<Tuple2<String, String>>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
(Scala-specific) Compute aggregates by specifying the column names and aggregate methods.
agg(Map<String, String>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
(Scala-specific) Compute aggregates by specifying a map from column name to aggregate methods.
agg(Map<String, String>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
(Java-specific) Compute aggregates by specifying a map from column name to aggregate methods.
agg(Column, Seq<Column>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Compute aggregates by specifying a series of aggregate columns.
aggregate(U, Function2<U, T, U>, Function2<U, U, U>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Aggregate the elements of each partition, and then the results for all the partitions, using given combine functions and a neutral "zero value".
aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
Aggregate the elements of each partition, and then the results for all the partitions, using given combine functions and a neutral "zero value".
aggregateByKey(U, Partitioner, Function2<U, V, U>, Function2<U, U, U>) - Method in class org.apache.spark.api.java.JavaPairRDD
Aggregate the values of each key, using given combine functions and a neutral "zero value".
aggregateByKey(U, int, Function2<U, V, U>, Function2<U, U, U>) - Method in class org.apache.spark.api.java.JavaPairRDD
Aggregate the values of each key, using given combine functions and a neutral "zero value".
aggregateByKey(U, Function2<U, V, U>, Function2<U, U, U>) - Method in class org.apache.spark.api.java.JavaPairRDD
Aggregate the values of each key, using given combine functions and a neutral "zero value".
aggregateByKey(U, Partitioner, Function2<U, V, U>, Function2<U, U, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Aggregate the values of each key, using given combine functions and a neutral "zero value".
aggregateByKey(U, int, Function2<U, V, U>, Function2<U, U, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Aggregate the values of each key, using given combine functions and a neutral "zero value".
aggregateByKey(U, Function2<U, V, U>, Function2<U, U, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Aggregate the values of each key, using given combine functions and a neutral "zero value".
AggregatedDialect - Class in org.apache.spark.sql.jdbc
AggregatedDialect can unify multiple dialects into one virtual Dialect.
AggregatedDialect(List<JdbcDialect>) - Constructor for class org.apache.spark.sql.jdbc.AggregatedDialect
 
aggregateMessages(Function1<EdgeContext<VD, ED, A>, BoxedUnit>, Function2<A, A, A>, TripletFields, ClassTag<A>) - Method in class org.apache.spark.graphx.Graph
Aggregates values from the neighboring edges and vertices of each vertex.
aggregateMessagesWithActiveSet(Function1<EdgeContext<VD, ED, A>, BoxedUnit>, Function2<A, A, A>, TripletFields, Option<Tuple2<VertexRDD<?>, EdgeDirection>>, ClassTag<A>) - Method in class org.apache.spark.graphx.impl.GraphImpl
 
aggregateUsingIndex(RDD<Tuple2<Object, VD2>>, Function2<VD2, VD2, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
aggregateUsingIndex(RDD<Tuple2<Object, VD2>>, Function2<VD2, VD2, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
Aggregates vertices in messages that have the same ids using reduceFunc, returning a VertexRDD co-indexed with this.
AggregatingEdgeContext<VD,ED,A> - Class in org.apache.spark.graphx.impl
 
AggregatingEdgeContext(Function2<A, A, A>, Object, BitSet) - Constructor for class org.apache.spark.graphx.impl.AggregatingEdgeContext
 
aggregationDepth() - Method in interface org.apache.spark.ml.param.shared.HasAggregationDepth
Param for suggested depth for treeAggregate (&gt;= 2).
Aggregator<K,V,C> - Class in org.apache.spark
:: DeveloperApi :: A set of functions used to aggregate data.
Aggregator(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>) - Constructor for class org.apache.spark.Aggregator
 
aggregator() - Method in class org.apache.spark.ShuffleDependency
 
Aggregator<IN,BUF,OUT> - Class in org.apache.spark.sql.expressions
:: Experimental :: A base class for user-defined aggregations, which can be used in Dataset operations to take all of the elements of a group and reduce them to a single value.
Aggregator() - Constructor for class org.apache.spark.sql.expressions.Aggregator
 
aic(RDD<Tuple3<Object, Object, Object>>, double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
 
aic(RDD<Tuple3<Object, Object, Object>>, double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
 
aic(RDD<Tuple3<Object, Object, Object>>, double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
 
aic(RDD<Tuple3<Object, Object, Object>>, double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
 
aic() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
Akaike Information Criterion (AIC) for the fitted model.
Algo - Class in org.apache.spark.mllib.tree.configuration
Enum to select the algorithm for the decision tree
Algo() - Constructor for class org.apache.spark.mllib.tree.configuration.Algo
 
algo() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
algo() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
 
algo() - Method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
 
algo() - Method in class org.apache.spark.mllib.tree.model.RandomForestModel
 
algorithm() - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
 
alias(String) - Method in class org.apache.spark.sql.Column
Gives the column an alias.
alias(String) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with an alias set.
alias(Symbol) - Method in class org.apache.spark.sql.Dataset
(Scala-specific) Returns a new Dataset with an alias set.
All - Static variable in class org.apache.spark.graphx.TripletFields
Expose all the fields (source, edge, and destination).
AllJobsCancelled - Class in org.apache.spark.scheduler
 
AllJobsCancelled() - Constructor for class org.apache.spark.scheduler.AllJobsCancelled
 
allocator() - Method in class org.apache.spark.storage.memory.SerializedValuesHolder
 
AllReceiverIds - Class in org.apache.spark.streaming.scheduler
A message used by ReceiverTracker to ask all receiver's ids still stored in ReceiverTrackerEndpoint.
AllReceiverIds() - Constructor for class org.apache.spark.streaming.scheduler.AllReceiverIds
 
allSources() - Static method in class org.apache.spark.metrics.source.StaticSources
The set of all static sources.
alpha() - Method in interface org.apache.spark.ml.recommendation.ALSParams
Param for the alpha parameter in the implicit preference formulation (nonnegative).
alpha() - Method in class org.apache.spark.mllib.random.WeibullGenerator
 
ALS - Class in org.apache.spark.ml.recommendation
Alternating Least Squares (ALS) matrix factorization.
ALS(String) - Constructor for class org.apache.spark.ml.recommendation.ALS
 
ALS() - Constructor for class org.apache.spark.ml.recommendation.ALS
 
ALS - Class in org.apache.spark.mllib.recommendation
Alternating Least Squares matrix factorization.
ALS() - Constructor for class org.apache.spark.mllib.recommendation.ALS
Constructs an ALS instance with default parameters: {numBlocks: -1, rank: 10, iterations: 10, lambda: 0.01, implicitPrefs: false, alpha: 1.0}.
ALS.InBlock$ - Class in org.apache.spark.ml.recommendation
 
ALS.LeastSquaresNESolver - Interface in org.apache.spark.ml.recommendation
Trait for least squares solvers applied to the normal equation.
ALS.Rating<ID> - Class in org.apache.spark.ml.recommendation
:: DeveloperApi :: Rating class for better code readability.
ALS.Rating$ - Class in org.apache.spark.ml.recommendation
 
ALS.RatingBlock$ - Class in org.apache.spark.ml.recommendation
 
ALSModel - Class in org.apache.spark.ml.recommendation
Model fitted by ALS.
ALSModelParams - Interface in org.apache.spark.ml.recommendation
Common params for ALS and ALSModel.
ALSParams - Interface in org.apache.spark.ml.recommendation
Common params for ALS.
alterDatabase(CatalogDatabase) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Alter a database whose name matches the one specified in database, assuming it exists.
alterFunction(String, CatalogFunction) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Alter a function whose name matches the one specified in `func`, assuming it exists.
alterPartitions(String, String, Seq<CatalogTablePartition>) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Alter one or more table partitions whose specs match the ones specified in newParts, assuming the partitions exist.
alterTable(CatalogTable) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Alter a table whose name matches the one specified in `table`, assuming it exists.
alterTable(String, String, CatalogTable) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Updates the given table with new metadata, optionally renaming the table or moving across different database.
alterTableDataSchema(String, String, StructType, Map<String, String>) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Updates the given table with a new data schema and table properties, and keep everything else unchanged.
am() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterClusterManager
 
AnalysisException - Exception in org.apache.spark.sql
Thrown when a query fails to analyze, usually because the query itself is invalid.
and(Column) - Method in class org.apache.spark.sql.Column
Boolean AND.
And - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff both left or right evaluate to true.
And(Filter, Filter) - Constructor for class org.apache.spark.sql.sources.And
 
antecedent() - Method in class org.apache.spark.mllib.fpm.AssociationRules.Rule
 
ANY() - Static method in class org.apache.spark.scheduler.TaskLocality
 
AnyDataType - Class in org.apache.spark.sql.types
An AbstractDataType that matches any concrete data types.
AnyDataType() - Constructor for class org.apache.spark.sql.types.AnyDataType
 
anyNull() - Method in interface org.apache.spark.sql.Row
Returns true if there are any NULL values in this row.
anyNull() - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
ApiHelper - Class in org.apache.spark.ui.jobs
 
ApiHelper() - Constructor for class org.apache.spark.ui.jobs.ApiHelper
 
ApiRequestContext - Interface in org.apache.spark.status.api.v1
 
appAttemptId() - Method in class org.apache.spark.scheduler.SparkListenerApplicationStart
 
Append() - Static method in class org.apache.spark.sql.streaming.OutputMode
OutputMode in which only the new rows in the streaming DataFrame/Dataset will be written to the sink.
appendBias(Vector) - Static method in class org.apache.spark.mllib.util.MLUtils
Returns a new vector with 1.0 (bias) appended to the input vector.
appendColumn(StructType, String, DataType, boolean) - Static method in class org.apache.spark.ml.util.SchemaUtils
Appends a new column to the input schema.
appendColumn(StructType, StructField) - Static method in class org.apache.spark.ml.util.SchemaUtils
Appends a new column to the input schema.
appendReadColumns(Configuration, Seq<Integer>, Seq<String>) - Static method in class org.apache.spark.sql.hive.HiveShim
 
AppHistoryServerPlugin - Interface in org.apache.spark.status
An interface for creating history listeners(to replay event logs) defined in other modules like SQL, and setup the UI of the plugin to rebuild the history UI.
appId() - Method in interface org.apache.spark.scheduler.SchedulerBackend
 
appId() - Method in class org.apache.spark.scheduler.SparkListenerApplicationStart
 
appId() - Method in interface org.apache.spark.scheduler.TaskScheduler
 
appId() - Method in interface org.apache.spark.status.api.v1.BaseAppResource
 
APPLICATION_EXECUTOR_LIMIT() - Static method in class org.apache.spark.ui.ToolTips
 
applicationAttemptId() - Method in interface org.apache.spark.scheduler.SchedulerBackend
Get the attempt ID for this run, if the cluster manager supports multiple attempts.
applicationAttemptId() - Method in interface org.apache.spark.scheduler.TaskScheduler
Get an application's attempt ID associated with the job.
applicationAttemptId() - Method in class org.apache.spark.SparkContext
 
ApplicationAttemptInfo - Class in org.apache.spark.status.api.v1
 
applicationEndFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
applicationEndToJson(SparkListenerApplicationEnd) - Static method in class org.apache.spark.util.JsonProtocol
 
ApplicationEnvironmentInfo - Class in org.apache.spark.status.api.v1
 
applicationId() - Method in interface org.apache.spark.scheduler.SchedulerBackend
Get an application ID associated with the job.
applicationId() - Method in interface org.apache.spark.scheduler.TaskScheduler
Get an application ID associated with the job.
applicationId() - Method in class org.apache.spark.SparkContext
A unique identifier for the Spark application.
ApplicationInfo - Class in org.apache.spark.status.api.v1
 
applicationStartFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
applicationStartToJson(SparkListenerApplicationStart) - Static method in class org.apache.spark.util.JsonProtocol
 
ApplicationStatus - Enum in org.apache.spark.status.api.v1
 
apply(T1) - Static method in class org.apache.spark.CleanAccum
 
apply(T1) - Static method in class org.apache.spark.CleanBroadcast
 
apply(T1) - Static method in class org.apache.spark.CleanCheckpoint
 
apply(T1) - Static method in class org.apache.spark.CleanRDD
 
apply(T1) - Static method in class org.apache.spark.CleanShuffle
 
apply(T1, T2) - Static method in class org.apache.spark.ContextBarrierId
 
apply(T1, T2, T3, T4, T5, T6, T7) - Static method in class org.apache.spark.ExceptionFailure
 
apply(T1, T2, T3) - Static method in class org.apache.spark.ExecutorLostFailure
 
apply(T1) - Static method in class org.apache.spark.ExecutorRegistered
 
apply(T1) - Static method in class org.apache.spark.ExecutorRemoved
 
apply(T1, T2, T3, T4, T5) - Static method in class org.apache.spark.FetchFailed
 
apply(RDD<Tuple2<Object, VD>>, RDD<Edge<ED>>, VD, StorageLevel, StorageLevel, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.Graph
Construct a graph from a collection of vertices and edges with attributes.
apply(RDD<Edge<ED>>, VD, StorageLevel, StorageLevel, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
Create a graph from edges, setting referenced vertices to defaultVertexAttr.
apply(RDD<Tuple2<Object, VD>>, RDD<Edge<ED>>, VD, StorageLevel, StorageLevel, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
Create a graph from vertices and edges, setting missing vertices to defaultVertexAttr.
apply(VertexRDD<VD>, EdgeRDD<ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
Create a graph from a VertexRDD and an EdgeRDD with arbitrary replicated vertices.
apply(Graph<VD, ED>, A, int, EdgeDirection, Function3<Object, VD, A, VD>, Function1<EdgeTriplet<VD, ED>, Iterator<Tuple2<Object, A>>>, Function2<A, A, A>, ClassTag<VD>, ClassTag<ED>, ClassTag<A>) - Static method in class org.apache.spark.graphx.Pregel
Execute a Pregel-like iterative vertex-parallel abstraction.
apply(RDD<Tuple2<Object, VD>>, ClassTag<VD>) - Static method in class org.apache.spark.graphx.VertexRDD
Constructs a standalone VertexRDD (one that is not set up for efficient joins with an EdgeRDD) from an RDD of vertex-attribute pairs.
apply(RDD<Tuple2<Object, VD>>, EdgeRDD<?>, VD, ClassTag<VD>) - Static method in class org.apache.spark.graphx.VertexRDD
Constructs a VertexRDD from an RDD of vertex-attribute pairs.
apply(RDD<Tuple2<Object, VD>>, EdgeRDD<?>, VD, Function2<VD, VD, VD>, ClassTag<VD>) - Static method in class org.apache.spark.graphx.VertexRDD
Constructs a VertexRDD from an RDD of vertex-attribute pairs.
apply(DenseMatrix<Object>, DenseMatrix<Object>, Function1<Object, Object>) - Static method in class org.apache.spark.ml.ann.ApplyInPlace
 
apply(DenseMatrix<Object>, DenseMatrix<Object>, DenseMatrix<Object>, Function2<Object, Object, Object>) - Static method in class org.apache.spark.ml.ann.ApplyInPlace
 
apply(String) - Method in class org.apache.spark.ml.attribute.AttributeGroup
Gets an attribute by its name.
apply(int) - Method in class org.apache.spark.ml.attribute.AttributeGroup
Gets an attribute by its index.
apply(T1, T2) - Static method in class org.apache.spark.ml.clustering.ClusterData
 
apply(T1, T2) - Static method in class org.apache.spark.ml.feature.LabeledPoint
 
apply(int, int) - Method in class org.apache.spark.ml.linalg.DenseMatrix
 
apply(int) - Method in class org.apache.spark.ml.linalg.DenseVector
 
apply(int, int) - Method in interface org.apache.spark.ml.linalg.Matrix
Gets the (i, j)-th element.
apply(int, int) - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
apply(int) - Method in class org.apache.spark.ml.linalg.SparseVector
 
apply(int) - Method in interface org.apache.spark.ml.linalg.Vector
Gets the value of the ith element.
apply(Param<T>) - Method in class org.apache.spark.ml.param.ParamMap
Gets the value of the input param or its default value if it does not exist.
apply(GeneralizedLinearRegressionBase) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.FamilyAndLink$
Constructs the FamilyAndLink object from a parameter map
apply(Split) - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData$
 
apply(T1, T2, T3) - Static method in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$.Data
 
apply(T1, T2, T3) - Static method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$.Data
 
apply(T1, T2, T3, T4) - Static method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data
 
apply(BinaryConfusionMatrix) - Method in interface org.apache.spark.mllib.evaluation.binary.BinaryClassificationMetricComputer
 
apply(BinaryConfusionMatrix) - Static method in class org.apache.spark.mllib.evaluation.binary.FalsePositiveRate
 
apply(BinaryConfusionMatrix) - Static method in class org.apache.spark.mllib.evaluation.binary.Precision
 
apply(BinaryConfusionMatrix) - Static method in class org.apache.spark.mllib.evaluation.binary.Recall
 
apply(T1) - Static method in class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$.Data
 
apply(T1, T2, T3, T4, T5) - Static method in class org.apache.spark.mllib.feature.VocabWord
 
apply(int, int) - Method in class org.apache.spark.mllib.linalg.DenseMatrix
 
apply(int) - Method in class org.apache.spark.mllib.linalg.DenseVector
 
apply(T1, T2) - Static method in class org.apache.spark.mllib.linalg.distributed.IndexedRow
 
apply(T1, T2, T3) - Static method in class org.apache.spark.mllib.linalg.distributed.MatrixEntry
 
apply(int, int) - Method in interface org.apache.spark.mllib.linalg.Matrix
Gets the (i, j)-th element.
apply(int, int) - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
apply(int) - Method in class org.apache.spark.mllib.linalg.SparseVector
 
apply(int) - Method in interface org.apache.spark.mllib.linalg.Vector
Gets the value of the ith element.
apply(T1, T2, T3) - Static method in class org.apache.spark.mllib.recommendation.Rating
 
apply(T1, T2) - Static method in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$.Data
 
apply(T1, T2) - Static method in class org.apache.spark.mllib.stat.test.BinarySample
 
apply(int) - Static method in class org.apache.spark.mllib.tree.configuration.Algo
 
apply(int) - Static method in class org.apache.spark.mllib.tree.configuration.EnsembleCombiningStrategy
 
apply(int) - Static method in class org.apache.spark.mllib.tree.configuration.FeatureType
 
apply(int) - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
 
apply(int, Node) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData$
 
apply(Row) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData$
 
apply(int, Node) - Static method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
 
apply(Row) - Static method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
 
apply(Predict) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData$
 
apply(Row) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData$
 
apply(Predict) - Static method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData
 
apply(Row) - Static method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData
 
apply(Split) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData$
 
apply(Row) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData$
 
apply(Split) - Static method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData
 
apply(Row) - Static method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData
 
apply(int, Predict, double, boolean) - Static method in class org.apache.spark.mllib.tree.model.Node
Construct a node with nodeIndex, predict, impurity and isLeaf parameters.
apply(T1, T2, T3, T4) - Static method in class org.apache.spark.mllib.tree.model.Split
 
apply(int) - Static method in class org.apache.spark.rdd.CheckpointState
 
apply(int) - Static method in class org.apache.spark.rdd.DeterministicLevel
 
apply(long, String, Option<String>, String, boolean) - Static method in class org.apache.spark.scheduler.AccumulableInfo
Deprecated.
do not create AccumulableInfo. Since 2.0.0.
apply(long, String, Option<String>, String) - Static method in class org.apache.spark.scheduler.AccumulableInfo
Deprecated.
do not create AccumulableInfo. Since 2.0.0.
apply(long, String, String) - Static method in class org.apache.spark.scheduler.AccumulableInfo
Deprecated.
do not create AccumulableInfo. Since 2.0.0.
apply(T1, T2, T3, T4) - Static method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
 
apply(T1, T2) - Static method in class org.apache.spark.scheduler.BlacklistedExecutor
 
apply(String, long, Enumeration.Value, ByteBuffer) - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate$
Alternate factory method that takes a ByteBuffer directly for the data field
apply(T1, T2, T3) - Static method in class org.apache.spark.scheduler.local.KillTask
 
apply() - Static method in class org.apache.spark.scheduler.local.ReviveOffers
 
apply(T1, T2, T3) - Static method in class org.apache.spark.scheduler.local.StatusUpdate
 
apply() - Static method in class org.apache.spark.scheduler.local.StopExecutor
 
apply(long, TaskMetrics) - Static method in class org.apache.spark.scheduler.RuntimePercentage
 
apply(int) - Static method in class org.apache.spark.scheduler.SchedulingMode
 
apply(T1) - Static method in class org.apache.spark.scheduler.SparkListenerApplicationEnd
 
apply(T1, T2, T3, T4, T5, T6) - Static method in class org.apache.spark.scheduler.SparkListenerApplicationStart
 
apply(T1, T2, T3, T4, T5) - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
 
apply(T1, T2) - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerRemoved
 
apply(T1) - Static method in class org.apache.spark.scheduler.SparkListenerBlockUpdated
 
apply(T1) - Static method in class org.apache.spark.scheduler.SparkListenerEnvironmentUpdate
 
apply(T1, T2, T3) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorAdded
 
apply(T1, T2, T3) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklisted
 
apply(T1, T2, T3, T4, T5) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklistedForStage
 
apply(T1, T2) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
 
apply(T1, T2, T3) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorRemoved
 
apply(T1, T2) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorUnblacklisted
 
apply(T1, T2, T3) - Static method in class org.apache.spark.scheduler.SparkListenerJobEnd
 
apply(T1, T2, T3, T4) - Static method in class org.apache.spark.scheduler.SparkListenerJobStart
 
apply(T1) - Static method in class org.apache.spark.scheduler.SparkListenerLogStart
 
apply(T1, T2, T3) - Static method in class org.apache.spark.scheduler.SparkListenerNodeBlacklisted
 
apply(T1, T2, T3, T4, T5) - Static method in class org.apache.spark.scheduler.SparkListenerNodeBlacklistedForStage
 
apply(T1, T2) - Static method in class org.apache.spark.scheduler.SparkListenerNodeUnblacklisted
 
apply(T1) - Static method in class org.apache.spark.scheduler.SparkListenerSpeculativeTaskSubmitted
 
apply(T1) - Static method in class org.apache.spark.scheduler.SparkListenerStageCompleted
 
apply(T1, T2) - Static method in class org.apache.spark.scheduler.SparkListenerStageSubmitted
 
apply(T1, T2, T3, T4, T5, T6) - Static method in class org.apache.spark.scheduler.SparkListenerTaskEnd
 
apply(T1) - Static method in class org.apache.spark.scheduler.SparkListenerTaskGettingResult
 
apply(T1, T2, T3) - Static method in class org.apache.spark.scheduler.SparkListenerTaskStart
 
apply(T1) - Static method in class org.apache.spark.scheduler.SparkListenerUnpersistRDD
 
apply(int) - Static method in class org.apache.spark.scheduler.TaskLocality
 
apply(Object) - Method in class org.apache.spark.sql.Column
Extracts a value or values from a complex type.
apply(String) - Method in class org.apache.spark.sql.Dataset
Selects column based on the column name and returns it as a Column.
apply(Column...) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
Creates a Column for this UDAF using given Columns as input arguments.
apply(Seq<Column>) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
Creates a Column for this UDAF using given Columns as input arguments.
apply(Column...) - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
Returns an expression that invokes the UDF, using the given arguments.
apply(Seq<Column>) - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
Returns an expression that invokes the UDF, using the given arguments.
apply(LogicalPlan) - Method in class org.apache.spark.sql.hive.DetermineTableStats
 
apply(T1, T2, T3, T4) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
 
apply(ScriptInputOutputSchema) - Static method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
apply(T1, T2, T3, T4, T5) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
 
apply(T1, T2, T3, T4, T5, T6) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
 
apply(T1, T2, T3, T4, T5) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
 
apply(LogicalPlan) - Static method in class org.apache.spark.sql.hive.HiveAnalysis
 
apply(LogicalPlan) - Method in class org.apache.spark.sql.hive.HiveStrategies.HiveTableScans$
 
apply(LogicalPlan) - Static method in class org.apache.spark.sql.hive.HiveStrategies.HiveTableScans
 
apply(LogicalPlan) - Method in class org.apache.spark.sql.hive.HiveStrategies.Scripts$
 
apply(LogicalPlan) - Static method in class org.apache.spark.sql.hive.HiveStrategies.Scripts
 
apply(T1, T2) - Static method in class org.apache.spark.sql.hive.HiveUDAFBuffer
 
apply(LogicalPlan) - Method in class org.apache.spark.sql.hive.RelationConversions
 
apply(LogicalPlan) - Method in class org.apache.spark.sql.hive.ResolveHiveSerdeTable
 
apply(T1, T2) - Static method in class org.apache.spark.sql.jdbc.JdbcType
 
apply(Dataset<Row>, Seq<Expression>, RelationalGroupedDataset.GroupType) - Static method in class org.apache.spark.sql.RelationalGroupedDataset
 
apply(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i.
apply(T1, T2) - Static method in class org.apache.spark.sql.sources.And
 
apply(T1, T2) - Static method in class org.apache.spark.sql.sources.EqualNullSafe
 
apply(T1, T2) - Static method in class org.apache.spark.sql.sources.EqualTo
 
apply(T1, T2) - Static method in class org.apache.spark.sql.sources.GreaterThan
 
apply(T1, T2) - Static method in class org.apache.spark.sql.sources.GreaterThanOrEqual
 
apply(T1, T2) - Static method in class org.apache.spark.sql.sources.In
 
apply(T1) - Static method in class org.apache.spark.sql.sources.IsNotNull
 
apply(T1) - Static method in class org.apache.spark.sql.sources.IsNull
 
apply(T1, T2) - Static method in class org.apache.spark.sql.sources.LessThan
 
apply(T1, T2) - Static method in class org.apache.spark.sql.sources.LessThanOrEqual
 
apply(T1) - Static method in class org.apache.spark.sql.sources.Not
 
apply(T1, T2) - Static method in class org.apache.spark.sql.sources.Or
 
apply(T1, T2) - Static method in class org.apache.spark.sql.sources.StringContains
 
apply(T1, T2) - Static method in class org.apache.spark.sql.sources.StringEndsWith
 
apply(T1, T2) - Static method in class org.apache.spark.sql.sources.StringStartsWith
 
apply(String) - Static method in class org.apache.spark.sql.streaming.ProcessingTime
Deprecated.
use Trigger.ProcessingTime(interval)
apply(Duration) - Static method in class org.apache.spark.sql.streaming.ProcessingTime
Deprecated.
use Trigger.ProcessingTime(interval)
apply(DataType) - Static method in class org.apache.spark.sql.types.ArrayType
Construct a ArrayType object with the given element type.
apply(T1) - Static method in class org.apache.spark.sql.types.CharType
 
apply(double) - Static method in class org.apache.spark.sql.types.Decimal
 
apply(long) - Static method in class org.apache.spark.sql.types.Decimal
 
apply(int) - Static method in class org.apache.spark.sql.types.Decimal
 
apply(BigDecimal) - Static method in class org.apache.spark.sql.types.Decimal
 
apply(BigDecimal) - Static method in class org.apache.spark.sql.types.Decimal
 
apply(BigInteger) - Static method in class org.apache.spark.sql.types.Decimal
 
apply(BigInt) - Static method in class org.apache.spark.sql.types.Decimal
 
apply(BigDecimal, int, int) - Static method in class org.apache.spark.sql.types.Decimal
 
apply(BigDecimal, int, int) - Static method in class org.apache.spark.sql.types.Decimal
 
apply(long, int, int) - Static method in class org.apache.spark.sql.types.Decimal
 
apply(String) - Static method in class org.apache.spark.sql.types.Decimal
 
apply(DataType, DataType) - Static method in class org.apache.spark.sql.types.MapType
Construct a MapType object with the given key type and value type.
apply(T1, T2, T3, T4) - Static method in class org.apache.spark.sql.types.StructField
 
apply(String) - Method in class org.apache.spark.sql.types.StructType
Extracts the StructField with the given name.
apply(Set<String>) - Method in class org.apache.spark.sql.types.StructType
Returns a StructType containing StructFields of the given names, preserving the original order of fields.
apply(int) - Method in class org.apache.spark.sql.types.StructType
 
apply(T1) - Static method in class org.apache.spark.sql.types.VarcharType
 
apply(T1, T2, T3, T4, T5, T6, T7, T8) - Static method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
 
apply(T1, T2, T3, T4, T5, T6, T7) - Static method in class org.apache.spark.status.api.v1.ApplicationInfo
 
apply(T1) - Static method in class org.apache.spark.status.api.v1.StackTrace
 
apply(T1, T2, T3, T4, T5, T6, T7) - Static method in class org.apache.spark.status.api.v1.ThreadStackTrace
 
apply(int) - Method in class org.apache.spark.status.RDDPartitionSeq
 
apply(String) - Static method in class org.apache.spark.storage.BlockId
 
apply(String, String, int, Option<String>) - Static method in class org.apache.spark.storage.BlockManagerId
Returns a BlockManagerId for the given configuration.
apply(ObjectInput) - Static method in class org.apache.spark.storage.BlockManagerId
 
apply(T1, T2) - Static method in class org.apache.spark.storage.BroadcastBlockId
 
apply(T1, T2) - Static method in class org.apache.spark.storage.RDDBlockId
 
apply(T1, T2, T3) - Static method in class org.apache.spark.storage.ShuffleBlockId
 
apply(T1, T2, T3) - Static method in class org.apache.spark.storage.ShuffleDataBlockId
 
apply(T1, T2, T3) - Static method in class org.apache.spark.storage.ShuffleIndexBlockId
 
apply(boolean, boolean, boolean, boolean, int) - Static method in class org.apache.spark.storage.StorageLevel
:: DeveloperApi :: Create a new StorageLevel object.
apply(boolean, boolean, boolean, int) - Static method in class org.apache.spark.storage.StorageLevel
:: DeveloperApi :: Create a new StorageLevel object without setting useOffHeap.
apply(int, int) - Static method in class org.apache.spark.storage.StorageLevel
:: DeveloperApi :: Create a new StorageLevel object from its integer representation.
apply(ObjectInput) - Static method in class org.apache.spark.storage.StorageLevel
:: DeveloperApi :: Read StorageLevel object from ObjectInput stream.
apply(T1, T2) - Static method in class org.apache.spark.storage.StreamBlockId
 
apply(T1) - Static method in class org.apache.spark.storage.TaskResultBlockId
 
apply(T1) - Static method in class org.apache.spark.streaming.Duration
 
apply(long) - Static method in class org.apache.spark.streaming.Milliseconds
 
apply(long) - Static method in class org.apache.spark.streaming.Minutes
 
apply(T1, T2, T3, T4, T5, T6) - Static method in class org.apache.spark.streaming.scheduler.BatchInfo
 
apply(T1, T2, T3, T4, T5, T6, T7) - Static method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
 
apply(T1, T2, T3, T4, T5, T6, T7, T8) - Static method in class org.apache.spark.streaming.scheduler.ReceiverInfo
 
apply(int) - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
 
apply(T1) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchCompleted
 
apply(T1) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchStarted
 
apply(T1) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchSubmitted
 
apply(T1) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationCompleted
 
apply(T1) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationStarted
 
apply(T1) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverError
 
apply(T1) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted
 
apply(T1) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStopped
 
apply(T1) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerStreamingStarted
 
apply(long) - Static method in class org.apache.spark.streaming.Seconds
 
apply(T1, T2, T3) - Static method in class org.apache.spark.TaskCommitDenied
 
apply(T1, T2, T3) - Static method in class org.apache.spark.TaskKilled
 
apply(int) - Static method in class org.apache.spark.TaskState
 
apply(TraversableOnce<Object>) - Static method in class org.apache.spark.util.StatCounter
Build a StatCounter from a list of values.
apply(Seq<Object>) - Static method in class org.apache.spark.util.StatCounter
Build a StatCounter from a list of values passed as variable-length arguments.
ApplyInPlace - Class in org.apache.spark.ml.ann
Implements in-place application of functions in the arrays
ApplyInPlace() - Constructor for class org.apache.spark.ml.ann.ApplyInPlace
 
applySchema(RDD<Row>, StructType) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
Use createDataFrame instead. Since 1.3.0.
applySchema(JavaRDD<Row>, StructType) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
Use createDataFrame instead. Since 1.3.0.
applySchema(RDD<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
Use createDataFrame instead. Since 1.3.0.
applySchema(JavaRDD<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
Use createDataFrame instead. Since 1.3.0.
appName() - Method in class org.apache.spark.api.java.JavaSparkContext
 
appName() - Method in class org.apache.spark.scheduler.SparkListenerApplicationStart
 
appName() - Method in class org.apache.spark.SparkContext
 
appName(String) - Method in class org.apache.spark.sql.SparkSession.Builder
Sets a name for the application, which will be shown in the Spark web UI.
approx_count_distinct(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the approximate number of distinct items in a group.
approx_count_distinct(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the approximate number of distinct items in a group.
approx_count_distinct(Column, double) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the approximate number of distinct items in a group.
approx_count_distinct(String, double) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the approximate number of distinct items in a group.
approxCountDistinct(Column) - Static method in class org.apache.spark.sql.functions
Deprecated.
Use approx_count_distinct. Since 2.1.0.
approxCountDistinct(String) - Static method in class org.apache.spark.sql.functions
Deprecated.
Use approx_count_distinct. Since 2.1.0.
approxCountDistinct(Column, double) - Static method in class org.apache.spark.sql.functions
Deprecated.
Use approx_count_distinct. Since 2.1.0.
approxCountDistinct(String, double) - Static method in class org.apache.spark.sql.functions
Deprecated.
Use approx_count_distinct. Since 2.1.0.
ApproxHist() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
 
ApproximateEvaluator<U,R> - Interface in org.apache.spark.partial
An object that computes a function incrementally by merging in results of type U from multiple tasks.
approxQuantile(String, double[], double) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Calculates the approximate quantiles of a numerical column of a DataFrame.
approxQuantile(String[], double[], double) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Calculates the approximate quantiles of numerical columns of a DataFrame.
appSparkVersion() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
 
AppStatusUtils - Class in org.apache.spark.status
 
AppStatusUtils() - Constructor for class org.apache.spark.status.AppStatusUtils
 
AreaUnderCurve - Class in org.apache.spark.mllib.evaluation
Computes the area under the curve (AUC) using the trapezoidal rule.
AreaUnderCurve() - Constructor for class org.apache.spark.mllib.evaluation.AreaUnderCurve
 
areaUnderPR() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
Computes the area under the precision-recall curve.
areaUnderROC() - Method in interface org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
Computes the area under the receiver operating characteristic (ROC) curve.
areaUnderROC() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
Computes the area under the receiver operating characteristic (ROC) curve.
argmax() - Method in class org.apache.spark.ml.linalg.DenseVector
 
argmax() - Method in class org.apache.spark.ml.linalg.SparseVector
 
argmax() - Method in interface org.apache.spark.ml.linalg.Vector
Find the index of a maximal element.
argmax() - Method in class org.apache.spark.mllib.linalg.DenseVector
 
argmax() - Method in class org.apache.spark.mllib.linalg.SparseVector
 
argmax() - Method in interface org.apache.spark.mllib.linalg.Vector
Find the index of a maximal element.
argString() - Method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
 
array(DataType) - Method in class org.apache.spark.sql.ColumnName
Creates a new StructField of type array.
array(Column...) - Static method in class org.apache.spark.sql.functions
Creates a new array column.
array(String, String...) - Static method in class org.apache.spark.sql.functions
Creates a new array column.
array(Seq<Column>) - Static method in class org.apache.spark.sql.functions
Creates a new array column.
array(String, Seq<String>) - Static method in class org.apache.spark.sql.functions
Creates a new array column.
array() - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
array_contains(Column, Object) - Static method in class org.apache.spark.sql.functions
Returns null if the array is null, true if the array contains value, and false otherwise.
array_distinct(Column) - Static method in class org.apache.spark.sql.functions
Removes duplicate values from the array.
array_except(Column, Column) - Static method in class org.apache.spark.sql.functions
Returns an array of the elements in the first array but not in the second array, without duplicates.
array_intersect(Column, Column) - Static method in class org.apache.spark.sql.functions
Returns an array of the elements in the intersection of the given two arrays, without duplicates.
array_join(Column, String, String) - Static method in class org.apache.spark.sql.functions
Concatenates the elements of column using the delimiter.
array_join(Column, String) - Static method in class org.apache.spark.sql.functions
Concatenates the elements of column using the delimiter.
array_max(Column) - Static method in class org.apache.spark.sql.functions
Returns the maximum value in the array.
array_min(Column) - Static method in class org.apache.spark.sql.functions
Returns the minimum value in the array.
array_position(Column, Object) - Static method in class org.apache.spark.sql.functions
Locates the position of the first occurrence of the value in the given array as long.
array_remove(Column, Object) - Static method in class org.apache.spark.sql.functions
Remove all elements that equal to element from the given array.
array_repeat(Column, Column) - Static method in class org.apache.spark.sql.functions
Creates an array containing the left argument repeated the number of times given by the right argument.
array_repeat(Column, int) - Static method in class org.apache.spark.sql.functions
Creates an array containing the left argument repeated the number of times given by the right argument.
array_sort(Column) - Static method in class org.apache.spark.sql.functions
Sorts the input array in ascending order.
array_union(Column, Column) - Static method in class org.apache.spark.sql.functions
Returns an array of the elements in the union of the given two arrays, without duplicates.
arrayLengthGt(double) - Static method in class org.apache.spark.ml.param.ParamValidators
Check that the array length is greater than lowerBound.
arrays_overlap(Column, Column) - Static method in class org.apache.spark.sql.functions
Returns true if a1 and a2 have at least one non-null element in common.
arrays_zip(Column...) - Static method in class org.apache.spark.sql.functions
Returns a merged array of structs in which the N-th struct contains all N-th values of input arrays.
arrays_zip(Seq<Column>) - Static method in class org.apache.spark.sql.functions
Returns a merged array of structs in which the N-th struct contains all N-th values of input arrays.
ArrayType - Class in org.apache.spark.sql.types
 
ArrayType(DataType, boolean) - Constructor for class org.apache.spark.sql.types.ArrayType
 
arrayValues() - Method in class org.apache.spark.storage.memory.DeserializedValuesHolder
 
ArrowColumnVector - Class in org.apache.spark.sql.vectorized
A column vector backed by Apache Arrow.
ArrowColumnVector(ValueVector) - Constructor for class org.apache.spark.sql.vectorized.ArrowColumnVector
 
as(Encoder<U>) - Method in class org.apache.spark.sql.Column
Provides a type hint about the expected return value of this column.
as(String) - Method in class org.apache.spark.sql.Column
Gives the column an alias.
as(Seq<String>) - Method in class org.apache.spark.sql.Column
(Scala-specific) Assigns the given aliases to the results of a table generating function.
as(String[]) - Method in class org.apache.spark.sql.Column
Assigns the given aliases to the results of a table generating function.
as(Symbol) - Method in class org.apache.spark.sql.Column
Gives the column an alias.
as(String, Metadata) - Method in class org.apache.spark.sql.Column
Gives the column an alias with metadata.
as(Encoder<U>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: Returns a new Dataset where each record has been mapped on to the specified type.
as(String) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with an alias set.
as(Symbol) - Method in class org.apache.spark.sql.Dataset
(Scala-specific) Returns a new Dataset with an alias set.
asBinary() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Convenient method for casting to binary logistic regression summary.
asBreeze() - Method in interface org.apache.spark.ml.linalg.Matrix
Converts to a breeze matrix.
asBreeze() - Method in interface org.apache.spark.ml.linalg.Vector
Converts the instance to a breeze vector.
asBreeze() - Method in interface org.apache.spark.mllib.linalg.Matrix
Converts to a breeze matrix.
asBreeze() - Method in interface org.apache.spark.mllib.linalg.Vector
Converts the instance to a breeze vector.
asc() - Method in class org.apache.spark.sql.Column
Returns a sort expression based on ascending order of the column.
asc(String) - Static method in class org.apache.spark.sql.functions
Returns a sort expression based on ascending order of the column.
asc_nulls_first() - Method in class org.apache.spark.sql.Column
Returns a sort expression based on ascending order of the column, and null values return before non-null values.
asc_nulls_first(String) - Static method in class org.apache.spark.sql.functions
Returns a sort expression based on ascending order of the column, and null values return before non-null values.
asc_nulls_last() - Method in class org.apache.spark.sql.Column
Returns a sort expression based on ascending order of the column, and null values appear after non-null values.
asc_nulls_last(String) - Static method in class org.apache.spark.sql.functions
Returns a sort expression based on ascending order of the column, and null values appear after non-null values.
ascii(Column) - Static method in class org.apache.spark.sql.functions
Computes the numeric value of the first character of the string column, and returns the result as an int column.
asin(Column) - Static method in class org.apache.spark.sql.functions
 
asin(String) - Static method in class org.apache.spark.sql.functions
 
asIterator() - Method in class org.apache.spark.serializer.DeserializationStream
Read the elements of this stream through an iterator.
asJavaPairRDD() - Method in class org.apache.spark.api.r.PairwiseRRDD
 
asJavaRDD() - Method in class org.apache.spark.api.r.RRDD
 
asJavaRDD() - Method in class org.apache.spark.api.r.StringRRDD
 
asKeyValueIterator() - Method in class org.apache.spark.serializer.DeserializationStream
Read the elements of this stream through an iterator over key-value pairs.
AskPermissionToCommitOutput - Class in org.apache.spark.scheduler
 
AskPermissionToCommitOutput(int, int, int, int) - Constructor for class org.apache.spark.scheduler.AskPermissionToCommitOutput
 
askRpcTimeout(SparkConf) - Static method in class org.apache.spark.util.RpcUtils
Returns the default Spark timeout to use for RPC ask operations.
askSlaves() - Method in class org.apache.spark.storage.BlockManagerMessages.GetBlockStatus
 
askSlaves() - Method in class org.apache.spark.storage.BlockManagerMessages.GetMatchingBlockIds
 
asMap() - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
 
asML() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
 
asML() - Method in class org.apache.spark.mllib.linalg.DenseVector
 
asML() - Method in interface org.apache.spark.mllib.linalg.Matrix
Convert this matrix to the new mllib-local representation.
asML() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
asML() - Method in class org.apache.spark.mllib.linalg.SparseVector
 
asML() - Method in interface org.apache.spark.mllib.linalg.Vector
Convert this vector to the new mllib-local representation.
asNondeterministic() - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
Updates UserDefinedFunction to nondeterministic.
asNonNullable() - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
Updates UserDefinedFunction to non-nullable.
asNullable() - Method in class org.apache.spark.sql.types.ObjectType
 
asRDDId() - Method in class org.apache.spark.storage.BlockId
 
assertConf(JobContext, SparkConf) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
 
assertNotSpilled(SparkContext, String, Function0<BoxedUnit>) - Static method in class org.apache.spark.TestUtils
Run some code involving jobs submitted to the given context and assert that the jobs did not spill.
assertSpilled(SparkContext, String, Function0<BoxedUnit>) - Static method in class org.apache.spark.TestUtils
Run some code involving jobs submitted to the given context and assert that the jobs spilled.
assignClusters(Dataset<?>) - Method in class org.apache.spark.ml.clustering.PowerIterationClustering
Run the PIC algorithm and returns a cluster assignment for each input vertex.
Assignment(long, int) - Constructor for class org.apache.spark.mllib.clustering.PowerIterationClustering.Assignment
 
Assignment$() - Constructor for class org.apache.spark.mllib.clustering.PowerIterationClustering.Assignment$
 
assignments() - Method in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel
 
AssociationRules - Class in org.apache.spark.ml.fpm
 
AssociationRules() - Constructor for class org.apache.spark.ml.fpm.AssociationRules
 
associationRules() - Method in class org.apache.spark.ml.fpm.FPGrowthModel
Get association rules fitted using the minConfidence.
AssociationRules - Class in org.apache.spark.mllib.fpm
Generates association rules from a RDD[FreqItemset[Item}.
AssociationRules() - Constructor for class org.apache.spark.mllib.fpm.AssociationRules
Constructs a default instance with default parameters {minConfidence = 0.8}.
AssociationRules.Rule<Item> - Class in org.apache.spark.mllib.fpm
An association rule between sets of items.
ASYNC_TRACKING_ENABLED() - Static method in class org.apache.spark.status.config
 
AsyncEventQueue - Class in org.apache.spark.scheduler
An asynchronous queue for events.
AsyncEventQueue(String, SparkConf, LiveListenerBusMetrics, LiveListenerBus) - Constructor for class org.apache.spark.scheduler.AsyncEventQueue
 
AsyncRDDActions<T> - Class in org.apache.spark.rdd
A set of asynchronous RDD actions available through an implicit conversion.
AsyncRDDActions(RDD<T>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.AsyncRDDActions
 
atan(Column) - Static method in class org.apache.spark.sql.functions
 
atan(String) - Static method in class org.apache.spark.sql.functions
 
atan2(Column, Column) - Static method in class org.apache.spark.sql.functions
 
atan2(Column, String) - Static method in class org.apache.spark.sql.functions
 
atan2(String, Column) - Static method in class org.apache.spark.sql.functions
 
atan2(String, String) - Static method in class org.apache.spark.sql.functions
 
atan2(Column, double) - Static method in class org.apache.spark.sql.functions
 
atan2(String, double) - Static method in class org.apache.spark.sql.functions
 
atan2(double, Column) - Static method in class org.apache.spark.sql.functions
 
atan2(double, String) - Static method in class org.apache.spark.sql.functions
 
attempt() - Method in class org.apache.spark.status.api.v1.TaskData
 
ATTEMPT() - Static method in class org.apache.spark.status.TaskIndexNames
 
attemptId() - Method in class org.apache.spark.scheduler.StageInfo
Deprecated.
Use attemptNumber instead. Since 2.3.0.
attemptId() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
 
attemptId() - Method in interface org.apache.spark.status.api.v1.BaseAppResource
 
attemptId() - Method in class org.apache.spark.status.api.v1.StageData
 
attemptNumber() - Method in class org.apache.spark.BarrierTaskContext
 
attemptNumber() - Method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
 
attemptNumber() - Method in class org.apache.spark.scheduler.StageInfo
 
attemptNumber() - Method in class org.apache.spark.scheduler.TaskInfo
 
attemptNumber() - Method in class org.apache.spark.TaskCommitDenied
 
attemptNumber() - Method in class org.apache.spark.TaskContext
How many times this task has been attempted.
attempts() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
 
AtTimestamp(Date) - Constructor for class org.apache.spark.streaming.kinesis.KinesisInitialPositions.AtTimestamp
 
attr() - Method in class org.apache.spark.graphx.Edge
 
attr() - Method in class org.apache.spark.graphx.EdgeContext
The attribute associated with the edge.
attr() - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
 
Attribute - Class in org.apache.spark.ml.attribute
:: DeveloperApi :: Abstract class for ML attributes.
Attribute() - Constructor for class org.apache.spark.ml.attribute.Attribute
 
attribute() - Method in class org.apache.spark.sql.sources.EqualNullSafe
 
attribute() - Method in class org.apache.spark.sql.sources.EqualTo
 
attribute() - Method in class org.apache.spark.sql.sources.GreaterThan
 
attribute() - Method in class org.apache.spark.sql.sources.GreaterThanOrEqual
 
attribute() - Method in class org.apache.spark.sql.sources.In
 
attribute() - Method in class org.apache.spark.sql.sources.IsNotNull
 
attribute() - Method in class org.apache.spark.sql.sources.IsNull
 
attribute() - Method in class org.apache.spark.sql.sources.LessThan
 
attribute() - Method in class org.apache.spark.sql.sources.LessThanOrEqual
 
attribute() - Method in class org.apache.spark.sql.sources.StringContains
 
attribute() - Method in class org.apache.spark.sql.sources.StringEndsWith
 
attribute() - Method in class org.apache.spark.sql.sources.StringStartsWith
 
AttributeFactory - Interface in org.apache.spark.ml.attribute
Trait for ML attribute factories.
AttributeGroup - Class in org.apache.spark.ml.attribute
:: DeveloperApi :: Attributes that describe a vector ML column.
AttributeGroup(String) - Constructor for class org.apache.spark.ml.attribute.AttributeGroup
Creates an attribute group without attribute info.
AttributeGroup(String, int) - Constructor for class org.apache.spark.ml.attribute.AttributeGroup
Creates an attribute group knowing only the number of attributes.
AttributeGroup(String, Attribute[]) - Constructor for class org.apache.spark.ml.attribute.AttributeGroup
Creates an attribute group with attributes.
AttributeKeys - Class in org.apache.spark.ml.attribute
Keys used to store attributes.
AttributeKeys() - Constructor for class org.apache.spark.ml.attribute.AttributeKeys
 
attributes() - Method in class org.apache.spark.ml.attribute.AttributeGroup
Optional array of attributes.
ATTRIBUTES() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
 
AttributeType - Class in org.apache.spark.ml.attribute
:: DeveloperApi :: An enum-like type for attribute types: AttributeType$.Numeric, AttributeType$.Nominal, and AttributeType$.Binary.
AttributeType(String) - Constructor for class org.apache.spark.ml.attribute.AttributeType
 
attrType() - Method in class org.apache.spark.ml.attribute.Attribute
Attribute type.
attrType() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
 
attrType() - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
attrType() - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
attrType() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
available() - Method in class org.apache.spark.io.NioBufferedFileInputStream
 
available() - Method in class org.apache.spark.io.ReadAheadInputStream
 
available() - Method in class org.apache.spark.storage.BufferReleasingInputStream
 
Average() - Static method in class org.apache.spark.mllib.tree.configuration.EnsembleCombiningStrategy
 
avg(MapFunction<T, Double>) - Static method in class org.apache.spark.sql.expressions.javalang.typed
Average aggregate function.
avg(Function1<IN, Object>) - Static method in class org.apache.spark.sql.expressions.scalalang.typed
Average aggregate function.
avg(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the average of the values in a group.
avg(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the average of the values in a group.
avg(String...) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Compute the mean value for each numeric columns for each group.
avg(Seq<String>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Compute the mean value for each numeric columns for each group.
avg() - Method in class org.apache.spark.util.DoubleAccumulator
Returns the average of elements added to the accumulator.
avg() - Method in class org.apache.spark.util.LongAccumulator
Returns the average of elements added to the accumulator.
avgEventRate() - Method in class org.apache.spark.status.api.v1.streaming.ReceiverInfo
 
avgInputRate() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
avgMetrics() - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
 
avgProcessingTime() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
avgSchedulingDelay() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
avgTotalDelay() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
awaitAnyTermination() - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
Wait until any of the queries on the associated SQLContext has terminated since the creation of the context, or since resetTerminated() was called.
awaitAnyTermination(long) - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
Wait until any of the queries on the associated SQLContext has terminated since the creation of the context, or since resetTerminated() was called.
awaitReady(Awaitable<T>, Duration) - Static method in class org.apache.spark.util.ThreadUtils
Preferred alternative to Await.ready().
awaitResult(Awaitable<T>, Duration) - Static method in class org.apache.spark.util.ThreadUtils
Preferred alternative to Await.result().
awaitTermination() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Waits for the termination of this query, either by query.stop() or by an exception.
awaitTermination(long) - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Waits for the termination of this query, either by query.stop() or by an exception.
awaitTermination() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Wait for the execution to stop.
awaitTermination() - Method in class org.apache.spark.streaming.StreamingContext
Wait for the execution to stop.
awaitTerminationOrTimeout(long) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Wait for the execution to stop.
awaitTerminationOrTimeout(long) - Method in class org.apache.spark.streaming.StreamingContext
Wait for the execution to stop.
axpy(double, Vector, Vector) - Static method in class org.apache.spark.ml.linalg.BLAS
y += a * x
axpy(double, Vector, Vector) - Static method in class org.apache.spark.mllib.linalg.BLAS
y += a * x

B

BACKUP_STANDALONE_MASTER_PREFIX() - Static method in class org.apache.spark.util.Utils
An identifier that backup masters use in their responses.
balanceSlack() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
 
barrier() - Method in class org.apache.spark.BarrierTaskContext
:: Experimental :: Sets a global barrier and waits until all tasks in this stage hit this barrier.
barrier() - Method in class org.apache.spark.rdd.RDD
:: Experimental :: Marks the current stage as a barrier stage, where Spark must launch all tasks together.
BarrierCoordinatorMessage - Interface in org.apache.spark
 
BarrierTaskContext - Class in org.apache.spark
:: Experimental :: A TaskContext with extra contextual info and tooling for tasks in a barrier stage.
BarrierTaskInfo - Class in org.apache.spark
:: Experimental :: Carries all task infos of a barrier task.
base64(Column) - Static method in class org.apache.spark.sql.functions
Computes the BASE64 encoding of a binary column and returns it as a string column.
BaseAppResource - Interface in org.apache.spark.status.api.v1
Base class for resource handlers that use app-specific data.
baseOn(ParamPair<?>...) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
Sets the given parameters in this grid to fixed values.
baseOn(ParamMap) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
Sets the given parameters in this grid to fixed values.
baseOn(Seq<ParamPair<?>>) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
Sets the given parameters in this grid to fixed values.
BaseReadWrite - Interface in org.apache.spark.ml.util
Trait for MLWriter and MLReader.
BaseRelation - Class in org.apache.spark.sql.sources
Represents a collection of tuples with a known schema.
BaseRelation() - Constructor for class org.apache.spark.sql.sources.BaseRelation
 
baseRelationToDataFrame(BaseRelation) - Method in class org.apache.spark.sql.SparkSession
Convert a BaseRelation created for external data sources into a DataFrame.
baseRelationToDataFrame(BaseRelation) - Method in class org.apache.spark.sql.SQLContext
 
BaseRRDD<T,U> - Class in org.apache.spark.api.r
 
BaseRRDD(RDD<T>, int, byte[], String, String, byte[], Broadcast<Object>[], ClassTag<T>, ClassTag<U>) - Constructor for class org.apache.spark.api.r.BaseRRDD
 
BaseStreamingAppResource - Interface in org.apache.spark.status.api.v1.streaming
Base class for streaming API handlers, provides easy access to the streaming listener that holds the app's information.
BasicBlockReplicationPolicy - Class in org.apache.spark.storage
 
BasicBlockReplicationPolicy() - Constructor for class org.apache.spark.storage.BasicBlockReplicationPolicy
 
basicCredentials(String, String) - Method in class org.apache.spark.streaming.kinesis.SparkAWSCredentials.Builder
Use a basic AWS keypair for long-lived authorization.
basicSparkPage(HttpServletRequest, Function0<Seq<Node>>, String, boolean) - Static method in class org.apache.spark.ui.UIUtils
Returns a page with the spark css/js and a simple format.
batchDuration() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
 
batchDuration() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
BATCHES() - Static method in class org.apache.spark.mllib.clustering.StreamingKMeans
 
batchId() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
 
batchId() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
 
BatchInfo - Class in org.apache.spark.status.api.v1.streaming
 
BatchInfo - Class in org.apache.spark.streaming.scheduler
:: DeveloperApi :: Class having information on completed batches.
BatchInfo(Time, Map<Object, StreamInputInfo>, long, Option<Object>, Option<Object>, Map<Object, OutputOperationInfo>) - Constructor for class org.apache.spark.streaming.scheduler.BatchInfo
 
batchInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchCompleted
 
batchInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchStarted
 
batchInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchSubmitted
 
batchInfos() - Method in class org.apache.spark.streaming.scheduler.StatsReportListener
 
BatchStatus - Enum in org.apache.spark.status.api.v1.streaming
 
batchTime() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
 
batchTime() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
 
batchTime() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
 
bbos() - Method in class org.apache.spark.storage.memory.SerializedValuesHolder
 
bean(Class<T>) - Static method in class org.apache.spark.sql.Encoders
Creates an encoder for Java Bean of type T.
beforeFetch(Connection, Map<String, String>) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
 
beforeFetch(Connection, Map<String, String>) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
 
beforeFetch(Connection, Map<String, String>) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
Override connection specific properties to run before a select is made.
beforeFetch(Connection, Map<String, String>) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
 
beforeFetch(Connection, Map<String, String>) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
beforeFetch(Connection, Map<String, String>) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
 
beforeFetch(Connection, Map<String, String>) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
beforeFetch(Connection, Map<String, String>) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
 
beforeFetch(Connection, Map<String, String>) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
BernoulliCellSampler<T> - Class in org.apache.spark.util.random
:: DeveloperApi :: A sampler based on Bernoulli trials for partitioning a data sequence.
BernoulliCellSampler(double, double, boolean) - Constructor for class org.apache.spark.util.random.BernoulliCellSampler
 
BernoulliSampler<T> - Class in org.apache.spark.util.random
:: DeveloperApi :: A sampler based on Bernoulli trials.
BernoulliSampler(double, ClassTag<T>) - Constructor for class org.apache.spark.util.random.BernoulliSampler
 
bestModel() - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
 
bestModel() - Method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
 
beta() - Method in class org.apache.spark.mllib.random.WeibullGenerator
 
between(Object, Object) - Method in class org.apache.spark.sql.Column
True if the current column is between the lower bound and upper bound, inclusive.
bin(Column) - Static method in class org.apache.spark.sql.functions
An expression that returns the string representation of the binary value of the given long column.
bin(String) - Static method in class org.apache.spark.sql.functions
An expression that returns the string representation of the binary value of the given long column.
Binarizer - Class in org.apache.spark.ml.feature
Binarize a column of continuous features given a threshold.
Binarizer(String) - Constructor for class org.apache.spark.ml.feature.Binarizer
 
Binarizer() - Constructor for class org.apache.spark.ml.feature.Binarizer
 
Binary() - Static method in class org.apache.spark.ml.attribute.AttributeType
Binary type.
binary() - Method in interface org.apache.spark.ml.feature.CountVectorizerParams
Binary toggle to control the output vector values.
binary() - Method in class org.apache.spark.ml.feature.HashingTF
Binary toggle to control term frequency counts.
binary() - Method in class org.apache.spark.sql.ColumnName
Creates a new StructField of type binary.
BINARY() - Static method in class org.apache.spark.sql.Encoders
An encoder for arrays of bytes.
BinaryAttribute - Class in org.apache.spark.ml.attribute
:: DeveloperApi :: A binary attribute.
BinaryClassificationEvaluator - Class in org.apache.spark.ml.evaluation
:: Experimental :: Evaluator for binary classification, which expects two input columns: rawPrediction and label.
BinaryClassificationEvaluator(String) - Constructor for class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
 
BinaryClassificationEvaluator() - Constructor for class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
 
BinaryClassificationMetricComputer - Interface in org.apache.spark.mllib.evaluation.binary
Trait for a binary classification evaluation metric computer.
BinaryClassificationMetrics - Class in org.apache.spark.mllib.evaluation
Evaluator for binary classification.
BinaryClassificationMetrics(RDD<Tuple2<Object, Object>>, int) - Constructor for class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
 
BinaryClassificationMetrics(RDD<Tuple2<Object, Object>>) - Constructor for class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
Defaults numBins to 0.
BinaryConfusionMatrix - Interface in org.apache.spark.mllib.evaluation.binary
Trait for a binary confusion matrix.
binaryFiles(String, int) - Method in class org.apache.spark.api.java.JavaSparkContext
Read a directory of binary files from HDFS, a local file system (available on all nodes), or any Hadoop-supported file system URI as a byte array.
binaryFiles(String) - Method in class org.apache.spark.api.java.JavaSparkContext
Read a directory of binary files from HDFS, a local file system (available on all nodes), or any Hadoop-supported file system URI as a byte array.
binaryFiles(String, int) - Method in class org.apache.spark.SparkContext
Get an RDD for a Hadoop-readable dataset as PortableDataStream for each file (useful for binary data)
binaryLabelValidator() - Static method in class org.apache.spark.mllib.util.DataValidators
Function to check if labels used for classification are either zero or one.
BinaryLogisticRegressionSummary - Interface in org.apache.spark.ml.classification
:: Experimental :: Abstraction for binary logistic regression results for a given model.
BinaryLogisticRegressionSummaryImpl - Class in org.apache.spark.ml.classification
Binary logistic regression results for a given model.
BinaryLogisticRegressionSummaryImpl(Dataset<Row>, String, String, String, String) - Constructor for class org.apache.spark.ml.classification.BinaryLogisticRegressionSummaryImpl
 
BinaryLogisticRegressionTrainingSummary - Interface in org.apache.spark.ml.classification
:: Experimental :: Abstraction for binary logistic regression training results.
BinaryLogisticRegressionTrainingSummaryImpl - Class in org.apache.spark.ml.classification
Binary logistic regression training results.
BinaryLogisticRegressionTrainingSummaryImpl(Dataset<Row>, String, String, String, String, double[]) - Constructor for class org.apache.spark.ml.classification.BinaryLogisticRegressionTrainingSummaryImpl
 
binaryMetrics() - Method in interface org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
 
binaryRecords(String, int) - Method in class org.apache.spark.api.java.JavaSparkContext
Load data from a flat binary file, assuming the length of each record is constant.
binaryRecords(String, int, Configuration) - Method in class org.apache.spark.SparkContext
Load data from a flat binary file, assuming the length of each record is constant.
binaryRecordsStream(String, int) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream that monitors a Hadoop-compatible filesystem for new files and reads them as flat binary files with fixed record lengths, yielding byte arrays
binaryRecordsStream(String, int) - Method in class org.apache.spark.streaming.StreamingContext
Create an input stream that monitors a Hadoop-compatible filesystem for new files and reads them as flat binary files, assuming a fixed length per record, generating one byte array per record.
BinarySample - Class in org.apache.spark.mllib.stat.test
Class that represents the group and value of a sample.
BinarySample(boolean, double) - Constructor for class org.apache.spark.mllib.stat.test.BinarySample
 
binarySummary() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
Gets summary of model on training set.
BinaryType - Class in org.apache.spark.sql.types
The data type representing Array[Byte] values.
BinaryType() - Constructor for class org.apache.spark.sql.types.BinaryType
 
BinaryType - Static variable in class org.apache.spark.sql.types.DataTypes
Gets the BinaryType object.
Binomial$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
 
BinomialBounds - Class in org.apache.spark.util.random
Utility functions that help us determine bounds on adjusted sampling rate to guarantee exact sample size with high confidence when sampling without replacement.
BinomialBounds() - Constructor for class org.apache.spark.util.random.BinomialBounds
 
BisectingKMeans - Class in org.apache.spark.ml.clustering
A bisecting k-means algorithm based on the paper "A comparison of document clustering techniques" by Steinbach, Karypis, and Kumar, with modification to fit Spark.
BisectingKMeans(String) - Constructor for class org.apache.spark.ml.clustering.BisectingKMeans
 
BisectingKMeans() - Constructor for class org.apache.spark.ml.clustering.BisectingKMeans
 
BisectingKMeans - Class in org.apache.spark.mllib.clustering
A bisecting k-means algorithm based on the paper "A comparison of document clustering techniques" by Steinbach, Karypis, and Kumar, with modification to fit Spark.
BisectingKMeans() - Constructor for class org.apache.spark.mllib.clustering.BisectingKMeans
Constructs with the default configuration
BisectingKMeansModel - Class in org.apache.spark.ml.clustering
Model fitted by BisectingKMeans.
BisectingKMeansModel - Class in org.apache.spark.mllib.clustering
Clustering model produced by BisectingKMeans.
BisectingKMeansModel(ClusteringTreeNode) - Constructor for class org.apache.spark.mllib.clustering.BisectingKMeansModel
 
BisectingKMeansModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.clustering
 
BisectingKMeansModel.SaveLoadV2_0$ - Class in org.apache.spark.mllib.clustering
 
BisectingKMeansParams - Interface in org.apache.spark.ml.clustering
Common params for BisectingKMeans and BisectingKMeansModel
BisectingKMeansSummary - Class in org.apache.spark.ml.clustering
:: Experimental :: Summary of BisectingKMeans.
bitSize() - Method in class org.apache.spark.util.sketch.BloomFilter
Returns the number of bits in the underlying bit array.
bitwiseAND(Object) - Method in class org.apache.spark.sql.Column
Compute bitwise AND of this expression with another expression.
bitwiseNOT(Column) - Static method in class org.apache.spark.sql.functions
Computes bitwise NOT (~) of a number.
bitwiseOR(Object) - Method in class org.apache.spark.sql.Column
Compute bitwise OR of this expression with another expression.
bitwiseXOR(Object) - Method in class org.apache.spark.sql.Column
Compute bitwise XOR of this expression with another expression.
BLACKLISTED() - Static method in class org.apache.spark.ui.ToolTips
 
BlacklistedExecutor - Class in org.apache.spark.scheduler
 
BlacklistedExecutor(String, long) - Constructor for class org.apache.spark.scheduler.BlacklistedExecutor
 
blackListedExecutors() - Method in class org.apache.spark.status.LiveStage
 
blacklistedInStages() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
blacklistedInStages() - Method in class org.apache.spark.status.LiveExecutor
 
BLAS - Class in org.apache.spark.ml.linalg
BLAS routines for MLlib's vectors and matrices.
BLAS() - Constructor for class org.apache.spark.ml.linalg.BLAS
 
BLAS - Class in org.apache.spark.mllib.linalg
BLAS routines for MLlib's vectors and matrices.
BLAS() - Constructor for class org.apache.spark.mllib.linalg.BLAS
 
BlockData - Interface in org.apache.spark.storage
Abstracts away how blocks are stored and provides different ways to read the underlying block data.
blockedByLock() - Method in class org.apache.spark.status.api.v1.ThreadStackTrace
 
blockedByThreadId() - Method in class org.apache.spark.status.api.v1.ThreadStackTrace
 
BlockEvictionHandler - Interface in org.apache.spark.storage.memory
 
BlockGeneratorListener - Interface in org.apache.spark.streaming.receiver
Listener object for BlockGenerator events
BlockId - Class in org.apache.spark.storage
:: DeveloperApi :: Identifies a particular Block of data, usually associated with a single file.
BlockId() - Constructor for class org.apache.spark.storage.BlockId
 
blockId() - Method in class org.apache.spark.storage.BlockManagerMessages.GetBlockStatus
 
blockId() - Method in class org.apache.spark.storage.BlockManagerMessages.GetLocations
 
blockId() - Method in class org.apache.spark.storage.BlockManagerMessages.GetLocationsAndStatus
 
blockId() - Method in class org.apache.spark.storage.BlockManagerMessages.RemoveBlock
 
blockId() - Method in class org.apache.spark.storage.BlockManagerMessages.ReplicateBlock
 
blockId() - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
 
blockId() - Method in class org.apache.spark.storage.BlockUpdatedInfo
 
blockId() - Method in interface org.apache.spark.streaming.receiver.ReceivedBlockStoreResult
 
blockIds() - Method in class org.apache.spark.storage.BlockManagerMessages.GetLocationsMultipleBlockIds
 
BlockLocationsAndStatus(Seq<BlockManagerId>, BlockStatus) - Constructor for class org.apache.spark.storage.BlockManagerMessages.BlockLocationsAndStatus
 
BlockLocationsAndStatus$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.BlockLocationsAndStatus$
 
blockManager() - Method in class org.apache.spark.SparkEnv
 
blockManagerAddedFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
blockManagerAddedToJson(SparkListenerBlockManagerAdded) - Static method in class org.apache.spark.util.JsonProtocol
 
BlockManagerHeartbeat(BlockManagerId) - Constructor for class org.apache.spark.storage.BlockManagerMessages.BlockManagerHeartbeat
 
BlockManagerHeartbeat$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.BlockManagerHeartbeat$
 
blockManagerId() - Method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
 
blockManagerId() - Method in class org.apache.spark.scheduler.SparkListenerBlockManagerRemoved
 
BlockManagerId - Class in org.apache.spark.storage
:: DeveloperApi :: This class represent a unique identifier for a BlockManager.
BlockManagerId() - Constructor for class org.apache.spark.storage.BlockManagerId
 
blockManagerId() - Method in class org.apache.spark.storage.BlockManagerMessages.BlockManagerHeartbeat
 
blockManagerId() - Method in class org.apache.spark.storage.BlockManagerMessages.GetPeers
 
blockManagerId() - Method in class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager
 
blockManagerId() - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
 
blockManagerId() - Method in class org.apache.spark.storage.BlockUpdatedInfo
 
blockManagerIdCache() - Static method in class org.apache.spark.storage.BlockManagerId
The max cache size is hardcoded to 10000, since the size of a BlockManagerId object is about 48B, the total memory cost should be below 1MB which is feasible.
blockManagerIdFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
blockManagerIdToJson(BlockManagerId) - Static method in class org.apache.spark.util.JsonProtocol
 
BlockManagerMessages - Class in org.apache.spark.storage
 
BlockManagerMessages() - Constructor for class org.apache.spark.storage.BlockManagerMessages
 
BlockManagerMessages.BlockLocationsAndStatus - Class in org.apache.spark.storage
 
BlockManagerMessages.BlockLocationsAndStatus$ - Class in org.apache.spark.storage
 
BlockManagerMessages.BlockManagerHeartbeat - Class in org.apache.spark.storage
 
BlockManagerMessages.BlockManagerHeartbeat$ - Class in org.apache.spark.storage
 
BlockManagerMessages.GetBlockStatus - Class in org.apache.spark.storage
 
BlockManagerMessages.GetBlockStatus$ - Class in org.apache.spark.storage
 
BlockManagerMessages.GetExecutorEndpointRef - Class in org.apache.spark.storage
 
BlockManagerMessages.GetExecutorEndpointRef$ - Class in org.apache.spark.storage
 
BlockManagerMessages.GetLocations - Class in org.apache.spark.storage
 
BlockManagerMessages.GetLocations$ - Class in org.apache.spark.storage
 
BlockManagerMessages.GetLocationsAndStatus - Class in org.apache.spark.storage
 
BlockManagerMessages.GetLocationsAndStatus$ - Class in org.apache.spark.storage
 
BlockManagerMessages.GetLocationsMultipleBlockIds - Class in org.apache.spark.storage
 
BlockManagerMessages.GetLocationsMultipleBlockIds$ - Class in org.apache.spark.storage
 
BlockManagerMessages.GetMatchingBlockIds - Class in org.apache.spark.storage
 
BlockManagerMessages.GetMatchingBlockIds$ - Class in org.apache.spark.storage
 
BlockManagerMessages.GetMemoryStatus$ - Class in org.apache.spark.storage
 
BlockManagerMessages.GetPeers - Class in org.apache.spark.storage
 
BlockManagerMessages.GetPeers$ - Class in org.apache.spark.storage
 
BlockManagerMessages.GetStorageStatus$ - Class in org.apache.spark.storage
 
BlockManagerMessages.HasCachedBlocks - Class in org.apache.spark.storage
 
BlockManagerMessages.HasCachedBlocks$ - Class in org.apache.spark.storage
 
BlockManagerMessages.RegisterBlockManager - Class in org.apache.spark.storage
 
BlockManagerMessages.RegisterBlockManager$ - Class in org.apache.spark.storage
 
BlockManagerMessages.RemoveBlock - Class in org.apache.spark.storage
 
BlockManagerMessages.RemoveBlock$ - Class in org.apache.spark.storage
 
BlockManagerMessages.RemoveBroadcast - Class in org.apache.spark.storage
 
BlockManagerMessages.RemoveBroadcast$ - Class in org.apache.spark.storage
 
BlockManagerMessages.RemoveExecutor - Class in org.apache.spark.storage
 
BlockManagerMessages.RemoveExecutor$ - Class in org.apache.spark.storage
 
BlockManagerMessages.RemoveRdd - Class in org.apache.spark.storage
 
BlockManagerMessages.RemoveRdd$ - Class in org.apache.spark.storage
 
BlockManagerMessages.RemoveShuffle - Class in org.apache.spark.storage
 
BlockManagerMessages.RemoveShuffle$ - Class in org.apache.spark.storage
 
BlockManagerMessages.ReplicateBlock - Class in org.apache.spark.storage
 
BlockManagerMessages.ReplicateBlock$ - Class in org.apache.spark.storage
 
BlockManagerMessages.StopBlockManagerMaster$ - Class in org.apache.spark.storage
 
BlockManagerMessages.ToBlockManagerMaster - Interface in org.apache.spark.storage
 
BlockManagerMessages.ToBlockManagerSlave - Interface in org.apache.spark.storage
 
BlockManagerMessages.TriggerThreadDump$ - Class in org.apache.spark.storage
Driver to Executor message to trigger a thread dump.
BlockManagerMessages.UpdateBlockInfo - Class in org.apache.spark.storage
 
BlockManagerMessages.UpdateBlockInfo$ - Class in org.apache.spark.storage
 
blockManagerRemovedFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
blockManagerRemovedToJson(SparkListenerBlockManagerRemoved) - Static method in class org.apache.spark.util.JsonProtocol
 
BlockMatrix - Class in org.apache.spark.mllib.linalg.distributed
Represents a distributed matrix in blocks of local matrices.
BlockMatrix(RDD<Tuple2<Tuple2<Object, Object>, Matrix>>, int, int, long, long) - Constructor for class org.apache.spark.mllib.linalg.distributed.BlockMatrix
 
BlockMatrix(RDD<Tuple2<Tuple2<Object, Object>, Matrix>>, int, int) - Constructor for class org.apache.spark.mllib.linalg.distributed.BlockMatrix
Alternate constructor for BlockMatrix without the input of the number of rows and columns.
blockName() - Method in class org.apache.spark.status.api.v1.RDDPartitionInfo
 
blockName() - Method in class org.apache.spark.status.LiveRDDPartition
 
BlockNotFoundException - Exception in org.apache.spark.storage
 
BlockNotFoundException(String) - Constructor for exception org.apache.spark.storage.BlockNotFoundException
 
BlockReplicationPolicy - Interface in org.apache.spark.storage
::DeveloperApi:: BlockReplicationPrioritization provides logic for prioritizing a sequence of peers for replicating blocks.
BlockReplicationUtils - Class in org.apache.spark.storage
 
BlockReplicationUtils() - Constructor for class org.apache.spark.storage.BlockReplicationUtils
 
blocks() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
 
blockSize() - Method in interface org.apache.spark.ml.classification.MultilayerPerceptronParams
Block size for stacking input data in matrices to speed up the computation.
BlockStatus - Class in org.apache.spark.storage
 
BlockStatus(StorageLevel, long, long) - Constructor for class org.apache.spark.storage.BlockStatus
 
blockStatusFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
blockStatusToJson(BlockStatus) - Static method in class org.apache.spark.util.JsonProtocol
 
blockUpdatedInfo() - Method in class org.apache.spark.scheduler.SparkListenerBlockUpdated
 
BlockUpdatedInfo - Class in org.apache.spark.storage
:: DeveloperApi :: Stores information about a block status in a block manager.
BlockUpdatedInfo(BlockManagerId, BlockId, StorageLevel, long, long) - Constructor for class org.apache.spark.storage.BlockUpdatedInfo
 
blockUpdatedInfoFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
blockUpdatedInfoToJson(BlockUpdatedInfo) - Static method in class org.apache.spark.util.JsonProtocol
 
blockUpdateFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
blockUpdateToJson(SparkListenerBlockUpdated) - Static method in class org.apache.spark.util.JsonProtocol
 
bloomFilter(String, long, double) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Builds a Bloom filter over a specified column.
bloomFilter(Column, long, double) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Builds a Bloom filter over a specified column.
bloomFilter(String, long, long) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Builds a Bloom filter over a specified column.
bloomFilter(Column, long, long) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Builds a Bloom filter over a specified column.
BloomFilter - Class in org.apache.spark.util.sketch
A Bloom filter is a space-efficient probabilistic data structure that offers an approximate containment test with one-sided error: if it claims that an item is contained in it, this might be in error, but if it claims that an item is not contained in it, then this is definitely true.
BloomFilter() - Constructor for class org.apache.spark.util.sketch.BloomFilter
 
BloomFilter.Version - Enum in org.apache.spark.util.sketch
 
bmAddress() - Method in class org.apache.spark.FetchFailed
 
BOOLEAN() - Static method in class org.apache.spark.sql.Encoders
An encoder for nullable boolean type.
BooleanParam - Class in org.apache.spark.ml.param
:: DeveloperApi :: Specialized version of Param[Boolean] for Java.
BooleanParam(String, String, String) - Constructor for class org.apache.spark.ml.param.BooleanParam
 
BooleanParam(Identifiable, String, String) - Constructor for class org.apache.spark.ml.param.BooleanParam
 
BooleanType - Class in org.apache.spark.sql.types
The data type representing Boolean values.
BooleanType() - Constructor for class org.apache.spark.sql.types.BooleanType
 
BooleanType - Static variable in class org.apache.spark.sql.types.DataTypes
Gets the BooleanType object.
boost(RDD<LabeledPoint>, RDD<LabeledPoint>, BoostingStrategy, boolean, long, String) - Static method in class org.apache.spark.ml.tree.impl.GradientBoostedTrees
Internal method for performing regression using trees as base learners.
BoostingStrategy - Class in org.apache.spark.mllib.tree.configuration
Configuration options for GradientBoostedTrees.
BoostingStrategy(Strategy, Loss, int, double, double) - Constructor for class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
Both() - Static method in class org.apache.spark.graphx.EdgeDirection
Edges originating from *and* arriving at a vertex of interest.
boundaries() - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
Boundaries in increasing order for which predictions are known.
boundaries() - Method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
 
BoundedDouble - Class in org.apache.spark.partial
A Double value with error bars and associated confidence.
BoundedDouble(double, double, double, double) - Constructor for class org.apache.spark.partial.BoundedDouble
 
BreezeUtil - Class in org.apache.spark.ml.ann
In-place DGEMM and DGEMV for Breeze
BreezeUtil() - Constructor for class org.apache.spark.ml.ann.BreezeUtil
 
broadcast(T) - Method in class org.apache.spark.api.java.JavaSparkContext
Broadcast a read-only variable to the cluster, returning a Broadcast object for reading it in distributed functions.
Broadcast<T> - Class in org.apache.spark.broadcast
A broadcast variable.
Broadcast(long, ClassTag<T>) - Constructor for class org.apache.spark.broadcast.Broadcast
 
broadcast(T, ClassTag<T>) - Method in class org.apache.spark.SparkContext
Broadcast a read-only variable to the cluster, returning a Broadcast object for reading it in distributed functions.
broadcast(Dataset<T>) - Static method in class org.apache.spark.sql.functions
Marks a DataFrame as small enough for use in broadcast joins.
BROADCAST() - Static method in class org.apache.spark.storage.BlockId
 
BroadcastBlockId - Class in org.apache.spark.storage
 
BroadcastBlockId(long, String) - Constructor for class org.apache.spark.storage.BroadcastBlockId
 
broadcastCleaned(long) - Method in interface org.apache.spark.CleanerListener
 
BroadcastFactory - Interface in org.apache.spark.broadcast
An interface for all the broadcast implementations in Spark (to allow multiple broadcast implementations).
broadcastId() - Method in class org.apache.spark.CleanBroadcast
 
broadcastId() - Method in class org.apache.spark.storage.BlockManagerMessages.RemoveBroadcast
 
broadcastId() - Method in class org.apache.spark.storage.BroadcastBlockId
 
broadcastManager() - Method in class org.apache.spark.SparkEnv
 
bround(Column) - Static method in class org.apache.spark.sql.functions
Returns the value of the column e rounded to 0 decimal places with HALF_EVEN round mode.
bround(Column, int) - Static method in class org.apache.spark.sql.functions
Round the value of e to scale decimal places with HALF_EVEN round mode if scale is greater than or equal to 0 or at integral part when scale is less than 0.
bucketBy(int, String, String...) - Method in class org.apache.spark.sql.DataFrameWriter
Buckets the output by the given columns.
bucketBy(int, String, Seq<String>) - Method in class org.apache.spark.sql.DataFrameWriter
Buckets the output by the given columns.
BucketedRandomProjectionLSH - Class in org.apache.spark.ml.feature
:: Experimental ::
BucketedRandomProjectionLSH(String) - Constructor for class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
 
BucketedRandomProjectionLSH() - Constructor for class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
 
BucketedRandomProjectionLSHModel - Class in org.apache.spark.ml.feature
:: Experimental ::
BucketedRandomProjectionLSHParams - Interface in org.apache.spark.ml.feature
:: Experimental ::
Bucketizer - Class in org.apache.spark.ml.feature
Bucketizer maps a column of continuous features to a column of feature buckets.
Bucketizer(String) - Constructor for class org.apache.spark.ml.feature.Bucketizer
 
Bucketizer() - Constructor for class org.apache.spark.ml.feature.Bucketizer
 
bucketLength() - Method in interface org.apache.spark.ml.feature.BucketedRandomProjectionLSHParams
The length of each hash bucket, a larger bucket lowers the false negative rate.
buf() - Method in class org.apache.spark.sql.hive.HiveUDAFBuffer
 
buffer() - Method in class org.apache.spark.storage.memory.SerializedMemoryEntry
 
bufferEncoder() - Method in class org.apache.spark.sql.expressions.Aggregator
Specifies the Encoder for the intermediate value type.
BufferReleasingInputStream - Class in org.apache.spark.storage
Helper class that ensures a ManagedBuffer is released upon InputStream.close()
BufferReleasingInputStream(InputStream, ShuffleBlockFetcherIterator) - Constructor for class org.apache.spark.storage.BufferReleasingInputStream
 
bufferSchema() - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
A StructType represents data types of values in the aggregation buffer.
build(Node, int) - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData$
Create DecisionTreeModelReadWrite.NodeData instances for this node and all children.
build(DecisionTreeModel, int) - Method in class org.apache.spark.ml.tree.EnsembleModelReadWrite.EnsembleNodeData$
Create EnsembleModelReadWrite.EnsembleNodeData instances for the given tree.
build() - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
Builds and returns all combinations of parameters specified by the param grid.
build() - Method in class org.apache.spark.sql.types.MetadataBuilder
Builds the Metadata instance.
build() - Method in interface org.apache.spark.storage.memory.MemoryEntryBuilder
 
build() - Method in class org.apache.spark.streaming.kinesis.SparkAWSCredentials.Builder
Returns the appropriate instance of SparkAWSCredentials given the configured parameters.
builder() - Static method in class org.apache.spark.sql.SparkSession
Creates a SparkSession.Builder for constructing a SparkSession.
Builder() - Constructor for class org.apache.spark.sql.SparkSession.Builder
 
Builder() - Constructor for class org.apache.spark.streaming.kinesis.SparkAWSCredentials.Builder
 
buildErrorResponse(Response.Status, String) - Static method in class org.apache.spark.ui.UIUtils
 
buildPools() - Method in interface org.apache.spark.scheduler.SchedulableBuilder
 
buildReader(SparkSession, StructType, StructType, StructType, Seq<Filter>, Map<String, String>, Configuration) - Method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
buildScan(Seq<Attribute>, Seq<Expression>) - Method in interface org.apache.spark.sql.sources.CatalystScan
 
buildScan(String[], Filter[]) - Method in interface org.apache.spark.sql.sources.PrunedFilteredScan
 
buildScan(String[]) - Method in interface org.apache.spark.sql.sources.PrunedScan
 
buildScan() - Method in interface org.apache.spark.sql.sources.TableScan
 
buildTreeFromNodes(DecisionTreeModelReadWrite.NodeData[], String) - Static method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite
Given all data for all nodes in a tree, rebuild the tree.
builtinHiveVersion() - Static method in class org.apache.spark.sql.hive.HiveUtils
The version of hive used internally by Spark SQL.
BYTE() - Static method in class org.apache.spark.api.r.SerializationFormats
 
BYTE() - Static method in class org.apache.spark.sql.Encoders
An encoder for nullable byte type.
BytecodeUtils - Class in org.apache.spark.graphx.util
Includes an utility function to test whether a function accesses a specific attribute of an object.
BytecodeUtils() - Constructor for class org.apache.spark.graphx.util.BytecodeUtils
 
byteFromString(String, ByteUnit) - Static method in class org.apache.spark.internal.config.ConfigHelpers
 
BYTES_READ() - Method in class org.apache.spark.InternalAccumulator.input$
 
BYTES_WRITTEN() - Method in class org.apache.spark.InternalAccumulator.output$
 
BYTES_WRITTEN() - Method in class org.apache.spark.InternalAccumulator.shuffleWrite$
 
bytesRead() - Method in class org.apache.spark.status.api.v1.InputMetricDistributions
 
bytesRead() - Method in class org.apache.spark.status.api.v1.InputMetrics
 
bytesToString(long) - Static method in class org.apache.spark.util.Utils
Convert a quantity in bytes to a human-readable string such as "4.0 MB".
bytesToString(BigInt) - Static method in class org.apache.spark.util.Utils
 
byteStringAsBytes(String) - Static method in class org.apache.spark.util.Utils
Convert a passed byte string (e.g.
byteStringAsGb(String) - Static method in class org.apache.spark.util.Utils
Convert a passed byte string (e.g.
byteStringAsKb(String) - Static method in class org.apache.spark.util.Utils
Convert a passed byte string (e.g.
byteStringAsMb(String) - Static method in class org.apache.spark.util.Utils
Convert a passed byte string (e.g.
bytesWritten() - Method in class org.apache.spark.status.api.v1.OutputMetricDistributions
 
bytesWritten() - Method in class org.apache.spark.status.api.v1.OutputMetrics
 
bytesWritten() - Method in class org.apache.spark.status.api.v1.ShuffleWriteMetrics
 
bytesWritten(long) - Method in interface org.apache.spark.util.logging.RollingPolicy
Notify that bytes have been written
byteToString(long, ByteUnit) - Static method in class org.apache.spark.internal.config.ConfigHelpers
 
ByteType - Class in org.apache.spark.sql.types
The data type representing Byte values.
ByteType() - Constructor for class org.apache.spark.sql.types.ByteType
 
ByteType - Static variable in class org.apache.spark.sql.types.DataTypes
Gets the ByteType object.

C

cache() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Persist this RDD with the default storage level (MEMORY_ONLY).
cache() - Method in class org.apache.spark.api.java.JavaPairRDD
Persist this RDD with the default storage level (MEMORY_ONLY).
cache() - Method in class org.apache.spark.api.java.JavaRDD
Persist this RDD with the default storage level (MEMORY_ONLY).
cache() - Method in class org.apache.spark.graphx.Graph
Caches the vertices and edges associated with this graph at the previously-specified target storage levels, which default to MEMORY_ONLY.
cache() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
Persists the edge partitions using targetStorageLevel, which defaults to MEMORY_ONLY.
cache() - Method in class org.apache.spark.graphx.impl.GraphImpl
 
cache() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
Persists the vertex partitions at targetStorageLevel, which defaults to MEMORY_ONLY.
cache() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
Caches the underlying RDD.
cache() - Method in class org.apache.spark.rdd.RDD
Persist this RDD with the default storage level (MEMORY_ONLY).
cache() - Method in class org.apache.spark.sql.Dataset
Persist this Dataset with the default storage level (MEMORY_AND_DISK).
cache() - Method in class org.apache.spark.streaming.api.java.JavaDStream
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
cache() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
cache() - Method in class org.apache.spark.streaming.dstream.DStream
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
cacheNodeIds() - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
If false, the algorithm will pass trees to executors to match instances with nodes.
cacheSize() - Method in interface org.apache.spark.SparkExecutorInfo
 
cacheSize() - Method in class org.apache.spark.SparkExecutorInfoImpl
 
cacheTable(String) - Method in class org.apache.spark.sql.catalog.Catalog
Caches the specified table in-memory.
cacheTable(String, StorageLevel) - Method in class org.apache.spark.sql.catalog.Catalog
Caches the specified table with the given storage level.
cacheTable(String) - Method in class org.apache.spark.sql.SQLContext
Caches the specified table in-memory.
calculate(DenseVector<Object>) - Method in class org.apache.spark.ml.regression.AFTCostFun
 
calculate(double[], double) - Static method in class org.apache.spark.mllib.tree.impurity.Entropy
:: DeveloperApi :: information calculation for multiclass classification
calculate(double, double, double) - Static method in class org.apache.spark.mllib.tree.impurity.Entropy
:: DeveloperApi :: variance calculation
calculate(double[], double) - Static method in class org.apache.spark.mllib.tree.impurity.Gini
:: DeveloperApi :: information calculation for multiclass classification
calculate(double, double, double) - Static method in class org.apache.spark.mllib.tree.impurity.Gini
:: DeveloperApi :: variance calculation
calculate(double[], double) - Method in interface org.apache.spark.mllib.tree.impurity.Impurity
:: DeveloperApi :: information calculation for multiclass classification
calculate(double, double, double) - Method in interface org.apache.spark.mllib.tree.impurity.Impurity
:: DeveloperApi :: information calculation for regression
calculate(double[], double) - Static method in class org.apache.spark.mllib.tree.impurity.Variance
:: DeveloperApi :: information calculation for multiclass classification
calculate(double, double, double) - Static method in class org.apache.spark.mllib.tree.impurity.Variance
:: DeveloperApi :: variance calculation
calculateNumberOfPartitions(long, int, int) - Method in class org.apache.spark.ml.feature.Word2VecModel.Word2VecModelWriter$
Calculate the number of partitions to use in saving the model.
CalendarIntervalType - Class in org.apache.spark.sql.types
The data type representing calendar time intervals.
CalendarIntervalType() - Constructor for class org.apache.spark.sql.types.CalendarIntervalType
 
CalendarIntervalType - Static variable in class org.apache.spark.sql.types.DataTypes
Gets the CalendarIntervalType object.
call(K, Iterator<V1>, Iterator<V2>) - Method in interface org.apache.spark.api.java.function.CoGroupFunction
 
call(T) - Method in interface org.apache.spark.api.java.function.DoubleFlatMapFunction
 
call(T) - Method in interface org.apache.spark.api.java.function.DoubleFunction
 
call(T) - Method in interface org.apache.spark.api.java.function.FilterFunction
 
call(T) - Method in interface org.apache.spark.api.java.function.FlatMapFunction
 
call(T1, T2) - Method in interface org.apache.spark.api.java.function.FlatMapFunction2
 
call(K, Iterator<V>) - Method in interface org.apache.spark.api.java.function.FlatMapGroupsFunction
 
call(K, Iterator<V>, GroupState<S>) - Method in interface org.apache.spark.api.java.function.FlatMapGroupsWithStateFunction
 
call(T) - Method in interface org.apache.spark.api.java.function.ForeachFunction
 
call(Iterator<T>) - Method in interface org.apache.spark.api.java.function.ForeachPartitionFunction
 
call(T1) - Method in interface org.apache.spark.api.java.function.Function
 
call() - Method in interface org.apache.spark.api.java.function.Function0
 
call(T1, T2) - Method in interface org.apache.spark.api.java.function.Function2
 
call(T1, T2, T3) - Method in interface org.apache.spark.api.java.function.Function3
 
call(T1, T2, T3, T4) - Method in interface org.apache.spark.api.java.function.Function4
 
call(T) - Method in interface org.apache.spark.api.java.function.MapFunction
 
call(K, Iterator<V>) - Method in interface org.apache.spark.api.java.function.MapGroupsFunction
 
call(K, Iterator<V>, GroupState<S>) - Method in interface org.apache.spark.api.java.function.MapGroupsWithStateFunction
 
call(Iterator<T>) - Method in interface org.apache.spark.api.java.function.MapPartitionsFunction
 
call(T) - Method in interface org.apache.spark.api.java.function.PairFlatMapFunction
 
call(T) - Method in interface org.apache.spark.api.java.function.PairFunction
 
call(T, T) - Method in interface org.apache.spark.api.java.function.ReduceFunction
 
call(T) - Method in interface org.apache.spark.api.java.function.VoidFunction
 
call(T1, T2) - Method in interface org.apache.spark.api.java.function.VoidFunction2
 
call() - Method in interface org.apache.spark.sql.api.java.UDF0
 
call(T1) - Method in interface org.apache.spark.sql.api.java.UDF1
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10) - Method in interface org.apache.spark.sql.api.java.UDF10
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11) - Method in interface org.apache.spark.sql.api.java.UDF11
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12) - Method in interface org.apache.spark.sql.api.java.UDF12
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13) - Method in interface org.apache.spark.sql.api.java.UDF13
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14) - Method in interface org.apache.spark.sql.api.java.UDF14
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15) - Method in interface org.apache.spark.sql.api.java.UDF15
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16) - Method in interface org.apache.spark.sql.api.java.UDF16
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16, T17) - Method in interface org.apache.spark.sql.api.java.UDF17
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16, T17, T18) - Method in interface org.apache.spark.sql.api.java.UDF18
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16, T17, T18, T19) - Method in interface org.apache.spark.sql.api.java.UDF19
 
call(T1, T2) - Method in interface org.apache.spark.sql.api.java.UDF2
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16, T17, T18, T19, T20) - Method in interface org.apache.spark.sql.api.java.UDF20
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16, T17, T18, T19, T20, T21) - Method in interface org.apache.spark.sql.api.java.UDF21
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16, T17, T18, T19, T20, T21, T22) - Method in interface org.apache.spark.sql.api.java.UDF22
 
call(T1, T2, T3) - Method in interface org.apache.spark.sql.api.java.UDF3
 
call(T1, T2, T3, T4) - Method in interface org.apache.spark.sql.api.java.UDF4
 
call(T1, T2, T3, T4, T5) - Method in interface org.apache.spark.sql.api.java.UDF5
 
call(T1, T2, T3, T4, T5, T6) - Method in interface org.apache.spark.sql.api.java.UDF6
 
call(T1, T2, T3, T4, T5, T6, T7) - Method in interface org.apache.spark.sql.api.java.UDF7
 
call(T1, T2, T3, T4, T5, T6, T7, T8) - Method in interface org.apache.spark.sql.api.java.UDF8
 
call(T1, T2, T3, T4, T5, T6, T7, T8, T9) - Method in interface org.apache.spark.sql.api.java.UDF9
 
callSite() - Method in class org.apache.spark.storage.RDDInfo
 
callUDF(String, Column...) - Static method in class org.apache.spark.sql.functions
Call an user-defined function.
callUDF(String, Seq<Column>) - Static method in class org.apache.spark.sql.functions
Call an user-defined function.
cancel() - Method in class org.apache.spark.ComplexFutureAction
 
cancel() - Method in interface org.apache.spark.FutureAction
Cancels the execution of this action.
cancel() - Method in class org.apache.spark.SimpleFutureAction
 
cancelAllJobs() - Method in class org.apache.spark.api.java.JavaSparkContext
Cancel all jobs that have been scheduled or are running.
cancelAllJobs() - Method in class org.apache.spark.SparkContext
Cancel all jobs that have been scheduled or are running.
cancelJob(int, String) - Method in class org.apache.spark.SparkContext
Cancel a given job if it's scheduled or running.
cancelJob(int) - Method in class org.apache.spark.SparkContext
Cancel a given job if it's scheduled or running.
cancelJobGroup(String) - Method in class org.apache.spark.api.java.JavaSparkContext
Cancel active jobs for the specified group.
cancelJobGroup(String) - Method in class org.apache.spark.SparkContext
Cancel active jobs for the specified group.
cancelStage(int, String) - Method in class org.apache.spark.SparkContext
Cancel a given stage and all jobs associated with it.
cancelStage(int) - Method in class org.apache.spark.SparkContext
Cancel a given stage and all jobs associated with it.
cancelTasks(int, boolean) - Method in interface org.apache.spark.scheduler.TaskScheduler
 
canCreate(String) - Method in interface org.apache.spark.scheduler.ExternalClusterManager
Check if this cluster manager instance can create scheduler components for a certain master URL.
canDoMerge() - Method in class org.apache.spark.sql.hive.HiveUDAFBuffer
 
canEqual(Object) - Static method in class org.apache.spark.ExpireDeadHosts
 
canEqual(Object) - Static method in class org.apache.spark.ml.feature.Dot
 
canEqual(Object) - Static method in class org.apache.spark.Resubmitted
 
canEqual(Object) - Static method in class org.apache.spark.rpc.netty.OnStart
 
canEqual(Object) - Static method in class org.apache.spark.rpc.netty.OnStop
 
canEqual(Object) - Static method in class org.apache.spark.scheduler.AllJobsCancelled
 
canEqual(Object) - Method in class org.apache.spark.scheduler.cluster.ExecutorInfo
 
canEqual(Object) - Static method in class org.apache.spark.scheduler.JobSucceeded
 
canEqual(Object) - Static method in class org.apache.spark.scheduler.ResubmitFailedStages
 
canEqual(Object) - Static method in class org.apache.spark.scheduler.StopCoordinator
 
canEqual(Object) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
canEqual(Object) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
canEqual(Object) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
canEqual(Object) - Static method in class org.apache.spark.sql.types.BinaryType
 
canEqual(Object) - Static method in class org.apache.spark.sql.types.BooleanType
 
canEqual(Object) - Static method in class org.apache.spark.sql.types.ByteType
 
canEqual(Object) - Static method in class org.apache.spark.sql.types.CalendarIntervalType
 
canEqual(Object) - Static method in class org.apache.spark.sql.types.DateType
 
canEqual(Object) - Static method in class org.apache.spark.sql.types.DoubleType
 
canEqual(Object) - Static method in class org.apache.spark.sql.types.FloatType
 
canEqual(Object) - Static method in class org.apache.spark.sql.types.IntegerType
 
canEqual(Object) - Static method in class org.apache.spark.sql.types.LongType
 
canEqual(Object) - Static method in class org.apache.spark.sql.types.NullType
 
canEqual(Object) - Static method in class org.apache.spark.sql.types.ShortType
 
canEqual(Object) - Static method in class org.apache.spark.sql.types.StringType
 
canEqual(Object) - Static method in class org.apache.spark.sql.types.TimestampType
 
canEqual(Object) - Static method in class org.apache.spark.StopMapOutputTracker
 
canEqual(Object) - Static method in class org.apache.spark.streaming.kinesis.DefaultCredentials
 
canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.AllReceiverIds
 
canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
 
canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StopAllReceivers
 
canEqual(Object) - Static method in class org.apache.spark.Success
 
canEqual(Object) - Static method in class org.apache.spark.TaskResultLost
 
canEqual(Object) - Static method in class org.apache.spark.TaskSchedulerIsSet
 
canEqual(Object) - Static method in class org.apache.spark.UnknownReason
 
canEqual(Object) - Method in class org.apache.spark.util.MutablePair
 
canHandle(String) - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
 
canHandle(String) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
 
canHandle(String) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
 
canHandle(String) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
Check if this dialect instance can handle a certain jdbc url.
canHandle(String) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
 
canHandle(String) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
canHandle(String) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
 
canHandle(String) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
canHandle(String) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
 
canHandle(String) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
CanonicalRandomVertexCut$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.CanonicalRandomVertexCut$
 
canWrite(DataType, DataType, Function2<String, String, Object>, String, Function1<String, BoxedUnit>) - Static method in class org.apache.spark.sql.types.DataType
Returns true if the write data type can be read using the read data type.
cartesian(JavaRDDLike<U, ?>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return the Cartesian product of this RDD and another one, that is, the RDD of all pairs of elements (a, b) where a is in this and b is in other.
cartesian(RDD<U>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
Return the Cartesian product of this RDD and another one, that is, the RDD of all pairs of elements (a, b) where a is in this and b is in other.
caseSensitive() - Method in class org.apache.spark.ml.feature.StopWordsRemover
Whether to do a case sensitive comparison over the stop words.
cast(DataType) - Method in class org.apache.spark.sql.Column
Casts the column to a different data type.
cast(String) - Method in class org.apache.spark.sql.Column
Casts the column to a different data type, using the canonical string representation of the type.
Catalog - Class in org.apache.spark.sql.catalog
Catalog interface for Spark.
Catalog() - Constructor for class org.apache.spark.sql.catalog.Catalog
 
catalog() - Method in class org.apache.spark.sql.SparkSession
Interface through which the user may create, drop, alter or query underlying databases, tables, functions etc.
catalogString() - Method in class org.apache.spark.sql.types.ArrayType
 
catalogString() - Static method in class org.apache.spark.sql.types.BinaryType
 
catalogString() - Static method in class org.apache.spark.sql.types.BooleanType
 
catalogString() - Static method in class org.apache.spark.sql.types.ByteType
 
catalogString() - Static method in class org.apache.spark.sql.types.CalendarIntervalType
 
catalogString() - Method in class org.apache.spark.sql.types.DataType
String representation for the type saved in external catalogs.
catalogString() - Static method in class org.apache.spark.sql.types.DateType
 
catalogString() - Static method in class org.apache.spark.sql.types.DoubleType
 
catalogString() - Static method in class org.apache.spark.sql.types.FloatType
 
catalogString() - Static method in class org.apache.spark.sql.types.IntegerType
 
catalogString() - Static method in class org.apache.spark.sql.types.LongType
 
catalogString() - Method in class org.apache.spark.sql.types.MapType
 
catalogString() - Static method in class org.apache.spark.sql.types.NullType
 
catalogString() - Static method in class org.apache.spark.sql.types.ShortType
 
catalogString() - Static method in class org.apache.spark.sql.types.StringType
 
catalogString() - Method in class org.apache.spark.sql.types.StructType
 
catalogString() - Static method in class org.apache.spark.sql.types.TimestampType
 
CatalystScan - Interface in org.apache.spark.sql.sources
::Experimental:: An interface for experimenting with a more direct connection to the query planner.
Categorical() - Static method in class org.apache.spark.mllib.tree.configuration.FeatureType
 
categoricalCols() - Method in class org.apache.spark.ml.feature.FeatureHasher
Numeric columns to treat as categorical features.
categoricalFeaturesInfo() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
CategoricalSplit - Class in org.apache.spark.ml.tree
Split which tests a categorical feature.
categories() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData
 
categories() - Method in class org.apache.spark.mllib.tree.model.Split
 
categoryMaps() - Method in class org.apache.spark.ml.feature.VectorIndexerModel
 
categorySizes() - Method in class org.apache.spark.ml.feature.OneHotEncoderModel
 
cause() - Method in exception org.apache.spark.sql.AnalysisException
 
cause() - Method in exception org.apache.spark.sql.streaming.StreamingQueryException
 
CausedBy - Class in org.apache.spark.util
Extractor Object for pulling out the root cause of an error.
CausedBy() - Constructor for class org.apache.spark.util.CausedBy
 
cbrt(Column) - Static method in class org.apache.spark.sql.functions
Computes the cube-root of the given value.
cbrt(String) - Static method in class org.apache.spark.sql.functions
Computes the cube-root of the given column.
ceil(Column) - Static method in class org.apache.spark.sql.functions
Computes the ceiling of the given value.
ceil(String) - Static method in class org.apache.spark.sql.functions
Computes the ceiling of the given column.
ceil() - Method in class org.apache.spark.sql.types.Decimal
 
censorCol() - Method in interface org.apache.spark.ml.regression.AFTSurvivalRegressionParams
Param for censor column name.
chainl1(Function0<Parsers.Parser<T>>, Function0<Parsers.Parser<Function2<T, T, T>>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
chainl1(Function0<Parsers.Parser<T>>, Function0<Parsers.Parser<U>>, Function0<Parsers.Parser<Function2<T, U, T>>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
chainr1(Function0<Parsers.Parser<T>>, Function0<Parsers.Parser<Function2<T, U, U>>>, Function2<T, U, U>, U) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
changePrecision(int, int) - Method in class org.apache.spark.sql.types.Decimal
Update precision and scale while keeping our value the same, and return true if successful.
channelRead0(ChannelHandlerContext, byte[]) - Method in class org.apache.spark.api.r.RBackendAuthHandler
 
CharType - Class in org.apache.spark.sql.types
Hive char type.
CharType(int) - Constructor for class org.apache.spark.sql.types.CharType
 
checkAndGetK8sMasterUrl(String) - Static method in class org.apache.spark.util.Utils
Check the validity of the given Kubernetes master URL and return the resolved URL.
checkColumnNameDuplication(Seq<String>, String, Function2<String, String, Object>) - Static method in class org.apache.spark.sql.util.SchemaUtils
Checks if input column names have duplicate identifiers.
checkColumnNameDuplication(Seq<String>, String, boolean) - Static method in class org.apache.spark.sql.util.SchemaUtils
Checks if input column names have duplicate identifiers.
checkColumnType(StructType, String, DataType, String) - Static method in class org.apache.spark.ml.util.SchemaUtils
Check whether the given schema contains a column of the required data type.
checkColumnTypes(StructType, String, Seq<DataType>, String) - Static method in class org.apache.spark.ml.util.SchemaUtils
Check whether the given schema contains a column of one of the require data types.
checkDataColumns(RFormula, Dataset<?>) - Static method in class org.apache.spark.ml.r.RWrapperUtils
DataFrame column check.
checkedCast() - Method in interface org.apache.spark.ml.recommendation.ALSModelParams
Attempts to safely cast a user/item id to an Int.
checkFileExists(String, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
Check if the file exists at the given path.
checkHost(String) - Static method in class org.apache.spark.util.Utils
 
checkHostPort(String) - Static method in class org.apache.spark.util.Utils
 
checkNumericType(StructType, String, String) - Static method in class org.apache.spark.ml.util.SchemaUtils
Check whether the given schema contains a column of the numeric data type.
checkpoint() - Method in interface org.apache.spark.api.java.JavaRDDLike
Mark this RDD for checkpointing.
checkpoint() - Method in class org.apache.spark.graphx.Graph
Mark this Graph for checkpointing.
checkpoint() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
checkpoint() - Method in class org.apache.spark.graphx.impl.GraphImpl
 
checkpoint() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
checkpoint() - Method in class org.apache.spark.rdd.HadoopRDD
 
checkpoint() - Method in class org.apache.spark.rdd.RDD
Mark this RDD for checkpointing.
checkpoint() - Method in class org.apache.spark.sql.Dataset
Eagerly checkpoint a Dataset and return the new Dataset.
checkpoint(boolean) - Method in class org.apache.spark.sql.Dataset
Returns a checkpointed version of this Dataset.
checkpoint(Duration) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Enable periodic checkpointing of RDDs of this DStream.
checkpoint(String) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Sets the context to periodically checkpoint the DStream operations for master fault-tolerance.
checkpoint(Duration) - Method in class org.apache.spark.streaming.dstream.DStream
Enable periodic checkpointing of RDDs of this DStream
checkpoint(String) - Method in class org.apache.spark.streaming.StreamingContext
Set the context to periodically checkpoint the DStream operations for driver fault-tolerance.
checkpointCleaned(long) - Method in interface org.apache.spark.CleanerListener
 
Checkpointed() - Static method in class org.apache.spark.rdd.CheckpointState
 
CheckpointingInProgress() - Static method in class org.apache.spark.rdd.CheckpointState
 
checkpointInterval() - Method in interface org.apache.spark.ml.param.shared.HasCheckpointInterval
Param for set checkpoint interval (&gt;= 1) or disable checkpoint (-1).
checkpointInterval() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
CheckpointReader - Class in org.apache.spark.streaming
 
CheckpointReader() - Constructor for class org.apache.spark.streaming.CheckpointReader
 
CheckpointState - Class in org.apache.spark.rdd
Enumeration to manage state transitions of an RDD through checkpointing
CheckpointState() - Constructor for class org.apache.spark.rdd.CheckpointState
 
checkSchemaColumnNameDuplication(StructType, String, boolean) - Static method in class org.apache.spark.sql.util.SchemaUtils
Checks if an input schema has duplicate column names.
checkSingleVsMultiColumnParams(Params, Seq<Param<?>>, Seq<Param<?>>) - Static method in class org.apache.spark.ml.param.ParamValidators
Utility for Param validity checks for Transformers which have both single- and multi-column support.
checkSpeculatableTasks(int) - Method in interface org.apache.spark.scheduler.Schedulable
 
checkState(boolean, Function0<String>) - Static method in class org.apache.spark.streaming.util.HdfsUtils
 
checkThresholdConsistency() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
If threshold and thresholds are both set, ensures they are consistent.
child() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
 
child() - Method in class org.apache.spark.sql.sources.Not
 
CHILD_CONNECTION_TIMEOUT - Static variable in class org.apache.spark.launcher.SparkLauncher
Maximum time (in ms) to wait for a child process to connect back to the launcher server when using @link{#start()}.
CHILD_PROCESS_LOGGER_NAME - Static variable in class org.apache.spark.launcher.SparkLauncher
Logger name to use when launching a child process.
ChildFirstURLClassLoader - Class in org.apache.spark.util
A mutable class loader that gives preference to its own URLs over the parent class loader when loading classes and resources.
ChildFirstURLClassLoader(URL[], ClassLoader) - Constructor for class org.apache.spark.util.ChildFirstURLClassLoader
 
chiSqFunc() - Method in class org.apache.spark.mllib.stat.test.ChiSqTest.Method
 
ChiSqSelector - Class in org.apache.spark.ml.feature
Chi-Squared feature selection, which selects categorical features to use for predicting a categorical label.
ChiSqSelector(String) - Constructor for class org.apache.spark.ml.feature.ChiSqSelector
 
ChiSqSelector() - Constructor for class org.apache.spark.ml.feature.ChiSqSelector
 
ChiSqSelector - Class in org.apache.spark.mllib.feature
Creates a ChiSquared feature selector.
ChiSqSelector() - Constructor for class org.apache.spark.mllib.feature.ChiSqSelector
 
ChiSqSelector(int) - Constructor for class org.apache.spark.mllib.feature.ChiSqSelector
The is the same to call this() and setNumTopFeatures(numTopFeatures)
ChiSqSelectorModel - Class in org.apache.spark.ml.feature
Model fitted by ChiSqSelector.
ChiSqSelectorModel - Class in org.apache.spark.mllib.feature
Chi Squared selector model.
ChiSqSelectorModel(int[]) - Constructor for class org.apache.spark.mllib.feature.ChiSqSelectorModel
 
ChiSqSelectorModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.feature
 
ChiSqSelectorModel.SaveLoadV1_0$.Data - Class in org.apache.spark.mllib.feature
Model data for import/export
ChiSqSelectorModel.SaveLoadV1_0$.Data$ - Class in org.apache.spark.mllib.feature
 
ChiSqSelectorParams - Interface in org.apache.spark.ml.feature
chiSqTest(Vector, Vector) - Static method in class org.apache.spark.mllib.stat.Statistics
Conduct Pearson's chi-squared goodness of fit test of the observed data against the expected distribution.
chiSqTest(Vector) - Static method in class org.apache.spark.mllib.stat.Statistics
Conduct Pearson's chi-squared goodness of fit test of the observed data against the uniform distribution, with each category having an expected frequency of 1 / observed.size.
chiSqTest(Matrix) - Static method in class org.apache.spark.mllib.stat.Statistics
Conduct Pearson's independence test on the input contingency matrix, which cannot contain negative entries or columns or rows that sum up to 0.
chiSqTest(RDD<LabeledPoint>) - Static method in class org.apache.spark.mllib.stat.Statistics
Conduct Pearson's independence test for every feature against the label across the input RDD.
chiSqTest(JavaRDD<LabeledPoint>) - Static method in class org.apache.spark.mllib.stat.Statistics
Java-friendly version of chiSqTest()
ChiSqTest - Class in org.apache.spark.mllib.stat.test
Conduct the chi-squared test for the input RDDs using the specified method.
ChiSqTest() - Constructor for class org.apache.spark.mllib.stat.test.ChiSqTest
 
ChiSqTest.Method - Class in org.apache.spark.mllib.stat.test
param: name String name for the method.
ChiSqTest.Method$ - Class in org.apache.spark.mllib.stat.test
 
ChiSqTest.NullHypothesis$ - Class in org.apache.spark.mllib.stat.test
 
ChiSqTestResult - Class in org.apache.spark.mllib.stat.test
Object containing the test results for the chi-squared hypothesis test.
chiSquared(Vector, Vector, String) - Static method in class org.apache.spark.mllib.stat.test.ChiSqTest
 
chiSquaredFeatures(RDD<LabeledPoint>, String) - Static method in class org.apache.spark.mllib.stat.test.ChiSqTest
Conduct Pearson's independence test for each feature against the label across the input RDD.
chiSquaredMatrix(Matrix, String) - Static method in class org.apache.spark.mllib.stat.test.ChiSqTest
 
ChiSquareTest - Class in org.apache.spark.ml.stat
:: Experimental ::
ChiSquareTest() - Constructor for class org.apache.spark.ml.stat.ChiSquareTest
 
chmod700(File) - Static method in class org.apache.spark.util.Utils
JDK equivalent of chmod 700 file.
CholeskyDecomposition - Class in org.apache.spark.mllib.linalg
Compute Cholesky decomposition.
CholeskyDecomposition() - Constructor for class org.apache.spark.mllib.linalg.CholeskyDecomposition
 
cipherStream() - Method in interface org.apache.spark.security.CryptoStreamUtils.BaseErrorHandler
The encrypted stream that may get into an unhealthy state.
classForName(String) - Static method in class org.apache.spark.util.Utils
Preferred alternative to Class.forName(className)
Classification() - Static method in class org.apache.spark.mllib.tree.configuration.Algo
 
ClassificationLoss - Interface in org.apache.spark.mllib.tree.loss
 
ClassificationModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>> - Class in org.apache.spark.ml.classification
:: DeveloperApi ::
ClassificationModel() - Constructor for class org.apache.spark.ml.classification.ClassificationModel
 
ClassificationModel - Interface in org.apache.spark.mllib.classification
Represents a classification model that predicts to which of a set of categories an example belongs.
Classifier<FeaturesType,E extends Classifier<FeaturesType,E,M>,M extends ClassificationModel<FeaturesType,M>> - Class in org.apache.spark.ml.classification
:: DeveloperApi ::
Classifier() - Constructor for class org.apache.spark.ml.classification.Classifier
 
classifier() - Method in interface org.apache.spark.ml.classification.OneVsRestParams
param for the base binary classifier that we reduce multiclass classification into.
ClassifierParams - Interface in org.apache.spark.ml.classification
(private[spark]) Params for classification.
ClassifierTypeTrait - Interface in org.apache.spark.ml.classification
 
classIsLoadable(String) - Static method in class org.apache.spark.util.Utils
Determines whether the provided class is loadable in the current thread.
className() - Method in class org.apache.spark.ExceptionFailure
 
className() - Static method in class org.apache.spark.ml.linalg.JsonMatrixConverter
Unique class name for identifying JSON object encoded by this class.
className() - Method in class org.apache.spark.sql.catalog.Function
 
classpathEntries() - Method in class org.apache.spark.status.api.v1.ApplicationEnvironmentInfo
 
classTag() - Method in class org.apache.spark.api.java.JavaDoubleRDD
 
classTag() - Method in class org.apache.spark.api.java.JavaPairRDD
 
classTag() - Method in class org.apache.spark.api.java.JavaRDD
 
classTag() - Method in interface org.apache.spark.api.java.JavaRDDLike
 
classTag() - Method in class org.apache.spark.sql.Dataset
 
classTag() - Method in class org.apache.spark.storage.memory.DeserializedMemoryEntry
 
classTag() - Method in interface org.apache.spark.storage.memory.MemoryEntry
 
classTag() - Method in class org.apache.spark.storage.memory.SerializedMemoryEntry
 
classTag() - Method in class org.apache.spark.streaming.api.java.JavaDStream
 
classTag() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
 
classTag() - Method in class org.apache.spark.streaming.api.java.JavaInputDStream
 
classTag() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
 
classTag() - Method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
 
clean(long, boolean) - Method in class org.apache.spark.streaming.util.WriteAheadLog
Clean all the records that are older than the threshold time.
clean(Object, boolean, boolean) - Static method in class org.apache.spark.util.ClosureCleaner
Clean the given closure in place.
CleanAccum - Class in org.apache.spark
 
CleanAccum(long) - Constructor for class org.apache.spark.CleanAccum
 
CleanBroadcast - Class in org.apache.spark
 
CleanBroadcast(long) - Constructor for class org.apache.spark.CleanBroadcast
 
CleanCheckpoint - Class in org.apache.spark
 
CleanCheckpoint(int) - Constructor for class org.apache.spark.CleanCheckpoint
 
CleanerListener - Interface in org.apache.spark
Listener class used for testing when any item has been cleaned by the Cleaner class.
cleaning() - Method in class org.apache.spark.status.LiveStage
 
CleanRDD - Class in org.apache.spark
 
CleanRDD(int) - Constructor for class org.apache.spark.CleanRDD
 
CleanShuffle - Class in org.apache.spark
 
CleanShuffle(int) - Constructor for class org.apache.spark.CleanShuffle
 
cleanupOldBlocks(long) - Method in interface org.apache.spark.streaming.receiver.ReceivedBlockHandler
Cleanup old blocks older than the given threshold time
CleanupTask - Interface in org.apache.spark
Classes that represent cleaning tasks.
CleanupTaskWeakReference - Class in org.apache.spark
A WeakReference associated with a CleanupTask.
CleanupTaskWeakReference(CleanupTask, Object, ReferenceQueue<Object>) - Constructor for class org.apache.spark.CleanupTaskWeakReference
 
clear(Param<?>) - Method in interface org.apache.spark.ml.param.Params
Clears the user-supplied value for the input param.
clear() - Method in class org.apache.spark.sql.util.ExecutionListenerManager
Removes all the registered QueryExecutionListener.
clear() - Static method in class org.apache.spark.util.AccumulatorContext
Clears all registered AccumulatorV2s.
clearActive() - Static method in class org.apache.spark.sql.SQLContext
Deprecated.
Use SparkSession.clearActiveSession instead. Since 2.0.0.
clearActiveSession() - Static method in class org.apache.spark.sql.SparkSession
Clears the active SparkSession for current thread.
clearCache() - Method in class org.apache.spark.sql.catalog.Catalog
Removes all cached tables from the in-memory cache.
clearCache() - Method in class org.apache.spark.sql.SQLContext
Removes all cached tables from the in-memory cache.
clearCallSite() - Method in class org.apache.spark.api.java.JavaSparkContext
Pass-through to SparkContext.setCallSite.
clearCallSite() - Method in class org.apache.spark.SparkContext
Clear the thread-local property for overriding the call sites of actions and RDDs.
clearDefaultSession() - Static method in class org.apache.spark.sql.SparkSession
Clears the default SparkSession that is returned by the builder.
clearDependencies() - Method in class org.apache.spark.rdd.CoGroupedRDD
 
clearDependencies() - Method in class org.apache.spark.rdd.ShuffledRDD
 
clearDependencies() - Method in class org.apache.spark.rdd.UnionRDD
 
clearJobGroup() - Method in class org.apache.spark.api.java.JavaSparkContext
Clear the current thread's job group ID and its description.
clearJobGroup() - Method in class org.apache.spark.SparkContext
Clear the current thread's job group ID and its description.
clearThreshold() - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
Clears the threshold so that predict will output raw prediction scores.
clearThreshold() - Method in class org.apache.spark.mllib.classification.SVMModel
Clears the threshold so that predict will output raw prediction scores.
Clock - Interface in org.apache.spark.util
An interface to represent clocks, so that they can be mocked out in unit tests.
CLogLog$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.CLogLog$
 
clone() - Method in class org.apache.spark.SparkConf
Copy this object
clone() - Method in class org.apache.spark.sql.ExperimentalMethods
 
clone() - Method in class org.apache.spark.sql.types.Decimal
 
clone() - Method in class org.apache.spark.sql.util.ExecutionListenerManager
Get an identical copy of this listener manager.
clone() - Method in class org.apache.spark.storage.StorageLevel
 
clone() - Method in class org.apache.spark.util.random.BernoulliCellSampler
 
clone() - Method in class org.apache.spark.util.random.BernoulliSampler
 
clone() - Method in class org.apache.spark.util.random.PoissonSampler
 
clone() - Method in interface org.apache.spark.util.random.RandomSampler
return a copy of the RandomSampler object
clone(T, SerializerInstance, ClassTag<T>) - Static method in class org.apache.spark.util.Utils
Clone an object using a Spark serializer.
cloneComplement() - Method in class org.apache.spark.util.random.BernoulliCellSampler
Return a sampler that is the complement of the range specified of the current sampler.
cloneProperties(Properties) - Static method in class org.apache.spark.util.Utils
Create a new properties object with the same values as `props`
close() - Method in class org.apache.spark.api.java.JavaSparkContext
 
close() - Method in class org.apache.spark.io.NioBufferedFileInputStream
 
close() - Method in class org.apache.spark.io.ReadAheadInputStream
 
close() - Method in class org.apache.spark.io.SnappyOutputStreamWrapper
 
close() - Method in interface org.apache.spark.security.CryptoStreamUtils.BaseErrorHandler
 
close() - Method in class org.apache.spark.serializer.DeserializationStream
 
close() - Method in class org.apache.spark.serializer.SerializationStream
 
close(Throwable) - Method in class org.apache.spark.sql.ForeachWriter
Called when stopping to process one partition of new data in the executor side.
close() - Method in class org.apache.spark.sql.hive.execution.HiveOutputWriter
 
close() - Method in class org.apache.spark.sql.SparkSession
Synonym for stop().
close() - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
close() - Method in class org.apache.spark.sql.vectorized.ColumnarBatch
Called to close all the columns in this batch.
close() - Method in class org.apache.spark.sql.vectorized.ColumnVector
Cleans up memory for this column vector.
close() - Method in class org.apache.spark.storage.BufferReleasingInputStream
 
close() - Method in class org.apache.spark.storage.CountingWritableChannel
 
close() - Method in class org.apache.spark.storage.TimeTrackingOutputStream
 
close() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
 
close() - Method in class org.apache.spark.streaming.util.WriteAheadLog
Close this log and release any resources.
closed() - Method in interface org.apache.spark.security.CryptoStreamUtils.BaseErrorHandler
 
closeWriter(TaskAttemptContext) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
 
ClosureCleaner - Class in org.apache.spark.util
A cleaner that renders closures serializable if they can be done so safely.
ClosureCleaner() - Constructor for class org.apache.spark.util.ClosureCleaner
 
closureSerializer() - Method in class org.apache.spark.SparkEnv
 
cls() - Method in class org.apache.spark.sql.types.ObjectType
 
cls() - Method in class org.apache.spark.util.MethodIdentifier
 
clsTag() - Method in interface org.apache.spark.sql.Encoder
A ClassTag that can be used to construct an Array to contain a collection of T.
cluster() - Method in class org.apache.spark.ml.clustering.ClusteringSummary
Cluster centers of the transformed data.
cluster() - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering.Assignment
 
clusterCenter() - Method in class org.apache.spark.ml.clustering.ClusterData
 
clusterCenters() - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
 
clusterCenters() - Method in class org.apache.spark.ml.clustering.KMeansModel
 
clusterCenters() - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
Leaf cluster centers.
clusterCenters() - Method in class org.apache.spark.mllib.clustering.KMeansModel
 
clusterCenters() - Method in class org.apache.spark.mllib.clustering.StreamingKMeansModel
 
ClusterData - Class in org.apache.spark.ml.clustering
Helper class for storing model data
ClusterData(int, Vector) - Constructor for class org.apache.spark.ml.clustering.ClusterData
 
clusteredColumns - Variable in class org.apache.spark.sql.sources.v2.reader.partitioning.ClusteredDistribution
The names of the clustered columns.
ClusteredDistribution - Class in org.apache.spark.sql.sources.v2.reader.partitioning
A concrete implementation of Distribution.
ClusteredDistribution(String[]) - Constructor for class org.apache.spark.sql.sources.v2.reader.partitioning.ClusteredDistribution
 
clusterIdx() - Method in class org.apache.spark.ml.clustering.ClusterData
 
ClusteringEvaluator - Class in org.apache.spark.ml.evaluation
:: Experimental ::
ClusteringEvaluator(String) - Constructor for class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
ClusteringEvaluator() - Constructor for class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
ClusteringSummary - Class in org.apache.spark.ml.clustering
:: Experimental :: Summary of clustering algorithms.
clusterSizes() - Method in class org.apache.spark.ml.clustering.ClusteringSummary
Size of (number of data points in) each cluster.
ClusterStats(Vector, double, long) - Constructor for class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette.ClusterStats
 
ClusterStats$() - Constructor for class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette.ClusterStats$
 
clusterWeights() - Method in class org.apache.spark.mllib.clustering.StreamingKMeansModel
 
cn() - Method in class org.apache.spark.mllib.feature.VocabWord
 
coalesce(int) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return a new RDD that is reduced into numPartitions partitions.
coalesce(int, boolean) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return a new RDD that is reduced into numPartitions partitions.
coalesce(int) - Method in class org.apache.spark.api.java.JavaPairRDD
Return a new RDD that is reduced into numPartitions partitions.
coalesce(int, boolean) - Method in class org.apache.spark.api.java.JavaPairRDD
Return a new RDD that is reduced into numPartitions partitions.
coalesce(int) - Method in class org.apache.spark.api.java.JavaRDD
Return a new RDD that is reduced into numPartitions partitions.
coalesce(int, boolean) - Method in class org.apache.spark.api.java.JavaRDD
Return a new RDD that is reduced into numPartitions partitions.
coalesce(int, RDD<?>) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
Runs the packing algorithm and returns an array of PartitionGroups that if possible are load balanced and grouped by locality
coalesce(int, RDD<?>) - Method in interface org.apache.spark.rdd.PartitionCoalescer
Coalesce the partitions of the given RDD.
coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
Return a new RDD that is reduced into numPartitions partitions.
coalesce(int) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset that has exactly numPartitions partitions, when the fewer partitions are requested.
coalesce(Column...) - Static method in class org.apache.spark.sql.functions
Returns the first column that is not null, or null if all inputs are null.
coalesce(Seq<Column>) - Static method in class org.apache.spark.sql.functions
Returns the first column that is not null, or null if all inputs are null.
CoarseGrainedClusterMessage - Interface in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages
 
CoarseGrainedClusterMessages.AddWebUIFilter - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.AddWebUIFilter$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.GetExecutorLossReason - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.GetExecutorLossReason$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.KillExecutors - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.KillExecutors$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.KillExecutorsOnHost - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.KillExecutorsOnHost$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.KillTask - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.KillTask$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.LaunchTask - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.LaunchTask$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RegisterClusterManager - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RegisterClusterManager$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RegisteredExecutor$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RegisterExecutor - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RegisterExecutor$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RegisterExecutorFailed - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RegisterExecutorFailed$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RegisterExecutorResponse - Interface in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RemoveExecutor - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RemoveExecutor$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RemoveWorker - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RemoveWorker$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RequestExecutors - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RequestExecutors$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RetrieveLastAllocatedExecutorId$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.RetrieveSparkAppConfig$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.ReviveOffers$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.SetupDriver - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.SetupDriver$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.Shutdown$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.SparkAppConfig - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.SparkAppConfig$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.StatusUpdate - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.StatusUpdate$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.StopDriver$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.StopExecutor$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.StopExecutors$ - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.UpdateDelegationTokens - Class in org.apache.spark.scheduler.cluster
 
CoarseGrainedClusterMessages.UpdateDelegationTokens$ - Class in org.apache.spark.scheduler.cluster
 
code() - Method in class org.apache.spark.mllib.feature.VocabWord
 
CodegenMetrics - Class in org.apache.spark.metrics.source
:: Experimental :: Metrics for code generation.
CodegenMetrics() - Constructor for class org.apache.spark.metrics.source.CodegenMetrics
 
codeLen() - Method in class org.apache.spark.mllib.feature.VocabWord
 
coefficientMatrix() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
 
coefficients() - Method in class org.apache.spark.ml.classification.LinearSVCModel
 
coefficients() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
A vector of model coefficients for "binomial" logistic regression.
coefficients() - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
coefficients() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
 
coefficients() - Method in class org.apache.spark.ml.regression.LinearRegressionModel
 
coefficientStandardErrors() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionTrainingSummary
Standard error of estimated coefficients and intercept.
coefficientStandardErrors() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
Standard error of estimated coefficients and intercept.
cogroup(JavaPairRDD<K, W>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
For each key k in this or other, return a resulting RDD that contains a tuple with the list of values for that key in this as well as other.
cogroup(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
For each key k in this or other1 or other2, return a resulting RDD that contains a tuple with the list of values for that key in this, other1 and other2.
cogroup(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>, JavaPairRDD<K, W3>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
For each key k in this or other1 or other2 or other3, return a resulting RDD that contains a tuple with the list of values for that key in this, other1, other2 and other3.
cogroup(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
For each key k in this or other, return a resulting RDD that contains a tuple with the list of values for that key in this as well as other.
cogroup(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>) - Method in class org.apache.spark.api.java.JavaPairRDD
For each key k in this or other1 or other2, return a resulting RDD that contains a tuple with the list of values for that key in this, other1 and other2.
cogroup(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>, JavaPairRDD<K, W3>) - Method in class org.apache.spark.api.java.JavaPairRDD
For each key k in this or other1 or other2 or other3, return a resulting RDD that contains a tuple with the list of values for that key in this, other1, other2 and other3.
cogroup(JavaPairRDD<K, W>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
For each key k in this or other, return a resulting RDD that contains a tuple with the list of values for that key in this as well as other.
cogroup(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
For each key k in this or other1 or other2, return a resulting RDD that contains a tuple with the list of values for that key in this, other1 and other2.
cogroup(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>, JavaPairRDD<K, W3>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
For each key k in this or other1 or other2 or other3, return a resulting RDD that contains a tuple with the list of values for that key in this, other1, other2 and other3.
cogroup(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>, RDD<Tuple2<K, W3>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
For each key k in this or other1 or other2 or other3, return a resulting RDD that contains a tuple with the list of values for that key in this, other1, other2 and other3.
cogroup(RDD<Tuple2<K, W>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
For each key k in this or other, return a resulting RDD that contains a tuple with the list of values for that key in this as well as other.
cogroup(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
For each key k in this or other1 or other2, return a resulting RDD that contains a tuple with the list of values for that key in this, other1 and other2.
cogroup(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>, RDD<Tuple2<K, W3>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
For each key k in this or other1 or other2 or other3, return a resulting RDD that contains a tuple with the list of values for that key in this, other1, other2 and other3.
cogroup(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
For each key k in this or other, return a resulting RDD that contains a tuple with the list of values for that key in this as well as other.
cogroup(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
For each key k in this or other1 or other2, return a resulting RDD that contains a tuple with the list of values for that key in this, other1 and other2.
cogroup(RDD<Tuple2<K, W>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
For each key k in this or other, return a resulting RDD that contains a tuple with the list of values for that key in this as well as other.
cogroup(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
For each key k in this or other1 or other2, return a resulting RDD that contains a tuple with the list of values for that key in this, other1 and other2.
cogroup(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>, RDD<Tuple2<K, W3>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
For each key k in this or other1 or other2 or other3, return a resulting RDD that contains a tuple with the list of values for that key in this, other1, other2 and other3.
cogroup(KeyValueGroupedDataset<K, U>, Function3<K, Iterator<V>, Iterator<U>, TraversableOnce<R>>, Encoder<R>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
(Scala-specific) Applies the given function to each cogrouped data.
cogroup(KeyValueGroupedDataset<K, U>, CoGroupFunction<K, V, U, R>, Encoder<R>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
(Java-specific) Applies the given function to each cogrouped data.
cogroup(JavaPairDStream<K, W>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'cogroup' between RDDs of this DStream and other DStream.
cogroup(JavaPairDStream<K, W>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'cogroup' between RDDs of this DStream and other DStream.
cogroup(JavaPairDStream<K, W>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'cogroup' between RDDs of this DStream and other DStream.
cogroup(DStream<Tuple2<K, W>>, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'cogroup' between RDDs of this DStream and other DStream.
cogroup(DStream<Tuple2<K, W>>, int, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'cogroup' between RDDs of this DStream and other DStream.
cogroup(DStream<Tuple2<K, W>>, Partitioner, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'cogroup' between RDDs of this DStream and other DStream.
CoGroupedRDD<K> - Class in org.apache.spark.rdd
:: DeveloperApi :: An RDD that cogroups its parents.
CoGroupedRDD(Seq<RDD<? extends Product2<K, ?>>>, Partitioner, ClassTag<K>) - Constructor for class org.apache.spark.rdd.CoGroupedRDD
 
CoGroupFunction<K,V1,V2,R> - Interface in org.apache.spark.api.java.function
A function that returns zero or more output records from each grouping key and its values from 2 Datasets.
col(String) - Method in class org.apache.spark.sql.Dataset
Selects column based on the column name and returns it as a Column.
col(String) - Static method in class org.apache.spark.sql.functions
Returns a Column based on the given column name.
coldStartStrategy() - Method in interface org.apache.spark.ml.recommendation.ALSModelParams
Param for strategy for dealing with unknown or new users/items at prediction time.
colIter() - Method in class org.apache.spark.ml.linalg.DenseMatrix
 
colIter() - Method in interface org.apache.spark.ml.linalg.Matrix
Returns an iterator of column vectors.
colIter() - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
colIter() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
 
colIter() - Method in interface org.apache.spark.mllib.linalg.Matrix
Returns an iterator of column vectors.
colIter() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
collect() - Method in interface org.apache.spark.api.java.JavaRDDLike
Return an array that contains all of the elements in this RDD.
collect() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
collect() - Method in class org.apache.spark.rdd.RDD
Return an array that contains all of the elements in this RDD.
collect(PartialFunction<T, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
Return an RDD that contains all matching values by applying f.
collect() - Method in class org.apache.spark.sql.Dataset
Returns an array that contains all rows in this Dataset.
collect_list(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns a list of objects with duplicates.
collect_list(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns a list of objects with duplicates.
collect_set(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns a set of objects with duplicate elements eliminated.
collect_set(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns a set of objects with duplicate elements eliminated.
collectAsList() - Method in class org.apache.spark.sql.Dataset
Returns a Java list that contains all rows in this Dataset.
collectAsMap() - Method in class org.apache.spark.api.java.JavaPairRDD
Return the key-value pairs in this RDD to the master as a Map.
collectAsMap() - Method in class org.apache.spark.rdd.PairRDDFunctions
Return the key-value pairs in this RDD to the master as a Map.
collectAsync() - Method in interface org.apache.spark.api.java.JavaRDDLike
The asynchronous version of collect, which returns a future for retrieving an array containing all of the elements in this RDD.
collectAsync() - Method in class org.apache.spark.rdd.AsyncRDDActions
Returns a future for retrieving all elements of this RDD.
collectEdges(EdgeDirection) - Method in class org.apache.spark.graphx.GraphOps
Returns an RDD that contains for each vertex v its local edges, i.e., the edges that are incident on v, in the user-specified direction.
collectionAccumulator() - Method in class org.apache.spark.SparkContext
Create and register a CollectionAccumulator, which starts with empty list and accumulates inputs by adding them into the list.
collectionAccumulator(String) - Method in class org.apache.spark.SparkContext
Create and register a CollectionAccumulator, which starts with empty list and accumulates inputs by adding them into the list.
CollectionAccumulator<T> - Class in org.apache.spark.util
An accumulator for collecting a list of elements.
CollectionAccumulator() - Constructor for class org.apache.spark.util.CollectionAccumulator
 
CollectionsUtils - Class in org.apache.spark.util
 
CollectionsUtils() - Constructor for class org.apache.spark.util.CollectionsUtils
 
collectNeighborIds(EdgeDirection) - Method in class org.apache.spark.graphx.GraphOps
Collect the neighbor vertex ids for each vertex.
collectNeighbors(EdgeDirection) - Method in class org.apache.spark.graphx.GraphOps
Collect the neighbor vertex attributes for each vertex.
collectPartitions(int[]) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return an array that contains all of the elements in a specific partition of this RDD.
collectSubModels() - Method in interface org.apache.spark.ml.param.shared.HasCollectSubModels
Param for whether to collect a list of sub-models trained during tuning.
colPtrs() - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
colPtrs() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
colRegex(String) - Method in class org.apache.spark.sql.Dataset
Selects column based on the column name specified as a regex and returns it as Column.
colsPerBlock() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
 
colStats(RDD<Vector>) - Static method in class org.apache.spark.mllib.stat.Statistics
Computes column-wise summary statistics for the input RDD[Vector].
Column - Class in org.apache.spark.sql.catalog
A column in Spark, as returned by listColumns method in Catalog.
Column(String, String, String, boolean, boolean, boolean) - Constructor for class org.apache.spark.sql.catalog.Column
 
Column - Class in org.apache.spark.sql
A column that will be computed based on the data in a DataFrame.
Column(Expression) - Constructor for class org.apache.spark.sql.Column
 
Column(String) - Constructor for class org.apache.spark.sql.Column
 
column(String) - Static method in class org.apache.spark.sql.functions
Returns a Column based on the given column name.
column(int) - Method in class org.apache.spark.sql.vectorized.ColumnarBatch
Returns the column at `ordinal`.
ColumnarArray - Class in org.apache.spark.sql.vectorized
Array abstraction in ColumnVector.
ColumnarArray(ColumnVector, int, int) - Constructor for class org.apache.spark.sql.vectorized.ColumnarArray
 
ColumnarBatch - Class in org.apache.spark.sql.vectorized
This class wraps multiple ColumnVectors as a row-wise table.
ColumnarBatch(ColumnVector[]) - Constructor for class org.apache.spark.sql.vectorized.ColumnarBatch
 
ColumnarMap - Class in org.apache.spark.sql.vectorized
Map abstraction in ColumnVector.
ColumnarMap(ColumnVector, ColumnVector, int, int) - Constructor for class org.apache.spark.sql.vectorized.ColumnarMap
 
ColumnarRow - Class in org.apache.spark.sql.vectorized
Row abstraction in ColumnVector.
ColumnarRow(ColumnVector, int) - Constructor for class org.apache.spark.sql.vectorized.ColumnarRow
 
ColumnName - Class in org.apache.spark.sql
A convenient class used for constructing schema.
ColumnName(String) - Constructor for class org.apache.spark.sql.ColumnName
 
ColumnPruner - Class in org.apache.spark.ml.feature
Utility transformer for removing temporary columns from a DataFrame.
ColumnPruner(String, Set<String>) - Constructor for class org.apache.spark.ml.feature.ColumnPruner
 
ColumnPruner(Set<String>) - Constructor for class org.apache.spark.ml.feature.ColumnPruner
 
columns() - Method in class org.apache.spark.sql.Dataset
Returns all column names as an array.
columnSchema() - Static method in class org.apache.spark.ml.image.ImageSchema
Schema for the image column: Row(String, Int, Int, Int, Int, Array[Byte])
columnSimilarities() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
Compute all cosine similarities between columns of this matrix using the brute-force approach of computing normalized dot products.
columnSimilarities() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
Compute all cosine similarities between columns of this matrix using the brute-force approach of computing normalized dot products.
columnSimilarities(double) - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
Compute similarities between columns of this matrix using a sampling approach.
columnsToPrune() - Method in class org.apache.spark.ml.feature.ColumnPruner
 
columnToOldVector(Dataset<?>, String) - Static method in class org.apache.spark.ml.util.DatasetUtils
 
columnToVector(Dataset<?>, String) - Static method in class org.apache.spark.ml.util.DatasetUtils
Cast a column in a Dataset to Vector type.
ColumnVector - Class in org.apache.spark.sql.vectorized
An interface representing in-memory columnar data in Spark.
combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean, Serializer) - Method in class org.apache.spark.api.java.JavaPairRDD
Generic function to combine the elements for each key using a custom set of aggregation functions.
combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
Generic function to combine the elements for each key using a custom set of aggregation functions.
combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
Simplified version of combineByKey that hash-partitions the output RDD and uses map-side aggregation.
combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>) - Method in class org.apache.spark.api.java.JavaPairRDD
Simplified version of combineByKey that hash-partitions the resulting RDD using the existing partitioner/parallelism level and using map-side aggregation.
combineByKey(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean, Serializer) - Method in class org.apache.spark.rdd.PairRDDFunctions
Generic function to combine the elements for each key using a custom set of aggregation functions.
combineByKey(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
Simplified version of combineByKeyWithClassTag that hash-partitions the output RDD.
combineByKey(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Simplified version of combineByKeyWithClassTag that hash-partitions the resulting RDD using the existing partitioner/parallelism level.
combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Combine elements of each key in DStream's RDDs using custom function.
combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Combine elements of each key in DStream's RDDs using custom function.
combineByKey(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean, ClassTag<C>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Combine elements of each key in DStream's RDDs using custom functions.
combineByKeyWithClassTag(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean, Serializer, ClassTag<C>) - Method in class org.apache.spark.rdd.PairRDDFunctions
:: Experimental :: Generic function to combine the elements for each key using a custom set of aggregation functions.
combineByKeyWithClassTag(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>, int, ClassTag<C>) - Method in class org.apache.spark.rdd.PairRDDFunctions
:: Experimental :: Simplified version of combineByKeyWithClassTag that hash-partitions the output RDD.
combineByKeyWithClassTag(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>, ClassTag<C>) - Method in class org.apache.spark.rdd.PairRDDFunctions
:: Experimental :: Simplified version of combineByKeyWithClassTag that hash-partitions the resulting RDD using the existing partitioner/parallelism level.
combineCombinersByKey(Iterator<? extends Product2<K, C>>, TaskContext) - Method in class org.apache.spark.Aggregator
 
combineValuesByKey(Iterator<? extends Product2<K, V>>, TaskContext) - Method in class org.apache.spark.Aggregator
 
CommandLineUtils - Interface in org.apache.spark.util
Contains basic command line parsing functionality and methods to parse some common Spark CLI options.
commit(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
commit(Offset) - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.ContinuousReader
Informs the source that Spark has completed processing all data for offsets less than or equal to `end` and will only request offsets greater than `end` in the future.
commit(Offset) - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.MicroBatchReader
Informs the source that Spark has completed processing all data for offsets less than or equal to `end` and will only request offsets greater than `end` in the future.
commit(WriterCommitMessage[]) - Method in interface org.apache.spark.sql.sources.v2.writer.DataSourceWriter
Commits this writing job with a list of commit messages.
commit() - Method in interface org.apache.spark.sql.sources.v2.writer.DataWriter
Commits this writer after all records are written successfully, returns a commit message which will be sent back to driver side and passed to DataSourceWriter.commit(WriterCommitMessage[]).
commit(long, WriterCommitMessage[]) - Method in interface org.apache.spark.sql.sources.v2.writer.streaming.StreamWriter
Commits this writing job for the specified epoch with a list of commit messages.
commit(WriterCommitMessage[]) - Method in interface org.apache.spark.sql.sources.v2.writer.streaming.StreamWriter
 
commitJob(JobContext, Seq<FileCommitProtocol.TaskCommitMessage>) - Method in class org.apache.spark.internal.io.FileCommitProtocol
Commits a job after the writes succeed.
commitJob(JobContext, Seq<FileCommitProtocol.TaskCommitMessage>) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
 
commitTask(TaskAttemptContext) - Method in class org.apache.spark.internal.io.FileCommitProtocol
Commits a task after the writes succeed.
commitTask(TaskAttemptContext) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
 
commitTask(OutputCommitter, TaskAttemptContext, int, int) - Static method in class org.apache.spark.mapred.SparkHadoopMapRedUtil
Commits a task output.
commonHeaderNodes(HttpServletRequest) - Static method in class org.apache.spark.ui.UIUtils
 
comparator(Schedulable, Schedulable) - Method in interface org.apache.spark.scheduler.SchedulingAlgorithm
 
compare(PartitionGroup, PartitionGroup) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
 
compare(Option<PartitionGroup>, Option<PartitionGroup>) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
 
compare(Decimal) - Method in class org.apache.spark.sql.types.Decimal
 
compare(Decimal, Decimal) - Method in interface org.apache.spark.sql.types.Decimal.DecimalIsConflicted
 
compare(RDDInfo) - Method in class org.apache.spark.storage.RDDInfo
 
compareTo(SparkShutdownHook) - Method in class org.apache.spark.util.SparkShutdownHook
 
compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
 
compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
 
compileValue(Object) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
Converts value to SQL expression.
compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
 
compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
 
compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
 
compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
Complete() - Static method in class org.apache.spark.sql.streaming.OutputMode
OutputMode in which all the rows in the streaming DataFrame/Dataset will be written to the sink every time there are some updates.
completed() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
 
completedIndices() - Method in class org.apache.spark.status.LiveJob
 
completedIndices() - Method in class org.apache.spark.status.LiveStage
 
completedStages() - Method in class org.apache.spark.status.LiveJob
 
completedTasks() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
completedTasks() - Method in class org.apache.spark.status.LiveExecutor
 
completedTasks() - Method in class org.apache.spark.status.LiveJob
 
completedTasks() - Method in class org.apache.spark.status.LiveStage
 
COMPLETION_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
 
completionTime() - Method in class org.apache.spark.scheduler.StageInfo
Time when all tasks in the stage completed or when the stage was cancelled.
completionTime() - Method in class org.apache.spark.status.api.v1.JobData
 
completionTime() - Method in class org.apache.spark.status.api.v1.StageData
 
completionTime() - Method in class org.apache.spark.status.LiveJob
 
ComplexFutureAction<T> - Class in org.apache.spark
A FutureAction for actions that could trigger multiple Spark jobs.
ComplexFutureAction(Function1<JobSubmitter, Future<T>>) - Constructor for class org.apache.spark.ComplexFutureAction
 
compressed() - Method in interface org.apache.spark.ml.linalg.Matrix
Returns a matrix in dense column major, dense row major, sparse row major, or sparse column major format, whichever uses less storage.
compressed() - Method in interface org.apache.spark.ml.linalg.Vector
Returns a vector in either dense or sparse format, whichever uses less storage.
compressed() - Method in interface org.apache.spark.mllib.linalg.Vector
Returns a vector in either dense or sparse format, whichever uses less storage.
compressedColMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
Returns a matrix in dense or sparse column major format, whichever uses less storage.
compressedInputStream(InputStream) - Method in interface org.apache.spark.io.CompressionCodec
 
compressedInputStream(InputStream) - Method in class org.apache.spark.io.LZ4CompressionCodec
 
compressedInputStream(InputStream) - Method in class org.apache.spark.io.LZFCompressionCodec
 
compressedInputStream(InputStream) - Method in class org.apache.spark.io.SnappyCompressionCodec
 
compressedInputStream(InputStream) - Method in class org.apache.spark.io.ZStdCompressionCodec
 
compressedOutputStream(OutputStream) - Method in interface org.apache.spark.io.CompressionCodec
 
compressedOutputStream(OutputStream) - Method in class org.apache.spark.io.LZ4CompressionCodec
 
compressedOutputStream(OutputStream) - Method in class org.apache.spark.io.LZFCompressionCodec
 
compressedOutputStream(OutputStream) - Method in class org.apache.spark.io.SnappyCompressionCodec
 
compressedOutputStream(OutputStream) - Method in class org.apache.spark.io.ZStdCompressionCodec
 
compressedRowMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
Returns a matrix in dense or sparse row major format, whichever uses less storage.
CompressionCodec - Interface in org.apache.spark.io
:: DeveloperApi :: CompressionCodec allows the customization of choosing different compression implementations to be used in block storage.
compute(Partition, TaskContext) - Method in class org.apache.spark.api.r.BaseRRDD
 
compute(Partition, TaskContext) - Method in class org.apache.spark.graphx.EdgeRDD
 
compute(Partition, TaskContext) - Method in class org.apache.spark.graphx.VertexRDD
Provides the RDD[(VertexId, VD)] equivalent output.
compute(Vector, double, Vector) - Method in class org.apache.spark.mllib.optimization.Gradient
Compute the gradient and loss given the features of a single data point.
compute(Vector, double, Vector, Vector) - Method in class org.apache.spark.mllib.optimization.Gradient
Compute the gradient and loss given the features of a single data point, add the gradient to a provided vector to avoid creating new objects, and return loss.
compute(Vector, double, Vector) - Method in class org.apache.spark.mllib.optimization.HingeGradient
 
compute(Vector, double, Vector, Vector) - Method in class org.apache.spark.mllib.optimization.HingeGradient
 
compute(Vector, Vector, double, int, double) - Method in class org.apache.spark.mllib.optimization.L1Updater
 
compute(Vector, double, Vector) - Method in class org.apache.spark.mllib.optimization.LeastSquaresGradient
 
compute(Vector, double, Vector, Vector) - Method in class org.apache.spark.mllib.optimization.LeastSquaresGradient
 
compute(Vector, double, Vector, Vector) - Method in class org.apache.spark.mllib.optimization.LogisticGradient
 
compute(Vector, Vector, double, int, double) - Method in class org.apache.spark.mllib.optimization.SimpleUpdater
 
compute(Vector, Vector, double, int, double) - Method in class org.apache.spark.mllib.optimization.SquaredL2Updater
 
compute(Vector, Vector, double, int, double) - Method in class org.apache.spark.mllib.optimization.Updater
Compute an updated value for weights given the gradient, stepSize, iteration number and regularization parameter.
compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.CoGroupedRDD
 
compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.HadoopRDD
 
compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.JdbcRDD
 
compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.NewHadoopRDD
 
compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.PartitionPruningRDD
 
compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.RDD
:: DeveloperApi :: Implemented by subclasses to compute a given partition.
compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.ShuffledRDD
 
compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.UnionRDD
 
compute(Time) - Method in class org.apache.spark.streaming.api.java.JavaDStream
Generate an RDD for the given duration
compute(Time) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Method that generates an RDD for the given Duration
compute(Time) - Method in class org.apache.spark.streaming.dstream.ConstantInputDStream
 
compute(Time) - Method in class org.apache.spark.streaming.dstream.DStream
Method that generates an RDD for the given time
compute(Time) - Method in class org.apache.spark.streaming.dstream.ReceiverInputDStream
 
compute(long, long, long, long) - Method in interface org.apache.spark.streaming.scheduler.rate.RateEstimator
Computes the number of records the stream attached to this RateEstimator should ingest per second, given an update on the size and completion times of the latest batch.
computeClusterStats(Dataset<Row>, String, String) - Static method in class org.apache.spark.ml.evaluation.CosineSilhouette
The method takes the input dataset and computes the aggregated values about a cluster which are needed by the algorithm.
computeClusterStats(Dataset<Row>, String, String) - Static method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette
The method takes the input dataset and computes the aggregated values about a cluster which are needed by the algorithm.
computeColumnSummaryStatistics() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
Computes column-wise summary statistics.
computeCorrelation(RDD<Object>, RDD<Object>) - Method in interface org.apache.spark.mllib.stat.correlation.Correlation
Compute correlation for two datasets.
computeCorrelation(RDD<Object>, RDD<Object>) - Static method in class org.apache.spark.mllib.stat.correlation.PearsonCorrelation
Compute the Pearson correlation for two datasets.
computeCorrelation(RDD<Object>, RDD<Object>) - Static method in class org.apache.spark.mllib.stat.correlation.SpearmanCorrelation
Compute Spearman's correlation for two datasets.
computeCorrelationMatrix(RDD<Vector>) - Method in interface org.apache.spark.mllib.stat.correlation.Correlation
Compute the correlation matrix S, for the input matrix, where S(i, j) is the correlation between column i and j.
computeCorrelationMatrix(RDD<Vector>) - Static method in class org.apache.spark.mllib.stat.correlation.PearsonCorrelation
Compute the Pearson correlation matrix S, for the input matrix, where S(i, j) is the correlation between column i and j.
computeCorrelationMatrix(RDD<Vector>) - Static method in class org.apache.spark.mllib.stat.correlation.SpearmanCorrelation
Compute Spearman's correlation matrix S, for the input matrix, where S(i, j) is the correlation between column i and j.
computeCorrelationMatrixFromCovariance(Matrix) - Static method in class org.apache.spark.mllib.stat.correlation.PearsonCorrelation
Compute the Pearson correlation matrix from the covariance matrix.
computeCorrelationWithMatrixImpl(RDD<Object>, RDD<Object>) - Method in interface org.apache.spark.mllib.stat.correlation.Correlation
Combine the two input RDD[Double]s into an RDD[Vector] and compute the correlation using the correlation implementation for RDD[Vector].
computeCorrelationWithMatrixImpl(RDD<Object>, RDD<Object>) - Static method in class org.apache.spark.mllib.stat.correlation.PearsonCorrelation
 
computeCorrelationWithMatrixImpl(RDD<Object>, RDD<Object>) - Static method in class org.apache.spark.mllib.stat.correlation.SpearmanCorrelation
 
computeCost(Dataset<?>) - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
Computes the sum of squared distances between the input points and their corresponding cluster centers.
computeCost(Dataset<?>) - Method in class org.apache.spark.ml.clustering.KMeansModel
Deprecated.
This method is deprecated and will be removed in 3.0.0. Use ClusteringEvaluator instead. You can also get the cost on the training dataset in the summary.
computeCost(Vector) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
Computes the squared distance between the input point and the cluster center it belongs to.
computeCost(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
Computes the sum of squared distances between the input points and their corresponding cluster centers.
computeCost(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
Java-friendly version of computeCost().
computeCost(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.KMeansModel
Return the K-means cost (sum of squared distances of points to their nearest center) for this model on the given data.
computeCovariance() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
Computes the covariance matrix, treating each row as an observation.
computeError(RDD<LabeledPoint>, DecisionTreeRegressionModel[], double[], Loss) - Static method in class org.apache.spark.ml.tree.impl.GradientBoostedTrees
Method to calculate error of the base learner for the gradient boosting calculation.
computeError(org.apache.spark.mllib.tree.model.TreeEnsembleModel, RDD<LabeledPoint>) - Method in interface org.apache.spark.mllib.tree.loss.Loss
Method to calculate error of the base learner for the gradient boosting calculation.
computeError(double, double) - Method in interface org.apache.spark.mllib.tree.loss.Loss
Method to calculate loss when the predictions are already known.
computeFractionForSampleSize(int, long, boolean) - Static method in class org.apache.spark.util.random.SamplingUtils
Returns a sampling rate that guarantees a sample of size greater than or equal to sampleSizeLowerBound 99.99% of the time.
computeGradient(DenseMatrix<Object>, DenseMatrix<Object>, Vector, int) - Method in interface org.apache.spark.ml.ann.TopologyModel
Computes gradient for the network
computeGramianMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
Computes the Gramian matrix A^T A.
computeGramianMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
Computes the Gramian matrix A^T A.
computeInitialPredictionAndError(RDD<LabeledPoint>, double, DecisionTreeRegressionModel, Loss) - Static method in class org.apache.spark.ml.tree.impl.GradientBoostedTrees
Compute the initial predictions and errors for a dataset for the first iteration of gradient boosting.
computeInitialPredictionAndError(RDD<LabeledPoint>, double, DecisionTreeModel, Loss) - Static method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
:: DeveloperApi :: Compute the initial predictions and errors for a dataset for the first iteration of gradient boosting.
computePreferredLocations(Seq<InputFormatInfo>) - Static method in class org.apache.spark.scheduler.InputFormatInfo
Computes the preferred locations based on input(s) and returned a location to block map.
computePrevDelta(DenseMatrix<Object>, DenseMatrix<Object>, DenseMatrix<Object>) - Method in interface org.apache.spark.ml.ann.LayerModel
Computes the delta for back propagation.
computePrincipalComponents(int) - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
Computes the top k principal components only.
computePrincipalComponentsAndExplainedVariance(int) - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
Computes the top k principal components and a vector of proportions of variance explained by each principal component.
computeProbability(double) - Method in interface org.apache.spark.mllib.tree.loss.ClassificationLoss
Computes the class probability given the margin.
computeSilhouetteCoefficient(Broadcast<Map<Object, Tuple2<Vector, Object>>>, Vector, double) - Static method in class org.apache.spark.ml.evaluation.CosineSilhouette
It computes the Silhouette coefficient for a point.
computeSilhouetteCoefficient(Broadcast<Map<Object, SquaredEuclideanSilhouette.ClusterStats>>, Vector, double, double) - Static method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette
It computes the Silhouette coefficient for a point.
computeSilhouetteScore(Dataset<?>, String, String) - Static method in class org.apache.spark.ml.evaluation.CosineSilhouette
Compute the Silhouette score of the dataset using the cosine distance measure.
computeSilhouetteScore(Dataset<?>, String, String) - Static method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette
Compute the Silhouette score of the dataset using squared Euclidean distance measure.
computeSVD(int, boolean, double) - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
Computes the singular value decomposition of this IndexedRowMatrix.
computeSVD(int, boolean, double) - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
Computes singular value decomposition of this matrix.
computeThresholdByKey(Map<K, AcceptanceResult>, Map<K, Object>) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
Given the result returned by getCounts, determine the threshold for accepting items to generate exact sample size.
concat(Column...) - Static method in class org.apache.spark.sql.functions
Concatenates multiple input columns together into a single column.
concat(Seq<Column>) - Static method in class org.apache.spark.sql.functions
Concatenates multiple input columns together into a single column.
concat_ws(String, Column...) - Static method in class org.apache.spark.sql.functions
Concatenates multiple input string columns together into a single string column, using the given separator.
concat_ws(String, Seq<Column>) - Static method in class org.apache.spark.sql.functions
Concatenates multiple input string columns together into a single string column, using the given separator.
Conf(int, int, double, double, double, double, double, double) - Constructor for class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
 
conf() - Method in interface org.apache.spark.input.Configurable
 
conf() - Method in class org.apache.spark.SparkEnv
 
conf() - Method in class org.apache.spark.sql.hive.RelationConversions
 
conf() - Method in class org.apache.spark.sql.SparkSession
Runtime configuration interface for Spark.
confidence() - Method in class org.apache.spark.mllib.fpm.AssociationRules.Rule
Returns the confidence of the rule.
confidence() - Method in class org.apache.spark.partial.BoundedDouble
 
confidence() - Method in class org.apache.spark.util.sketch.CountMinSketch
Returns the confidence (or delta) of this CountMinSketch.
config(String, String) - Method in class org.apache.spark.sql.SparkSession.Builder
Sets a config option.
config(String, long) - Method in class org.apache.spark.sql.SparkSession.Builder
Sets a config option.
config(String, double) - Method in class org.apache.spark.sql.SparkSession.Builder
Sets a config option.
config(String, boolean) - Method in class org.apache.spark.sql.SparkSession.Builder
Sets a config option.
config(SparkConf) - Method in class org.apache.spark.sql.SparkSession.Builder
Sets a list of config options based on the given SparkConf.
config - Class in org.apache.spark.status
 
config() - Constructor for class org.apache.spark.status.config
 
ConfigEntryWithDefault<T> - Class in org.apache.spark.internal.config
 
ConfigEntryWithDefault(String, List<String>, T, Function1<String, T>, Function1<T, String>, String, boolean) - Constructor for class org.apache.spark.internal.config.ConfigEntryWithDefault
 
ConfigEntryWithDefaultFunction<T> - Class in org.apache.spark.internal.config
 
ConfigEntryWithDefaultFunction(String, List<String>, Function0<T>, Function1<String, T>, Function1<T, String>, String, boolean) - Constructor for class org.apache.spark.internal.config.ConfigEntryWithDefaultFunction
 
ConfigEntryWithDefaultString<T> - Class in org.apache.spark.internal.config
 
ConfigEntryWithDefaultString(String, List<String>, String, Function1<String, T>, Function1<T, String>, String, boolean) - Constructor for class org.apache.spark.internal.config.ConfigEntryWithDefaultString
 
ConfigHelpers - Class in org.apache.spark.internal.config
 
ConfigHelpers() - Constructor for class org.apache.spark.internal.config.ConfigHelpers
 
ConfigProvider - Interface in org.apache.spark.internal.config
A source of configuration values.
configTestLog4j(String) - Static method in class org.apache.spark.TestUtils
config a log4j properties used for testsuite
Configurable - Interface in org.apache.spark.input
A trait to implement Configurable interface.
configuration() - Method in class org.apache.spark.scheduler.InputFormatInfo
 
CONFIGURATION_INSTANTIATION_LOCK() - Static method in class org.apache.spark.rdd.HadoopRDD
Configuration's constructor is not threadsafe (see SPARK-1097 and HADOOP-10456).
CONFIGURATION_INSTANTIATION_LOCK() - Static method in class org.apache.spark.rdd.NewHadoopRDD
Configuration's constructor is not threadsafe (see SPARK-1097 and HADOOP-10456).
configureJobPropertiesForStorageHandler(TableDesc, Configuration, boolean) - Static method in class org.apache.spark.sql.hive.HiveTableUtil
 
confusionMatrix() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns confusion matrix: predicted classes are in columns, they are ordered by class label ascending, as in "labels"
connectedComponents() - Method in class org.apache.spark.graphx.GraphOps
Compute the connected component membership of each vertex and return a graph with the vertex value containing the lowest vertex id in the connected component containing that vertex.
connectedComponents(int) - Method in class org.apache.spark.graphx.GraphOps
Compute the connected component membership of each vertex and return a graph with the vertex value containing the lowest vertex id in the connected component containing that vertex.
ConnectedComponents - Class in org.apache.spark.graphx.lib
Connected components algorithm.
ConnectedComponents() - Constructor for class org.apache.spark.graphx.lib.ConnectedComponents
 
consequent() - Method in class org.apache.spark.mllib.fpm.AssociationRules.Rule
 
ConstantInputDStream<T> - Class in org.apache.spark.streaming.dstream
An input stream that always returns the same RDD on each time step.
ConstantInputDStream(StreamingContext, RDD<T>, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.ConstantInputDStream
 
constructTree(org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0.NodeData[]) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
Given a list of nodes from a tree, construct the tree.
constructTrees(RDD<org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0.NodeData>) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
 
constructURIForAuthentication(URI, org.apache.spark.SecurityManager) - Static method in class org.apache.spark.util.Utils
Construct a URI container information used for authentication.
contains(Param<?>) - Method in class org.apache.spark.ml.param.ParamMap
Checks whether a parameter is explicitly specified.
contains(String) - Method in class org.apache.spark.SparkConf
Does the configuration contain a given parameter?
contains(Object) - Method in class org.apache.spark.sql.Column
Contains the other element.
contains(String) - Method in class org.apache.spark.sql.types.Metadata
Tests whether this Metadata contains a binding for a key.
containsDelimiters() - Method in class org.apache.spark.sql.hive.execution.HiveOptions
 
containsKey(Object) - Method in class org.apache.spark.api.java.JavaUtils.SerializableMapWrapper
 
containsNull() - Method in class org.apache.spark.sql.types.ArrayType
 
contentType() - Method in class org.apache.spark.ui.JettyUtils.ServletParams
 
context() - Method in interface org.apache.spark.api.java.JavaRDDLike
The SparkContext that this RDD was created on.
context() - Method in class org.apache.spark.InterruptibleIterator
 
context(SQLContext) - Static method in class org.apache.spark.ml.r.RWrappers
 
context(SQLContext) - Method in interface org.apache.spark.ml.util.BaseReadWrite
Deprecated.
Use session instead. This method will be removed in 3.0.0.
context(SQLContext) - Method in class org.apache.spark.ml.util.GeneralMLWriter
 
context(SQLContext) - Method in class org.apache.spark.ml.util.MLReader
 
context(SQLContext) - Method in class org.apache.spark.ml.util.MLWriter
 
context() - Method in class org.apache.spark.rdd.RDD
The SparkContext that this RDD was created on.
context() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return the StreamingContext associated with this DStream
context() - Method in class org.apache.spark.streaming.dstream.DStream
Return the StreamingContext associated with this DStream
ContextBarrierId - Class in org.apache.spark
For each barrier stage attempt, only at most one barrier() call can be active at any time, thus we can use (stageId, stageAttemptId) to identify the stage attempt where the barrier() call is from.
ContextBarrierId(int, int) - Constructor for class org.apache.spark.ContextBarrierId
 
Continuous() - Static method in class org.apache.spark.mllib.tree.configuration.FeatureType
 
Continuous(long) - Static method in class org.apache.spark.sql.streaming.Trigger
A trigger that continuously processes streaming data, asynchronously checkpointing at the specified interval.
Continuous(long, TimeUnit) - Static method in class org.apache.spark.sql.streaming.Trigger
A trigger that continuously processes streaming data, asynchronously checkpointing at the specified interval.
Continuous(Duration) - Static method in class org.apache.spark.sql.streaming.Trigger
(Scala-friendly) A trigger that continuously processes streaming data, asynchronously checkpointing at the specified interval.
Continuous(String) - Static method in class org.apache.spark.sql.streaming.Trigger
A trigger that continuously processes streaming data, asynchronously checkpointing at the specified interval.
ContinuousInputPartition<T> - Interface in org.apache.spark.sql.sources.v2.reader
A mix-in interface for InputPartition.
ContinuousInputPartitionReader<T> - Interface in org.apache.spark.sql.sources.v2.reader.streaming
A variation on InputPartitionReader for use with streaming in continuous processing mode.
ContinuousReader - Interface in org.apache.spark.sql.sources.v2.reader.streaming
A mix-in interface for DataSourceReader.
ContinuousReadSupport - Interface in org.apache.spark.sql.sources.v2
A mix-in interface for DataSourceV2.
ContinuousSplit - Class in org.apache.spark.ml.tree
Split which tests a continuous feature.
conv(Column, int, int) - Static method in class org.apache.spark.sql.functions
Convert a number in a string column from one base to another.
CONVERT_METASTORE_ORC() - Static method in class org.apache.spark.sql.hive.HiveUtils
 
CONVERT_METASTORE_PARQUET() - Static method in class org.apache.spark.sql.hive.HiveUtils
 
CONVERT_METASTORE_PARQUET_WITH_SCHEMA_MERGING() - Static method in class org.apache.spark.sql.hive.HiveUtils
 
convertMatrixColumnsFromML(Dataset<?>, String...) - Static method in class org.apache.spark.mllib.util.MLUtils
Converts matrix columns in an input Dataset to the Matrix type from the new Matrix type under the spark.ml package.
convertMatrixColumnsFromML(Dataset<?>, Seq<String>) - Static method in class org.apache.spark.mllib.util.MLUtils
Converts matrix columns in an input Dataset to the Matrix type from the new Matrix type under the spark.ml package.
convertMatrixColumnsToML(Dataset<?>, String...) - Static method in class org.apache.spark.mllib.util.MLUtils
Converts Matrix columns in an input Dataset from the Matrix type to the new Matrix type under the spark.ml package.
convertMatrixColumnsToML(Dataset<?>, Seq<String>) - Static method in class org.apache.spark.mllib.util.MLUtils
Converts Matrix columns in an input Dataset from the Matrix type to the new Matrix type under the spark.ml package.
convertToCanonicalEdges(Function2<ED, ED, ED>) - Method in class org.apache.spark.graphx.GraphOps
Convert bi-directional edges into uni-directional ones.
convertToOldLossType(String) - Method in interface org.apache.spark.ml.tree.GBTRegressorParams
 
convertToTimeUnit(long, TimeUnit) - Static method in class org.apache.spark.streaming.ui.UIUtils
Convert milliseconds to the specified unit.
convertVectorColumnsFromML(Dataset<?>, String...) - Static method in class org.apache.spark.mllib.util.MLUtils
Converts vector columns in an input Dataset to the Vector type from the new Vector type under the spark.ml package.
convertVectorColumnsFromML(Dataset<?>, Seq<String>) - Static method in class org.apache.spark.mllib.util.MLUtils
Converts vector columns in an input Dataset to the Vector type from the new Vector type under the spark.ml package.
convertVectorColumnsToML(Dataset<?>, String...) - Static method in class org.apache.spark.mllib.util.MLUtils
Converts vector columns in an input Dataset from the Vector type to the new Vector type under the spark.ml package.
convertVectorColumnsToML(Dataset<?>, Seq<String>) - Static method in class org.apache.spark.mllib.util.MLUtils
Converts vector columns in an input Dataset from the Vector type to the new Vector type under the spark.ml package.
CoordinateMatrix - Class in org.apache.spark.mllib.linalg.distributed
Represents a matrix in coordinate format.
CoordinateMatrix(RDD<MatrixEntry>, long, long) - Constructor for class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
 
CoordinateMatrix(RDD<MatrixEntry>) - Constructor for class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
Alternative constructor leaving matrix dimensions to be determined automatically.
copy(ParamMap) - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.GBTClassificationModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.LinearSVC
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.LinearSVCModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.LogisticRegression
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.NaiveBayes
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.NaiveBayesModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.OneVsRest
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.OneVsRestModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
 
copy(ParamMap) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
 
copy(ParamMap) - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.clustering.DistributedLDAModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.clustering.GaussianMixture
 
copy(ParamMap) - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.clustering.KMeans
 
copy(ParamMap) - Method in class org.apache.spark.ml.clustering.KMeansModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.clustering.LDA
 
copy(ParamMap) - Method in class org.apache.spark.ml.clustering.LocalLDAModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.clustering.PowerIterationClustering
 
copy(ParamMap) - Method in class org.apache.spark.ml.Estimator
 
copy(ParamMap) - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
 
copy(ParamMap) - Method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
copy(ParamMap) - Method in class org.apache.spark.ml.evaluation.Evaluator
 
copy(ParamMap) - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
 
copy(ParamMap) - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.Binarizer
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.Bucketizer
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.ChiSqSelector
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.ChiSqSelectorModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.ColumnPruner
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.CountVectorizer
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.CountVectorizerModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.FeatureHasher
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.HashingTF
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.IDF
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.IDFModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.Imputer
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.ImputerModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.IndexToString
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.Interaction
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.MaxAbsScaler
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.MaxAbsScalerModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.MinHashLSH
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.MinHashLSHModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.MinMaxScaler
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.OneHotEncoder
Deprecated.
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.OneHotEncoderModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.PCA
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.PCAModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.PolynomialExpansion
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.RegexTokenizer
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.RFormula
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.RFormulaModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.SQLTransformer
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.StandardScaler
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.StandardScalerModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.StopWordsRemover
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.StringIndexer
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.StringIndexerModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.Tokenizer
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.VectorAssembler
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.VectorAttributeRewriter
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.VectorIndexer
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.VectorIndexerModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.VectorSizeHint
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.VectorSlicer
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.Word2Vec
 
copy(ParamMap) - Method in class org.apache.spark.ml.feature.Word2VecModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.fpm.FPGrowth
 
copy(ParamMap) - Method in class org.apache.spark.ml.fpm.FPGrowthModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.fpm.PrefixSpan
 
copy(Vector, Vector) - Static method in class org.apache.spark.ml.linalg.BLAS
y = x
copy() - Method in class org.apache.spark.ml.linalg.DenseMatrix
 
copy() - Method in class org.apache.spark.ml.linalg.DenseVector
 
copy() - Method in interface org.apache.spark.ml.linalg.Matrix
Get a deep copy of the matrix.
copy() - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
copy() - Method in class org.apache.spark.ml.linalg.SparseVector
 
copy() - Method in interface org.apache.spark.ml.linalg.Vector
Makes a deep copy of this vector.
copy(ParamMap) - Method in class org.apache.spark.ml.Model
 
copy() - Method in class org.apache.spark.ml.param.ParamMap
Creates a copy of this param map.
copy(ParamMap) - Method in interface org.apache.spark.ml.param.Params
Creates a copy of this instance with the same UID and some extra params.
copy(ParamMap) - Method in class org.apache.spark.ml.Pipeline
 
copy(ParamMap) - Method in class org.apache.spark.ml.PipelineModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.PipelineStage
 
copy(ParamMap) - Method in class org.apache.spark.ml.Predictor
 
copy(ParamMap) - Method in class org.apache.spark.ml.recommendation.ALS
 
copy(ParamMap) - Method in class org.apache.spark.ml.recommendation.ALSModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.GBTRegressionModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.IsotonicRegression
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.LinearRegression
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.LinearRegressionModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.RandomForestRegressionModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
 
copy(ParamMap) - Method in class org.apache.spark.ml.Transformer
 
copy(ParamMap) - Method in class org.apache.spark.ml.tuning.CrossValidator
 
copy(ParamMap) - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
 
copy(ParamMap) - Method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
 
copy(ParamMap) - Method in class org.apache.spark.ml.UnaryTransformer
 
copy(Vector, Vector) - Static method in class org.apache.spark.mllib.linalg.BLAS
y = x
copy() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
 
copy() - Method in class org.apache.spark.mllib.linalg.DenseVector
 
copy() - Method in interface org.apache.spark.mllib.linalg.Matrix
Get a deep copy of the matrix.
copy() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
copy() - Method in class org.apache.spark.mllib.linalg.SparseVector
 
copy() - Method in interface org.apache.spark.mllib.linalg.Vector
Makes a deep copy of this vector.
copy() - Method in class org.apache.spark.mllib.random.ExponentialGenerator
 
copy() - Method in class org.apache.spark.mllib.random.GammaGenerator
 
copy() - Method in class org.apache.spark.mllib.random.LogNormalGenerator
 
copy() - Method in class org.apache.spark.mllib.random.PoissonGenerator
 
copy() - Method in interface org.apache.spark.mllib.random.RandomDataGenerator
Returns a copy of the RandomDataGenerator with a new instance of the rng object used in the class when applicable for non-locking concurrent usage.
copy() - Method in class org.apache.spark.mllib.random.StandardNormalGenerator
 
copy() - Method in class org.apache.spark.mllib.random.UniformGenerator
 
copy() - Method in class org.apache.spark.mllib.random.WeibullGenerator
 
copy() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
Returns a shallow copy of this instance.
copy() - Method in interface org.apache.spark.sql.Row
Make a copy of the current Row object.
copy() - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
copy() - Method in class org.apache.spark.sql.vectorized.ColumnarMap
 
copy() - Method in class org.apache.spark.sql.vectorized.ColumnarRow
Revisit this.
copy() - Method in class org.apache.spark.util.AccumulatorV2
Creates a new copy of this accumulator.
copy() - Method in class org.apache.spark.util.CollectionAccumulator
 
copy() - Method in class org.apache.spark.util.DoubleAccumulator
 
copy() - Method in class org.apache.spark.util.LegacyAccumulatorWrapper
 
copy() - Method in class org.apache.spark.util.LongAccumulator
 
copy() - Method in class org.apache.spark.util.StatCounter
Clone this StatCounter
copyAndReset() - Method in class org.apache.spark.util.AccumulatorV2
Creates a new copy of this accumulator, which is zero value.
copyAndReset() - Method in class org.apache.spark.util.CollectionAccumulator
 
copyFileStreamNIO(FileChannel, FileChannel, long, long) - Static method in class org.apache.spark.util.Utils
 
copyStream(InputStream, OutputStream, boolean, boolean) - Static method in class org.apache.spark.util.Utils
Copy all data from an InputStream to an OutputStream.
copyValues(T, ParamMap) - Method in interface org.apache.spark.ml.param.Params
Copies param values from this instance to another instance for params shared by them.
cores() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor
 
coresGranted() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
 
coresPerExecutor() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
 
corr(Dataset<?>, String, String) - Static method in class org.apache.spark.ml.stat.Correlation
:: Experimental :: Compute the correlation matrix for the input Dataset of Vectors using the specified method.
corr(Dataset<?>, String) - Static method in class org.apache.spark.ml.stat.Correlation
Compute the Pearson correlation matrix for the input Dataset of Vectors.
corr(RDD<Object>, RDD<Object>, String) - Static method in class org.apache.spark.mllib.stat.correlation.Correlations
 
corr(RDD<Vector>) - Static method in class org.apache.spark.mllib.stat.Statistics
Compute the Pearson correlation matrix for the input RDD of Vectors.
corr(RDD<Vector>, String) - Static method in class org.apache.spark.mllib.stat.Statistics
Compute the correlation matrix for the input RDD of Vectors using the specified method.
corr(RDD<Object>, RDD<Object>) - Static method in class org.apache.spark.mllib.stat.Statistics
Compute the Pearson correlation for the input RDDs.
corr(JavaRDD<Double>, JavaRDD<Double>) - Static method in class org.apache.spark.mllib.stat.Statistics
Java-friendly version of corr()
corr(RDD<Object>, RDD<Object>, String) - Static method in class org.apache.spark.mllib.stat.Statistics
Compute the correlation for the input RDDs using the specified method.
corr(JavaRDD<Double>, JavaRDD<Double>, String) - Static method in class org.apache.spark.mllib.stat.Statistics
Java-friendly version of corr()
corr(String, String, String) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Calculates the correlation of two columns of a DataFrame.
corr(String, String) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Calculates the Pearson Correlation Coefficient of two columns of a DataFrame.
corr(Column, Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the Pearson Correlation Coefficient for two columns.
corr(String, String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the Pearson Correlation Coefficient for two columns.
Correlation - Class in org.apache.spark.ml.stat
API for correlation functions in MLlib, compatible with DataFrames and Datasets.
Correlation() - Constructor for class org.apache.spark.ml.stat.Correlation
 
Correlation - Interface in org.apache.spark.mllib.stat.correlation
Trait for correlation algorithms.
CorrelationNames - Class in org.apache.spark.mllib.stat.correlation
Maintains supported and default correlation names.
CorrelationNames() - Constructor for class org.apache.spark.mllib.stat.correlation.CorrelationNames
 
Correlations - Class in org.apache.spark.mllib.stat.correlation
Delegates computation to the specific correlation object based on the input method name.
Correlations() - Constructor for class org.apache.spark.mllib.stat.correlation.Correlations
 
corrMatrix(RDD<Vector>, String) - Static method in class org.apache.spark.mllib.stat.correlation.Correlations
 
cos(Column) - Static method in class org.apache.spark.sql.functions
 
cos(String) - Static method in class org.apache.spark.sql.functions
 
cosh(Column) - Static method in class org.apache.spark.sql.functions
 
cosh(String) - Static method in class org.apache.spark.sql.functions
 
CosineSilhouette - Class in org.apache.spark.ml.evaluation
The algorithm which is implemented in this object, instead, is an efficient and parallel implementation of the Silhouette using the cosine distance measure.
CosineSilhouette() - Constructor for class org.apache.spark.ml.evaluation.CosineSilhouette
 
count() - Method in interface org.apache.spark.api.java.JavaRDDLike
Return the number of elements in the RDD.
count() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
The number of edges in the RDD.
count() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
The number of vertices in the RDD.
count() - Method in class org.apache.spark.ml.clustering.ExpectationAggregator
 
count() - Method in class org.apache.spark.ml.regression.AFTAggregator
 
count(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
count(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
count() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
Sample size.
count() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
Sample size.
count() - Method in class org.apache.spark.rdd.RDD
Return the number of elements in the RDD.
count() - Method in class org.apache.spark.sql.Dataset
Returns the number of rows in the Dataset.
count(MapFunction<T, Object>) - Static method in class org.apache.spark.sql.expressions.javalang.typed
Count aggregate function.
count(Function1<IN, Object>) - Static method in class org.apache.spark.sql.expressions.scalalang.typed
Count aggregate function.
count(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the number of items in a group.
count(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the number of items in a group.
count() - Method in class org.apache.spark.sql.KeyValueGroupedDataset
Returns a Dataset that contains a tuple with each key and the number of items present for that key.
count() - Method in class org.apache.spark.sql.RelationalGroupedDataset
Count the number of rows for each group.
count() - Method in class org.apache.spark.status.RDDPartitionSeq
 
count() - Method in class org.apache.spark.storage.ReadableChannelFileRegion
 
count() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD has a single element generated by counting each RDD of this DStream.
count() - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD has a single element generated by counting each RDD of this DStream.
count() - Method in class org.apache.spark.util.DoubleAccumulator
Returns the number of elements added to the accumulator.
count() - Method in class org.apache.spark.util.LongAccumulator
Returns the number of elements added to the accumulator.
count() - Method in class org.apache.spark.util.StatCounter
 
countApprox(long, double) - Method in interface org.apache.spark.api.java.JavaRDDLike
Approximate version of count() that returns a potentially incomplete result within a timeout, even if not all tasks have finished.
countApprox(long) - Method in interface org.apache.spark.api.java.JavaRDDLike
Approximate version of count() that returns a potentially incomplete result within a timeout, even if not all tasks have finished.
countApprox(long, double) - Method in class org.apache.spark.rdd.RDD
Approximate version of count() that returns a potentially incomplete result within a timeout, even if not all tasks have finished.
countApproxDistinct(double) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return approximate number of distinct elements in the RDD.
countApproxDistinct(int, int) - Method in class org.apache.spark.rdd.RDD
Return approximate number of distinct elements in the RDD.
countApproxDistinct(double) - Method in class org.apache.spark.rdd.RDD
Return approximate number of distinct elements in the RDD.
countApproxDistinctByKey(double, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
Return approximate number of distinct values for each key in this RDD.
countApproxDistinctByKey(double, int) - Method in class org.apache.spark.api.java.JavaPairRDD
Return approximate number of distinct values for each key in this RDD.
countApproxDistinctByKey(double) - Method in class org.apache.spark.api.java.JavaPairRDD
Return approximate number of distinct values for each key in this RDD.
countApproxDistinctByKey(int, int, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return approximate number of distinct values for each key in this RDD.
countApproxDistinctByKey(double, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return approximate number of distinct values for each key in this RDD.
countApproxDistinctByKey(double, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return approximate number of distinct values for each key in this RDD.
countApproxDistinctByKey(double) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return approximate number of distinct values for each key in this RDD.
countAsync() - Method in interface org.apache.spark.api.java.JavaRDDLike
The asynchronous version of count, which returns a future for counting the number of elements in this RDD.
countAsync() - Method in class org.apache.spark.rdd.AsyncRDDActions
Returns a future for counting the number of elements in the RDD.
countByKey() - Method in class org.apache.spark.api.java.JavaPairRDD
Count the number of elements for each key, and return the result to the master as a Map.
countByKey() - Method in class org.apache.spark.rdd.PairRDDFunctions
Count the number of elements for each key, collecting the results to a local Map.
countByKeyApprox(long) - Method in class org.apache.spark.api.java.JavaPairRDD
Approximate version of countByKey that can return a partial result if it does not finish within a timeout.
countByKeyApprox(long, double) - Method in class org.apache.spark.api.java.JavaPairRDD
Approximate version of countByKey that can return a partial result if it does not finish within a timeout.
countByKeyApprox(long, double) - Method in class org.apache.spark.rdd.PairRDDFunctions
Approximate version of countByKey that can return a partial result if it does not finish within a timeout.
countByValue() - Method in interface org.apache.spark.api.java.JavaRDDLike
Return the count of each unique value in this RDD as a map of (value, count) pairs.
countByValue(Ordering<T>) - Method in class org.apache.spark.rdd.RDD
Return the count of each unique value in this RDD as a local map of (value, count) pairs.
countByValue() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD contains the counts of each distinct value in each RDD of this DStream.
countByValue(int) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD contains the counts of each distinct value in each RDD of this DStream.
countByValue(int, Ordering<T>) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD contains the counts of each distinct value in each RDD of this DStream.
countByValueAndWindow(Duration, Duration) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD contains the count of distinct elements in RDDs in a sliding window over this DStream.
countByValueAndWindow(Duration, Duration, int) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD contains the count of distinct elements in RDDs in a sliding window over this DStream.
countByValueAndWindow(Duration, Duration, int, Ordering<T>) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD contains the count of distinct elements in RDDs in a sliding window over this DStream.
countByValueApprox(long, double) - Method in interface org.apache.spark.api.java.JavaRDDLike
Approximate version of countByValue().
countByValueApprox(long) - Method in interface org.apache.spark.api.java.JavaRDDLike
Approximate version of countByValue().
countByValueApprox(long, double, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
Approximate version of countByValue().
countByWindow(Duration, Duration) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD has a single element generated by counting the number of elements in a window over this DStream.
countByWindow(Duration, Duration) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD has a single element generated by counting the number of elements in a sliding window over this DStream.
countDistinct(Column, Column...) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the number of distinct items in a group.
countDistinct(String, String...) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the number of distinct items in a group.
countDistinct(Column, Seq<Column>) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the number of distinct items in a group.
countDistinct(String, Seq<String>) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the number of distinct items in a group.
COUNTER() - Static method in class org.apache.spark.metrics.sink.StatsdMetricType
 
CountingWritableChannel - Class in org.apache.spark.storage
 
CountingWritableChannel(WritableByteChannel) - Constructor for class org.apache.spark.storage.CountingWritableChannel
 
countMinSketch(String, int, int, int) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Builds a Count-min Sketch over a specified column.
countMinSketch(String, double, double, int) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Builds a Count-min Sketch over a specified column.
countMinSketch(Column, int, int, int) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Builds a Count-min Sketch over a specified column.
countMinSketch(Column, double, double, int) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Builds a Count-min Sketch over a specified column.
CountMinSketch - Class in org.apache.spark.util.sketch
A Count-min sketch is a probabilistic data structure used for cardinality estimation using sub-linear space.
CountMinSketch() - Constructor for class org.apache.spark.util.sketch.CountMinSketch
 
CountMinSketch.Version - Enum in org.apache.spark.util.sketch
 
countTowardsTaskFailures() - Method in class org.apache.spark.ExecutorLostFailure
 
countTowardsTaskFailures() - Method in class org.apache.spark.FetchFailed
Fetch failures lead to a different failure handling path: (1) we don't abort the stage after 4 task failures, instead we immediately go back to the stage which generated the map output, and regenerate the missing data.
countTowardsTaskFailures() - Static method in class org.apache.spark.Resubmitted
 
countTowardsTaskFailures() - Method in class org.apache.spark.TaskCommitDenied
If a task failed because its attempt to commit was denied, do not count this failure towards failing the stage.
countTowardsTaskFailures() - Method in interface org.apache.spark.TaskFailedReason
Whether this task failure should be counted towards the maximum number of times the task is allowed to fail before the stage is aborted.
countTowardsTaskFailures() - Method in class org.apache.spark.TaskKilled
 
countTowardsTaskFailures() - Static method in class org.apache.spark.TaskResultLost
 
countTowardsTaskFailures() - Static method in class org.apache.spark.UnknownReason
 
CountVectorizer - Class in org.apache.spark.ml.feature
Extracts a vocabulary from document collections and generates a CountVectorizerModel.
CountVectorizer(String) - Constructor for class org.apache.spark.ml.feature.CountVectorizer
 
CountVectorizer() - Constructor for class org.apache.spark.ml.feature.CountVectorizer
 
CountVectorizerModel - Class in org.apache.spark.ml.feature
Converts a text document to a sparse vector of token counts.
CountVectorizerModel(String, String[]) - Constructor for class org.apache.spark.ml.feature.CountVectorizerModel
 
CountVectorizerModel(String[]) - Constructor for class org.apache.spark.ml.feature.CountVectorizerModel
 
CountVectorizerParams - Interface in org.apache.spark.ml.feature
cov() - Method in class org.apache.spark.ml.stat.distribution.MultivariateGaussian
 
cov(String, String) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Calculate the sample covariance of two numerical columns of a DataFrame.
covar_pop(Column, Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the population covariance for two columns.
covar_pop(String, String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the population covariance for two columns.
covar_samp(Column, Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the sample covariance for two columns.
covar_samp(String, String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the sample covariance for two columns.
covs() - Method in class org.apache.spark.ml.clustering.ExpectationAggregator
 
crc32(Column) - Static method in class org.apache.spark.sql.functions
Calculates the cyclic redundancy check value (CRC32) of a binary column and returns the value as a bigint.
CreatableRelationProvider - Interface in org.apache.spark.sql.sources
 
create(boolean, boolean, boolean, boolean, int) - Static method in class org.apache.spark.api.java.StorageLevels
Create a new StorageLevel object.
create(JavaSparkContext, JdbcRDD.ConnectionFactory, String, long, long, int, Function<ResultSet, T>) - Static method in class org.apache.spark.rdd.JdbcRDD
Create an RDD that executes a SQL query on a JDBC connection and reads results.
create(JavaSparkContext, JdbcRDD.ConnectionFactory, String, long, long, int) - Static method in class org.apache.spark.rdd.JdbcRDD
Create an RDD that executes a SQL query on a JDBC connection and reads results.
create(RDD<T>, Function1<Object, Object>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
Create a PartitionPruningRDD.
create(RpcEnvConfig) - Method in interface org.apache.spark.rpc.RpcEnvFactory
 
create(Object, DataType, Seq<Option<ScalaReflection.Schema>>) - Static method in class org.apache.spark.sql.expressions.SparkUserDefinedFunction
 
create(Object...) - Static method in class org.apache.spark.sql.RowFactory
Create a Row from the given arguments.
create(String) - Static method in class org.apache.spark.sql.streaming.ProcessingTime
Deprecated.
use Trigger.ProcessingTime(interval)
create(long, TimeUnit) - Static method in class org.apache.spark.sql.streaming.ProcessingTime
Deprecated.
use Trigger.ProcessingTime(interval, unit)
create(long) - Static method in class org.apache.spark.util.sketch.BloomFilter
Creates a BloomFilter with the expected number of insertions and a default expected false positive probability of 3%.
create(long, double) - Static method in class org.apache.spark.util.sketch.BloomFilter
Creates a BloomFilter with the expected number of insertions and expected false positive probability.
create(long, long) - Static method in class org.apache.spark.util.sketch.BloomFilter
Creates a BloomFilter with given expectedNumItems and numBits, it will pick an optimal numHashFunctions which can minimize fpp for the bloom filter.
create(int, int, int) - Static method in class org.apache.spark.util.sketch.CountMinSketch
Creates a CountMinSketch with given depth, width, and random seed.
create(double, double, int) - Static method in class org.apache.spark.util.sketch.CountMinSketch
Creates a CountMinSketch with given relative error (eps), confidence, and random seed.
createArrayType(DataType) - Static method in class org.apache.spark.sql.types.DataTypes
Creates an ArrayType by specifying the data type of elements (elementType).
createArrayType(DataType, boolean) - Static method in class org.apache.spark.sql.types.DataTypes
Creates an ArrayType by specifying the data type of elements (elementType) and whether the array contains null values (containsNull).
createAttrGroupForAttrNames(String, int, boolean, boolean) - Static method in class org.apache.spark.ml.feature.OneHotEncoderCommon
Creates an `AttributeGroup` with the required number of `BinaryAttribute`.
createCombiner() - Method in class org.apache.spark.Aggregator
 
createCommitter(int) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
 
createCompiledClass(String, File, TestUtils.JavaSourceFromString, Seq<URL>) - Static method in class org.apache.spark.TestUtils
Creates a compiled class with the source file.
createCompiledClass(String, File, String, String, Seq<URL>) - Static method in class org.apache.spark.TestUtils
Creates a compiled class with the given name.
createContinuousReader(Optional<StructType>, String, DataSourceOptions) - Method in interface org.apache.spark.sql.sources.v2.ContinuousReadSupport
Creates a ContinuousReader to scan the data from this data source.
createContinuousReader(PartitionOffset) - Method in interface org.apache.spark.sql.sources.v2.reader.ContinuousInputPartition
Create an input partition reader with particular offset as its startOffset.
createCryptoInputStream(InputStream, SparkConf, byte[]) - Static method in class org.apache.spark.security.CryptoStreamUtils
Helper method to wrap InputStream with CryptoInputStream for decryption.
createCryptoOutputStream(OutputStream, SparkConf, byte[]) - Static method in class org.apache.spark.security.CryptoStreamUtils
Helper method to wrap OutputStream with CryptoOutputStream for encryption.
createDatabase(CatalogDatabase, boolean) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Creates a new database with the given name.
createDataFrame(RDD<A>, TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.SparkSession
:: Experimental :: Creates a DataFrame from an RDD of Product (e.g.
createDataFrame(Seq<A>, TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.SparkSession
:: Experimental :: Creates a DataFrame from a local Seq of Product.
createDataFrame(RDD<Row>, StructType) - Method in class org.apache.spark.sql.SparkSession
:: DeveloperApi :: Creates a DataFrame from an RDD containing Rows using the given schema.
createDataFrame(JavaRDD<Row>, StructType) - Method in class org.apache.spark.sql.SparkSession
:: DeveloperApi :: Creates a DataFrame from a JavaRDD containing Rows using the given schema.
createDataFrame(List<Row>, StructType) - Method in class org.apache.spark.sql.SparkSession
:: DeveloperApi :: Creates a DataFrame from a java.util.List containing Rows using the given schema.
createDataFrame(RDD<?>, Class<?>) - Method in class org.apache.spark.sql.SparkSession
Applies a schema to an RDD of Java Beans.
createDataFrame(JavaRDD<?>, Class<?>) - Method in class org.apache.spark.sql.SparkSession
Applies a schema to an RDD of Java Beans.
createDataFrame(List<?>, Class<?>) - Method in class org.apache.spark.sql.SparkSession
Applies a schema to a List of Java Beans.
createDataFrame(RDD<A>, TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.SQLContext
 
createDataFrame(Seq<A>, TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.SQLContext
 
createDataFrame(RDD<Row>, StructType) - Method in class org.apache.spark.sql.SQLContext
 
createDataFrame(JavaRDD<Row>, StructType) - Method in class org.apache.spark.sql.SQLContext
 
createDataFrame(List<Row>, StructType) - Method in class org.apache.spark.sql.SQLContext
 
createDataFrame(RDD<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
 
createDataFrame(JavaRDD<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
 
createDataFrame(List<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
 
createDataset(Seq<T>, Encoder<T>) - Method in class org.apache.spark.sql.SparkSession
:: Experimental :: Creates a Dataset from a local Seq of data of a given type.
createDataset(RDD<T>, Encoder<T>) - Method in class org.apache.spark.sql.SparkSession
:: Experimental :: Creates a Dataset from an RDD of a given type.
createDataset(List<T>, Encoder<T>) - Method in class org.apache.spark.sql.SparkSession
:: Experimental :: Creates a Dataset from a java.util.List of a given type.
createDataset(Seq<T>, Encoder<T>) - Method in class org.apache.spark.sql.SQLContext
 
createDataset(RDD<T>, Encoder<T>) - Method in class org.apache.spark.sql.SQLContext
 
createDataset(List<T>, Encoder<T>) - Method in class org.apache.spark.sql.SQLContext
 
createDataWriter(int, long, long) - Method in interface org.apache.spark.sql.sources.v2.writer.DataWriterFactory
Returns a data writer to do the actual writing work.
createDecimalType(int, int) - Static method in class org.apache.spark.sql.types.DataTypes
Creates a DecimalType by specifying the precision and scale.
createDecimalType() - Static method in class org.apache.spark.sql.types.DataTypes
Creates a DecimalType with default precision and scale, which are 10 and 0.
createDF(RDD<byte[]>, StructType, SparkSession) - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
createDirectory(String, String) - Static method in class org.apache.spark.util.Utils
Create a directory inside the given parent directory.
createdTempDir() - Method in interface org.apache.spark.sql.hive.execution.SaveAsHiveFile
 
createExternalTable(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
Deprecated.
use createTable instead. Since 2.2.0.
createExternalTable(String, String, String) - Method in class org.apache.spark.sql.catalog.Catalog
Deprecated.
use createTable instead. Since 2.2.0.
createExternalTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
Deprecated.
use createTable instead. Since 2.2.0.
createExternalTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
Deprecated.
use createTable instead. Since 2.2.0.
createExternalTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
Deprecated.
use createTable instead. Since 2.2.0.
createExternalTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
Deprecated.
use createTable instead. Since 2.2.0.
createExternalTable(String, String) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
use sparkSession.catalog.createTable instead. Since 2.2.0.
createExternalTable(String, String, String) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
use sparkSession.catalog.createTable instead. Since 2.2.0.
createExternalTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
use sparkSession.catalog.createTable instead. Since 2.2.0.
createExternalTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
use sparkSession.catalog.createTable instead. Since 2.2.0.
createExternalTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
use sparkSession.catalog.createTable instead. Since 2.2.0.
createExternalTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
use sparkSession.catalog.createTable instead. Since 2.2.0.
createFilter(StructType, Filter[]) - Static method in class org.apache.spark.sql.hive.orc.OrcFilters
 
createFunction(String, CatalogFunction) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Create a function in an existing database.
createGlobalTempView(String) - Method in class org.apache.spark.sql.Dataset
Creates a global temporary view using the given name.
CreateHiveTableAsSelectCommand - Class in org.apache.spark.sql.hive.execution
Create table and insert the query result into it.
CreateHiveTableAsSelectCommand(CatalogTable, LogicalPlan, Seq<String>, SaveMode) - Constructor for class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
 
createJar(Seq<File>, File, Option<String>) - Static method in class org.apache.spark.TestUtils
Create a jar file that contains this set of files.
createJarWithClasses(Seq<String>, String, Seq<Tuple2<String, String>>, Seq<URL>) - Static method in class org.apache.spark.TestUtils
Create a jar that defines classes with the given names.
createJarWithFiles(Map<String, String>, File) - Static method in class org.apache.spark.TestUtils
Create a jar file containing multiple files.
createJobContext(String, int) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
 
createJobID(Date, int) - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
 
createJobTrackerID(Date) - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
 
createKey(SparkConf) - Static method in class org.apache.spark.security.CryptoStreamUtils
Creates a new encryption key.
createListeners(SparkConf, ElementTrackingStore) - Method in interface org.apache.spark.status.AppHistoryServerPlugin
Creates listeners to replay the event logs.
createLogForDriver(SparkConf, String, Configuration) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
Create a WriteAheadLog for the driver.
createLogForReceiver(SparkConf, String, Configuration) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
Create a WriteAheadLog for the receiver.
createMapType(DataType, DataType) - Static method in class org.apache.spark.sql.types.DataTypes
Creates a MapType by specifying the data type of keys (keyType) and values (keyType).
createMapType(DataType, DataType, boolean) - Static method in class org.apache.spark.sql.types.DataTypes
Creates a MapType by specifying the data type of keys (keyType), the data type of values (keyType), and whether values contain any null value (valueContainsNull).
createMetrics(long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long) - Static method in class org.apache.spark.status.LiveEntityHelpers
 
createMetrics(long) - Static method in class org.apache.spark.status.LiveEntityHelpers
 
createMicroBatchReader(Optional<StructType>, String, DataSourceOptions) - Method in interface org.apache.spark.sql.sources.v2.MicroBatchReadSupport
Creates a MicroBatchReader to read batches of data from this data source in a streaming query.
createModel(DenseVector<Object>) - Method in interface org.apache.spark.ml.ann.Layer
Returns the instance of the layer based on weights provided.
createOrReplaceGlobalTempView(String) - Method in class org.apache.spark.sql.Dataset
Creates or replaces a global temporary view using the given name.
createOrReplaceTempView(String) - Method in class org.apache.spark.sql.Dataset
Creates a local temporary view using the given name.
createOutputOperationFailureForUI(String) - Static method in class org.apache.spark.streaming.ui.UIUtils
 
createPartitionReader() - Method in interface org.apache.spark.sql.sources.v2.reader.InputPartition
Returns an input partition reader to do the actual reading work.
createPartitions(String, String, Seq<CatalogTablePartition>, boolean) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Create one or many partitions in the given table.
createPathFromString(String, JobConf) - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
 
createPMMLModelExport(Object) - Static method in class org.apache.spark.mllib.pmml.export.PMMLModelExportFactory
Factory object to help creating the necessary PMMLModelExport implementation taking as input the machine learning model (for example KMeansModel).
createProxyHandler(Function1<String, Option<String>>) - Static method in class org.apache.spark.ui.JettyUtils
Create a handler for proxying request to Workers and Application Drivers
createProxyLocationHeader(String, HttpServletRequest, URI) - Static method in class org.apache.spark.ui.JettyUtils
 
createProxyURI(String, String, String, String) - Static method in class org.apache.spark.ui.JettyUtils
 
createRDDFromArray(JavaSparkContext, byte[][]) - Static method in class org.apache.spark.api.r.RRDD
Create an RRDD given a sequence of byte arrays.
createRDDFromFile(JavaSparkContext, String, int) - Static method in class org.apache.spark.api.r.RRDD
Create an RRDD given a temporary file name.
createReadableChannel(ReadableByteChannel, SparkConf, byte[]) - Static method in class org.apache.spark.security.CryptoStreamUtils
Wrap a ReadableByteChannel for decryption.
createReader(StructType, DataSourceOptions) - Method in interface org.apache.spark.sql.sources.v2.ReadSupport
Creates a DataSourceReader to scan the data from this data source.
createReader(DataSourceOptions) - Method in interface org.apache.spark.sql.sources.v2.ReadSupport
Creates a DataSourceReader to scan the data from this data source.
createRedirectHandler(String, String, Function1<HttpServletRequest, BoxedUnit>, String, Set<String>) - Static method in class org.apache.spark.ui.JettyUtils
Create a handler that always redirects the user to the given path
createRelation(SQLContext, SaveMode, Map<String, String>, Dataset<Row>) - Method in interface org.apache.spark.sql.sources.CreatableRelationProvider
Saves a DataFrame to a destination (using data source-specific parameters)
createRelation(SQLContext, Map<String, String>) - Method in interface org.apache.spark.sql.sources.RelationProvider
Returns a new base relation with the given parameters.
createRelation(SQLContext, Map<String, String>, StructType) - Method in interface org.apache.spark.sql.sources.SchemaRelationProvider
Returns a new base relation with the given parameters and user defined schema.
createSchedulerBackend(SparkContext, String, TaskScheduler) - Method in interface org.apache.spark.scheduler.ExternalClusterManager
Create a scheduler backend for the given SparkContext and scheduler.
createSecret(SparkConf) - Static method in class org.apache.spark.util.Utils
 
createServlet(JettyUtils.ServletParams<T>, org.apache.spark.SecurityManager, SparkConf) - Static method in class org.apache.spark.ui.JettyUtils
 
createServletHandler(String, JettyUtils.ServletParams<T>, org.apache.spark.SecurityManager, SparkConf, String) - Static method in class org.apache.spark.ui.JettyUtils
Create a context handler that responds to a request with the given path prefix
createServletHandler(String, HttpServlet, String) - Static method in class org.apache.spark.ui.JettyUtils
Create a context handler that responds to a request with the given path prefix
createSink(SQLContext, Map<String, String>, Seq<String>, OutputMode) - Method in interface org.apache.spark.sql.sources.StreamSinkProvider
 
createSource(SQLContext, String, Option<StructType>, String, Map<String, String>) - Method in interface org.apache.spark.sql.sources.StreamSourceProvider
 
createSparkContext(String, String, String, String[], Map<Object, Object>, Map<Object, Object>) - Static method in class org.apache.spark.api.r.RRDD
 
createStaticHandler(String, String) - Static method in class org.apache.spark.ui.JettyUtils
Create a handler for serving files from a static directory
createStream(StreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function1<Record, T>, ClassTag<T>) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
Deprecated.
Use KinesisInputDStream.builder instead. Since 2.2.0.
createStream(StreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function1<Record, T>, String, String, ClassTag<T>) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
Deprecated.
Use KinesisInputDStream.builder instead. Since 2.2.0.
createStream(StreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function1<Record, T>, String, String, String, String, String, ClassTag<T>) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
Deprecated.
Use KinesisInputDStream.builder instead. Since 2.2.0.
createStream(StreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
Deprecated.
Use KinesisInputDStream.builder instead. Since 2.2.0.
createStream(StreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, String, String) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
Deprecated.
Use KinesisInputDStream.builder instead. Since 2.2.0.
createStream(JavaStreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function<Record, T>, Class<T>) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
Deprecated.
Use KinesisInputDStream.builder instead. Since 2.2.0.
createStream(JavaStreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function<Record, T>, Class<T>, String, String) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
Deprecated.
Use KinesisInputDStream.builder instead. Since 2.2.0.
createStream(JavaStreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function<Record, T>, Class<T>, String, String, String, String, String) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
Deprecated.
Use KinesisInputDStream.builder instead. Since 2.2.0.
createStream(JavaStreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
Deprecated.
Use KinesisInputDStream.builder instead. Since 2.2.0.
createStream(JavaStreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, String, String) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
Deprecated.
Use KinesisInputDStream.builder instead. Since 2.2.0.
createStream(JavaStreamingContext, String, String, String, String, int, Duration, StorageLevel, String, String, String, String, String) - Method in class org.apache.spark.streaming.kinesis.KinesisUtilsPythonHelper
 
createStreamWriter(String, StructType, OutputMode, DataSourceOptions) - Method in interface org.apache.spark.sql.sources.v2.StreamWriteSupport
Creates an optional StreamWriter to save the data to this data source.
createStructField(String, String, boolean) - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
createStructField(String, DataType, boolean, Metadata) - Static method in class org.apache.spark.sql.types.DataTypes
Creates a StructField by specifying the name (name), data type (dataType) and whether values of this field can be null values (nullable).
createStructField(String, DataType, boolean) - Static method in class org.apache.spark.sql.types.DataTypes
Creates a StructField with empty metadata.
createStructType(Seq<StructField>) - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
createStructType(List<StructField>) - Static method in class org.apache.spark.sql.types.DataTypes
Creates a StructType with the given list of StructFields (fields).
createStructType(StructField[]) - Static method in class org.apache.spark.sql.types.DataTypes
Creates a StructType with the given StructField array (fields).
createTable(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
:: Experimental :: Creates a table from the given path and returns the corresponding DataFrame.
createTable(String, String, String) - Method in class org.apache.spark.sql.catalog.Catalog
:: Experimental :: Creates a table from the given path based on a data source and returns the corresponding DataFrame.
createTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
:: Experimental :: Creates a table based on the dataset in a data source and a set of options.
createTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
:: Experimental :: (Scala-specific) Creates a table based on the dataset in a data source and a set of options.
createTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
:: Experimental :: Create a table based on the dataset in a data source, a schema and a set of options.
createTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
:: Experimental :: (Scala-specific) Create a table based on the dataset in a data source, a schema and a set of options.
createTable(CatalogTable, boolean) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Creates a table with the given metadata.
createTaskAttemptContext(String, int, int, int) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
 
createTaskScheduler(SparkContext, String) - Method in interface org.apache.spark.scheduler.ExternalClusterManager
Create a task scheduler instance for the given SparkContext
createTempDir(String, String) - Static method in class org.apache.spark.util.Utils
Create a temporary directory inside the given parent directory.
createTempView(String) - Method in class org.apache.spark.sql.Dataset
Creates a local temporary view using the given name.
createUnsafe(long, int, int) - Static method in class org.apache.spark.sql.types.Decimal
Creates a decimal from unscaled, precision and scale without checking the bounds.
createWorkspace(int) - Static method in class org.apache.spark.mllib.optimization.NNLS
 
createWritableChannel(WritableByteChannel, SparkConf, byte[]) - Static method in class org.apache.spark.security.CryptoStreamUtils
Wrap a WritableByteChannel for encryption.
createWriter(String, StructType, SaveMode, DataSourceOptions) - Method in interface org.apache.spark.sql.sources.v2.WriteSupport
Creates an optional DataSourceWriter to save the data to this data source.
createWriterFactory() - Method in interface org.apache.spark.sql.sources.v2.writer.DataSourceWriter
Creates a writer factory which will be serialized and sent to executors.
crossJoin(Dataset<?>) - Method in class org.apache.spark.sql.Dataset
Explicit cartesian join with another DataFrame.
crosstab(String, String) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Computes a pair-wise frequency table of the given columns.
CrossValidator - Class in org.apache.spark.ml.tuning
K-fold cross validation performs model selection by splitting the dataset into a set of non-overlapping randomly partitioned folds which are used as separate training and test datasets e.g., with k=3 folds, K-fold cross validation will generate 3 (training, test) dataset pairs, each of which uses 2/3 of the data for training and 1/3 for testing.
CrossValidator(String) - Constructor for class org.apache.spark.ml.tuning.CrossValidator
 
CrossValidator() - Constructor for class org.apache.spark.ml.tuning.CrossValidator
 
CrossValidatorModel - Class in org.apache.spark.ml.tuning
CrossValidatorModel contains the model with the highest average cross-validation metric across folds and uses this model to transform input data.
CrossValidatorModel.CrossValidatorModelWriter - Class in org.apache.spark.ml.tuning
Writer for CrossValidatorModel.
CrossValidatorParams - Interface in org.apache.spark.ml.tuning
CryptoStreamUtils - Class in org.apache.spark.security
A util class for manipulating IO encryption and decryption streams.
CryptoStreamUtils() - Constructor for class org.apache.spark.security.CryptoStreamUtils
 
CryptoStreamUtils.BaseErrorHandler - Interface in org.apache.spark.security
SPARK-25535.
CryptoStreamUtils.ErrorHandlingReadableChannel - Class in org.apache.spark.security
 
csv(String...) - Method in class org.apache.spark.sql.DataFrameReader
Loads CSV files and returns the result as a DataFrame.
csv(String) - Method in class org.apache.spark.sql.DataFrameReader
Loads a CSV file and returns the result as a DataFrame.
csv(Dataset<String>) - Method in class org.apache.spark.sql.DataFrameReader
Loads an Dataset[String] storing CSV rows and returns the result as a DataFrame.
csv(Seq<String>) - Method in class org.apache.spark.sql.DataFrameReader
Loads CSV files and returns the result as a DataFrame.
csv(String) - Method in class org.apache.spark.sql.DataFrameWriter
Saves the content of the DataFrame in CSV format at the specified path.
csv(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Loads a CSV file stream and returns the result as a DataFrame.
cube(Column...) - Method in class org.apache.spark.sql.Dataset
Create a multi-dimensional cube for the current Dataset using the specified columns, so we can run aggregation on them.
cube(String, String...) - Method in class org.apache.spark.sql.Dataset
Create a multi-dimensional cube for the current Dataset using the specified columns, so we can run aggregation on them.
cube(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
Create a multi-dimensional cube for the current Dataset using the specified columns, so we can run aggregation on them.
cube(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
Create a multi-dimensional cube for the current Dataset using the specified columns, so we can run aggregation on them.
CubeType$() - Constructor for class org.apache.spark.sql.RelationalGroupedDataset.CubeType$
 
cume_dist() - Static method in class org.apache.spark.sql.functions
Window function: returns the cumulative distribution of values within a window partition, i.e.
current_date() - Static method in class org.apache.spark.sql.functions
Returns the current date as a date column.
current_timestamp() - Static method in class org.apache.spark.sql.functions
Returns the current timestamp as a timestamp column.
currentAttemptId() - Method in interface org.apache.spark.SparkStageInfo
 
currentAttemptId() - Method in class org.apache.spark.SparkStageInfoImpl
 
currentDatabase() - Method in class org.apache.spark.sql.catalog.Catalog
Returns the current default database in this session.
currentResult() - Method in interface org.apache.spark.partial.ApproximateEvaluator
 
currentRow() - Static method in class org.apache.spark.sql.expressions.Window
Value representing the current row.
currentRow() - Static method in class org.apache.spark.sql.functions
Deprecated.
Use Window.currentRow. Since 2.4.0.
currPrefLocs(Partition, RDD<?>) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
 
customMetrics() - Method in class org.apache.spark.sql.streaming.StateOperatorProgress
 

D

DAGSchedulerEvent - Interface in org.apache.spark.scheduler
Types of events that can be handled by the DAGScheduler.
dapply(Dataset<Row>, byte[], byte[], Object[], StructType) - Static method in class org.apache.spark.sql.api.r.SQLUtils
The helper function for dapply() on R side.
Data(Vector, double, Option<Object>) - Constructor for class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$.Data
 
Data(double[], double[], double[][]) - Constructor for class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$.Data
 
Data(double[], double[], double[][], String) - Constructor for class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data
 
Data(int) - Constructor for class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$.Data
 
Data(Vector, double) - Constructor for class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$.Data
 
data() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.LaunchTask
 
data() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate
 
Data$() - Constructor for class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$.Data$
 
Data$() - Constructor for class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$.Data$
 
Data$() - Constructor for class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data$
 
Data$() - Constructor for class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$.Data$
 
Data$() - Constructor for class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$.Data$
 
Database - Class in org.apache.spark.sql.catalog
A database in Spark, as returned by the listDatabases method defined in Catalog.
Database(String, String, String) - Constructor for class org.apache.spark.sql.catalog.Database
 
database() - Method in class org.apache.spark.sql.catalog.Function
 
database() - Method in class org.apache.spark.sql.catalog.Table
 
DATABASE_KEY - Static variable in class org.apache.spark.sql.sources.v2.DataSourceOptions
The option key for database name.
databaseExists(String) - Method in class org.apache.spark.sql.catalog.Catalog
Check if the database with the specified name exists.
databaseExists(String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Return whether a table/view with the specified name exists.
databaseName() - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
Returns the value of the database name option.
databaseTypeDefinition() - Method in class org.apache.spark.sql.jdbc.JdbcType
 
dataDistribution() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
 
DATAFRAME_DAPPLY() - Static method in class org.apache.spark.api.r.RRunnerModes
 
DATAFRAME_GAPPLY() - Static method in class org.apache.spark.api.r.RRunnerModes
 
DataFrameNaFunctions - Class in org.apache.spark.sql
Functionality for working with missing data in DataFrames.
DataFrameReader - Class in org.apache.spark.sql
Interface used to load a Dataset from external storage systems (e.g.
DataFrameStatFunctions - Class in org.apache.spark.sql
Statistic functions for DataFrames.
DataFrameWriter<T> - Class in org.apache.spark.sql
Interface used to write a Dataset to external storage systems (e.g.
Dataset<T> - Class in org.apache.spark.sql
A Dataset is a strongly typed collection of domain-specific objects that can be transformed in parallel using functional or relational operations.
Dataset(SparkSession, LogicalPlan, Encoder<T>) - Constructor for class org.apache.spark.sql.Dataset
 
Dataset(SQLContext, LogicalPlan, Encoder<T>) - Constructor for class org.apache.spark.sql.Dataset
 
DatasetHolder<T> - Class in org.apache.spark.sql
A container for a Dataset, used for implicit conversions in Scala.
DatasetUtils - Class in org.apache.spark.ml.util
 
DatasetUtils() - Constructor for class org.apache.spark.ml.util.DatasetUtils
 
dataSource() - Method in interface org.apache.spark.ui.PagedTable
 
DataSourceOptions - Class in org.apache.spark.sql.sources.v2
An immutable string-to-string map in which keys are case-insensitive.
DataSourceOptions(Map<String, String>) - Constructor for class org.apache.spark.sql.sources.v2.DataSourceOptions
 
DataSourceReader - Interface in org.apache.spark.sql.sources.v2.reader
DataSourceRegister - Interface in org.apache.spark.sql.sources
Data sources should implement this trait so that they can register an alias to their data source.
DataSourceV2 - Interface in org.apache.spark.sql.sources.v2
The base interface for data source v2.
DataSourceWriter - Interface in org.apache.spark.sql.sources.v2.writer
DataStreamReader - Class in org.apache.spark.sql.streaming
Interface used to load a streaming Dataset from external storage systems (e.g.
DataStreamWriter<T> - Class in org.apache.spark.sql.streaming
Interface used to write a streaming Dataset to external storage systems (e.g.
dataTablesHeaderNodes(HttpServletRequest) - Static method in class org.apache.spark.ui.UIUtils
 
dataType() - Method in class org.apache.spark.sql.catalog.Column
 
dataType() - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
The DataType of the returned value of this UserDefinedAggregateFunction.
dataType() - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
 
DataType - Class in org.apache.spark.sql.types
The base type of all Spark SQL data types.
DataType() - Constructor for class org.apache.spark.sql.types.DataType
 
dataType() - Method in class org.apache.spark.sql.types.StructField
 
dataType() - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the data type of this column vector.
DataTypes - Class in org.apache.spark.sql.types
To get/create specific data type, users should use singleton objects and factory methods provided by this class.
DataTypes() - Constructor for class org.apache.spark.sql.types.DataTypes
 
DataValidators - Class in org.apache.spark.mllib.util
:: DeveloperApi :: A collection of methods used to validate data before applying ML algorithms.
DataValidators() - Constructor for class org.apache.spark.mllib.util.DataValidators
 
DataWriter<T> - Interface in org.apache.spark.sql.sources.v2.writer
A data writer returned by DataWriterFactory.createDataWriter(int, long, long) and is responsible for writing data for an input RDD partition.
DataWriterFactory<T> - Interface in org.apache.spark.sql.sources.v2.writer
A factory of DataWriter returned by DataSourceWriter.createWriterFactory(), which is responsible for creating and initializing the actual data writer at executor side.
date() - Method in class org.apache.spark.sql.ColumnName
Creates a new StructField of type date.
DATE() - Static method in class org.apache.spark.sql.Encoders
An encoder for nullable date type.
date_add(Column, int) - Static method in class org.apache.spark.sql.functions
Returns the date that is days days after start
date_format(Column, String) - Static method in class org.apache.spark.sql.functions
Converts a date/timestamp/string to a value of string in the format specified by the date format given by the second argument.
date_sub(Column, int) - Static method in class org.apache.spark.sql.functions
Returns the date that is days days before start
date_trunc(String, Column) - Static method in class org.apache.spark.sql.functions
Returns timestamp truncated to the unit specified by the format.
datediff(Column, Column) - Static method in class org.apache.spark.sql.functions
Returns the number of days from start to end.
DateType - Static variable in class org.apache.spark.sql.types.DataTypes
Gets the DateType object.
DateType - Class in org.apache.spark.sql.types
A date type, supporting "0001-01-01" through "9999-12-31".
DateType() - Constructor for class org.apache.spark.sql.types.DateType
 
dayofmonth(Column) - Static method in class org.apache.spark.sql.functions
Extracts the day of the month as an integer from a given date/timestamp/string.
dayofweek(Column) - Static method in class org.apache.spark.sql.functions
Extracts the day of the week as an integer from a given date/timestamp/string.
dayofyear(Column) - Static method in class org.apache.spark.sql.functions
Extracts the day of the year as an integer from a given date/timestamp/string.
DB2Dialect - Class in org.apache.spark.sql.jdbc
 
DB2Dialect() - Constructor for class org.apache.spark.sql.jdbc.DB2Dialect
 
DCT - Class in org.apache.spark.ml.feature
A feature transformer that takes the 1D discrete cosine transform of a real vector.
DCT(String) - Constructor for class org.apache.spark.ml.feature.DCT
 
DCT() - Constructor for class org.apache.spark.ml.feature.DCT
 
deallocate() - Method in class org.apache.spark.storage.ReadableChannelFileRegion
 
decayFactor() - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
 
decimal() - Method in class org.apache.spark.sql.ColumnName
Creates a new StructField of type decimal.
decimal(int, int) - Method in class org.apache.spark.sql.ColumnName
Creates a new StructField of type decimal.
DECIMAL() - Static method in class org.apache.spark.sql.Encoders
An encoder for nullable decimal type.
Decimal - Class in org.apache.spark.sql.types
A mutable implementation of BigDecimal that can hold a Long if values are small enough.
Decimal() - Constructor for class org.apache.spark.sql.types.Decimal
 
Decimal.DecimalAsIfIntegral$ - Class in org.apache.spark.sql.types
A Integral evidence parameter for Decimals.
Decimal.DecimalIsConflicted - Interface in org.apache.spark.sql.types
Common methods for Decimal evidence parameters
Decimal.DecimalIsFractional$ - Class in org.apache.spark.sql.types
A Fractional evidence parameter for Decimals.
DecimalAsIfIntegral$() - Constructor for class org.apache.spark.sql.types.Decimal.DecimalAsIfIntegral$
 
DecimalIsFractional$() - Constructor for class org.apache.spark.sql.types.Decimal.DecimalIsFractional$
 
DecimalType - Class in org.apache.spark.sql.types
The data type representing java.math.BigDecimal values.
DecimalType(int, int) - Constructor for class org.apache.spark.sql.types.DecimalType
 
DecimalType(int) - Constructor for class org.apache.spark.sql.types.DecimalType
 
DecimalType() - Constructor for class org.apache.spark.sql.types.DecimalType
 
DecimalType.Expression$ - Class in org.apache.spark.sql.types
 
DecimalType.Fixed$ - Class in org.apache.spark.sql.types
 
decimalTypeInfoToCatalyst(PrimitiveObjectInspector) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
DecisionTree - Class in org.apache.spark.mllib.tree
A class which implements a decision tree learning algorithm for classification and regression.
DecisionTree(Strategy) - Constructor for class org.apache.spark.mllib.tree.DecisionTree
 
DecisionTreeClassificationModel - Class in org.apache.spark.ml.classification
Decision tree model (http://en.wikipedia.org/wiki/Decision_tree_learning) for classification.
DecisionTreeClassifier - Class in org.apache.spark.ml.classification
Decision tree learning algorithm (http://en.wikipedia.org/wiki/Decision_tree_learning) for classification.
DecisionTreeClassifier(String) - Constructor for class org.apache.spark.ml.classification.DecisionTreeClassifier
 
DecisionTreeClassifier() - Constructor for class org.apache.spark.ml.classification.DecisionTreeClassifier
 
DecisionTreeClassifierParams - Interface in org.apache.spark.ml.tree
 
DecisionTreeModel - Interface in org.apache.spark.ml.tree
Abstraction for Decision Tree models.
DecisionTreeModel - Class in org.apache.spark.mllib.tree.model
Decision tree model for classification or regression.
DecisionTreeModel(Node, Enumeration.Value) - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel
 
DecisionTreeModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.tree.model
 
DecisionTreeModel.SaveLoadV1_0$.NodeData - Class in org.apache.spark.mllib.tree.model
Model data for model import/export
DecisionTreeModel.SaveLoadV1_0$.NodeData$ - Class in org.apache.spark.mllib.tree.model
 
DecisionTreeModel.SaveLoadV1_0$.PredictData - Class in org.apache.spark.mllib.tree.model
 
DecisionTreeModel.SaveLoadV1_0$.PredictData$ - Class in org.apache.spark.mllib.tree.model
 
DecisionTreeModel.SaveLoadV1_0$.SplitData - Class in org.apache.spark.mllib.tree.model
 
DecisionTreeModel.SaveLoadV1_0$.SplitData$ - Class in org.apache.spark.mllib.tree.model
 
DecisionTreeModelReadWrite - Class in org.apache.spark.ml.tree
Helper classes for tree model persistence
DecisionTreeModelReadWrite() - Constructor for class org.apache.spark.ml.tree.DecisionTreeModelReadWrite
 
DecisionTreeModelReadWrite.NodeData - Class in org.apache.spark.ml.tree
Info for a Node
DecisionTreeModelReadWrite.NodeData$ - Class in org.apache.spark.ml.tree
 
DecisionTreeModelReadWrite.SplitData - Class in org.apache.spark.ml.tree
Info for a Split
DecisionTreeModelReadWrite.SplitData$ - Class in org.apache.spark.ml.tree
 
DecisionTreeParams - Interface in org.apache.spark.ml.tree
Parameters for Decision Tree-based algorithms.
DecisionTreeRegressionModel - Class in org.apache.spark.ml.regression
Decision tree (Wikipedia) model for regression.
DecisionTreeRegressor - Class in org.apache.spark.ml.regression
Decision tree learning algorithm for regression.
DecisionTreeRegressor(String) - Constructor for class org.apache.spark.ml.regression.DecisionTreeRegressor
 
DecisionTreeRegressor() - Constructor for class org.apache.spark.ml.regression.DecisionTreeRegressor
 
DecisionTreeRegressorParams - Interface in org.apache.spark.ml.tree
 
decode(Column, String) - Static method in class org.apache.spark.sql.functions
Computes the first argument into a string from a binary using the provided character set (one of 'US-ASCII', 'ISO-8859-1', 'UTF-8', 'UTF-16BE', 'UTF-16LE', 'UTF-16').
decodeFileNameInURI(URI) - Static method in class org.apache.spark.util.Utils
Get the file name from uri's raw path and decode it.
decodeStructField(StructField, boolean) - Method in interface org.apache.spark.ml.attribute.AttributeFactory
Creates an Attribute from a StructField instance, optionally preserving name.
decodeURLParameter(String) - Static method in class org.apache.spark.ui.UIUtils
Decode URLParameter if URL is encoded by YARN-WebAppProxyServlet.
DEFAULT_CONNECTION_TIMEOUT() - Static method in class org.apache.spark.api.r.SparkRDefaults
 
DEFAULT_DRIVER_MEM_MB() - Static method in class org.apache.spark.util.Utils
Define a default value for driver memory here since this value is referenced across the code base and nearly all files already use Utils.scala
DEFAULT_HEARTBEAT_INTERVAL() - Static method in class org.apache.spark.api.r.SparkRDefaults
 
DEFAULT_MAX_FAILURES() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
DEFAULT_MAX_TO_STRING_FIELDS() - Static method in class org.apache.spark.util.Utils
The performance overhead of creating and logging strings for wide schemas can be large.
DEFAULT_NUM_RBACKEND_THREADS() - Static method in class org.apache.spark.api.r.SparkRDefaults
 
DEFAULT_NUMBER_EXECUTORS() - Static method in class org.apache.spark.scheduler.cluster.SchedulerBackendUtils
 
DEFAULT_ROLLING_INTERVAL_SECS() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
DEFAULT_SHUTDOWN_PRIORITY() - Static method in class org.apache.spark.util.ShutdownHookManager
 
defaultAttr() - Static method in class org.apache.spark.ml.attribute.BinaryAttribute
The default binary attribute.
defaultAttr() - Static method in class org.apache.spark.ml.attribute.NominalAttribute
The default nominal attribute.
defaultAttr() - Static method in class org.apache.spark.ml.attribute.NumericAttribute
The default numeric attribute.
defaultCopy(ParamMap) - Method in interface org.apache.spark.ml.param.Params
Default implementation of copy with extra params.
defaultCorrName() - Static method in class org.apache.spark.mllib.stat.correlation.CorrelationNames
 
DefaultCredentials - Class in org.apache.spark.streaming.kinesis
Returns DefaultAWSCredentialsProviderChain for authentication.
DefaultCredentials() - Constructor for class org.apache.spark.streaming.kinesis.DefaultCredentials
 
defaultLink() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
 
defaultLink() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
 
defaultLink() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
 
defaultLink() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
 
defaultMinPartitions() - Method in class org.apache.spark.api.java.JavaSparkContext
Default min number of partitions for Hadoop RDDs when not given by user
defaultMinPartitions() - Method in class org.apache.spark.SparkContext
Default min number of partitions for Hadoop RDDs when not given by user Notice that we use math.min so the "defaultMinPartitions" cannot be higher than 2.
defaultParallelism() - Method in class org.apache.spark.api.java.JavaSparkContext
Default level of parallelism to use when not given by user (e.g.
defaultParallelism() - Method in interface org.apache.spark.scheduler.SchedulerBackend
 
defaultParallelism() - Method in interface org.apache.spark.scheduler.TaskScheduler
 
defaultParallelism() - Method in class org.apache.spark.SparkContext
Default level of parallelism to use when not given by user (e.g.
defaultParamMap() - Method in interface org.apache.spark.ml.param.Params
Internal param map for default values.
defaultParams(String) - Static method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
Returns default configuration for the boosting algorithm
defaultParams(Enumeration.Value) - Static method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
Returns default configuration for the boosting algorithm
DefaultParamsReadable<T> - Interface in org.apache.spark.ml.util
:: DeveloperApi ::
DefaultParamsWritable - Interface in org.apache.spark.ml.util
:: DeveloperApi ::
DefaultPartitionCoalescer - Class in org.apache.spark.rdd
Coalesce the partitions of a parent RDD (prev) into fewer partitions, so that each partition of this RDD computes one or more of the parent ones.
DefaultPartitionCoalescer(double) - Constructor for class org.apache.spark.rdd.DefaultPartitionCoalescer
 
DefaultPartitionCoalescer.PartitionLocations - Class in org.apache.spark.rdd
 
defaultPartitioner(RDD<?>, Seq<RDD<?>>) - Static method in class org.apache.spark.Partitioner
Choose a partitioner to use for a cogroup-like operation between a number of RDDs.
defaultSize() - Method in class org.apache.spark.sql.types.ArrayType
The default size of a value of the ArrayType is the default size of the element type.
defaultSize() - Method in class org.apache.spark.sql.types.BinaryType
The default size of a value of the BinaryType is 100 bytes.
defaultSize() - Method in class org.apache.spark.sql.types.BooleanType
The default size of a value of the BooleanType is 1 byte.
defaultSize() - Method in class org.apache.spark.sql.types.ByteType
The default size of a value of the ByteType is 1 byte.
defaultSize() - Method in class org.apache.spark.sql.types.CalendarIntervalType
 
defaultSize() - Method in class org.apache.spark.sql.types.DataType
The default size of a value of this data type, used internally for size estimation.
defaultSize() - Method in class org.apache.spark.sql.types.DateType
The default size of a value of the DateType is 4 bytes.
defaultSize() - Method in class org.apache.spark.sql.types.DecimalType
The default size of a value of the DecimalType is 8 bytes when precision is at most 18, and 16 bytes otherwise.
defaultSize() - Method in class org.apache.spark.sql.types.DoubleType
The default size of a value of the DoubleType is 8 bytes.
defaultSize() - Method in class org.apache.spark.sql.types.FloatType
The default size of a value of the FloatType is 4 bytes.
defaultSize() - Method in class org.apache.spark.sql.types.HiveStringType
 
defaultSize() - Method in class org.apache.spark.sql.types.IntegerType
The default size of a value of the IntegerType is 4 bytes.
defaultSize() - Method in class org.apache.spark.sql.types.LongType
The default size of a value of the LongType is 8 bytes.
defaultSize() - Method in class org.apache.spark.sql.types.MapType
The default size of a value of the MapType is (the default size of the key type + the default size of the value type).
defaultSize() - Method in class org.apache.spark.sql.types.NullType
 
defaultSize() - Method in class org.apache.spark.sql.types.ObjectType
 
defaultSize() - Method in class org.apache.spark.sql.types.ShortType
The default size of a value of the ShortType is 2 bytes.
defaultSize() - Method in class org.apache.spark.sql.types.StringType
The default size of a value of the StringType is 20 bytes.
defaultSize() - Method in class org.apache.spark.sql.types.StructType
The default size of a value of the StructType is the total default sizes of all field types.
defaultSize() - Method in class org.apache.spark.sql.types.TimestampType
The default size of a value of the TimestampType is 8 bytes.
defaultStrategy(String) - Static method in class org.apache.spark.mllib.tree.configuration.Strategy
Construct a default set of parameters for DecisionTree
defaultStrategy(Enumeration.Value) - Static method in class org.apache.spark.mllib.tree.configuration.Strategy
Construct a default set of parameters for DecisionTree
DefaultTopologyMapper - Class in org.apache.spark.storage
A TopologyMapper that assumes all nodes are in the same rack
DefaultTopologyMapper(SparkConf) - Constructor for class org.apache.spark.storage.DefaultTopologyMapper
 
defaultValue() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefault
 
defaultValue() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefaultFunction
 
defaultValue() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefaultString
 
defaultValueString() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefault
 
defaultValueString() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefaultFunction
 
defaultValueString() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefaultString
 
degree() - Method in class org.apache.spark.ml.feature.PolynomialExpansion
The polynomial degree to expand, which should be greater than equal to 1.
degrees() - Method in class org.apache.spark.graphx.GraphOps
The degree of each vertex in the graph.
degrees(Column) - Static method in class org.apache.spark.sql.functions
Converts an angle measured in radians to an approximately equivalent angle measured in degrees.
degrees(String) - Static method in class org.apache.spark.sql.functions
Converts an angle measured in radians to an approximately equivalent angle measured in degrees.
degreesOfFreedom() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
Degrees of freedom.
degreesOfFreedom() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
Degrees of freedom
degreesOfFreedom() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
 
degreesOfFreedom() - Method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTestResult
 
degreesOfFreedom() - Method in interface org.apache.spark.mllib.stat.test.TestResult
Returns the degree(s) of freedom of the hypothesis test.
delegate() - Method in class org.apache.spark.InterruptibleIterator
 
deleteCheckpointFiles() - Method in class org.apache.spark.ml.clustering.DistributedLDAModel
:: DeveloperApi ::
deleteExternalTmpPath(Configuration) - Method in interface org.apache.spark.sql.hive.execution.SaveAsHiveFile
 
deleteRecursively(File) - Static method in class org.apache.spark.util.Utils
Delete a file or directory and its contents recursively.
deleteWithJob(FileSystem, Path, boolean) - Method in class org.apache.spark.internal.io.FileCommitProtocol
Specifies that a file should be deleted with the commit of this job.
delimiterOptions() - Static method in class org.apache.spark.sql.hive.execution.HiveOptions
 
delta() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Tweedie$
Constant used in initialization and deviance to avoid numerical issues.
dense(int, int, double[]) - Static method in class org.apache.spark.ml.linalg.Matrices
Creates a column-major dense matrix.
dense(double, double...) - Static method in class org.apache.spark.ml.linalg.Vectors
Creates a dense vector from its values.
dense(double, Seq<Object>) - Static method in class org.apache.spark.ml.linalg.Vectors
Creates a dense vector from its values.
dense(double[]) - Static method in class org.apache.spark.ml.linalg.Vectors
Creates a dense vector from a double array.
dense(int, int, double[]) - Static method in class org.apache.spark.mllib.linalg.Matrices
Creates a column-major dense matrix.
dense(double, double...) - Static method in class org.apache.spark.mllib.linalg.Vectors
Creates a dense vector from its values.
dense(double, Seq<Object>) - Static method in class org.apache.spark.mllib.linalg.Vectors
Creates a dense vector from its values.
dense(double[]) - Static method in class org.apache.spark.mllib.linalg.Vectors
Creates a dense vector from a double array.
dense_rank() - Static method in class org.apache.spark.sql.functions
Window function: returns the rank of rows within a window partition, without any gaps.
DenseMatrix - Class in org.apache.spark.ml.linalg
Column-major dense matrix.
DenseMatrix(int, int, double[], boolean) - Constructor for class org.apache.spark.ml.linalg.DenseMatrix
 
DenseMatrix(int, int, double[]) - Constructor for class org.apache.spark.ml.linalg.DenseMatrix
Column-major dense matrix.
DenseMatrix - Class in org.apache.spark.mllib.linalg
Column-major dense matrix.
DenseMatrix(int, int, double[], boolean) - Constructor for class org.apache.spark.mllib.linalg.DenseMatrix
 
DenseMatrix(int, int, double[]) - Constructor for class org.apache.spark.mllib.linalg.DenseMatrix
Column-major dense matrix.
DenseVector - Class in org.apache.spark.ml.linalg
A dense vector represented by a value array.
DenseVector(double[]) - Constructor for class org.apache.spark.ml.linalg.DenseVector
 
DenseVector - Class in org.apache.spark.mllib.linalg
A dense vector represented by a value array.
DenseVector(double[]) - Constructor for class org.apache.spark.mllib.linalg.DenseVector
 
dependencies() - Method in class org.apache.spark.rdd.RDD
Get the list of dependencies of this RDD, taking into account whether the RDD is checkpointed or not.
dependencies() - Method in class org.apache.spark.streaming.dstream.DStream
List of parent DStreams on which this DStream depends on
dependencies() - Method in class org.apache.spark.streaming.dstream.InputDStream
 
Dependency<T> - Class in org.apache.spark
:: DeveloperApi :: Base class for dependencies.
Dependency() - Constructor for class org.apache.spark.Dependency
 
DEPLOY_MODE - Static variable in class org.apache.spark.launcher.SparkLauncher
The Spark deploy mode.
deployMode() - Method in class org.apache.spark.SparkContext
 
depth() - Method in interface org.apache.spark.ml.tree.DecisionTreeModel
Depth of the tree.
depth() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
Get depth of tree.
depth() - Method in class org.apache.spark.util.sketch.CountMinSketch
Depth of this CountMinSketch.
DerbyDialect - Class in org.apache.spark.sql.jdbc
 
DerbyDialect() - Constructor for class org.apache.spark.sql.jdbc.DerbyDialect
 
deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.CLogLog$
 
deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Identity$
 
deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Inverse$
 
deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Log$
 
deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Logit$
 
deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Probit$
 
deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Sqrt$
 
derivative() - Method in interface org.apache.spark.ml.ann.ActivationFunction
Implements a derivative of a function (needed for the back propagation)
desc() - Method in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
 
desc() - Method in class org.apache.spark.sql.Column
Returns a sort expression based on the descending order of the column.
desc(String) - Static method in class org.apache.spark.sql.functions
Returns a sort expression based on the descending order of the column.
desc() - Method in class org.apache.spark.util.MethodIdentifier
 
desc_nulls_first() - Method in class org.apache.spark.sql.Column
Returns a sort expression based on the descending order of the column, and null values appear before non-null values.
desc_nulls_first(String) - Static method in class org.apache.spark.sql.functions
Returns a sort expression based on the descending order of the column, and null values appear before non-null values.
desc_nulls_last() - Method in class org.apache.spark.sql.Column
Returns a sort expression based on the descending order of the column, and null values appear after non-null values.
desc_nulls_last(String) - Static method in class org.apache.spark.sql.functions
Returns a sort expression based on the descending order of the column, and null values appear after non-null values.
describe(String...) - Method in class org.apache.spark.sql.Dataset
Computes basic statistics for numeric and string columns, including count, mean, stddev, min, and max.
describe(Seq<String>) - Method in class org.apache.spark.sql.Dataset
Computes basic statistics for numeric and string columns, including count, mean, stddev, min, and max.
describeTopics(int) - Method in class org.apache.spark.ml.clustering.LDAModel
Return the topics described by their top-weighted terms.
describeTopics() - Method in class org.apache.spark.ml.clustering.LDAModel
 
describeTopics(int) - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
 
describeTopics(int) - Method in class org.apache.spark.mllib.clustering.LDAModel
Return the topics described by weighted terms.
describeTopics() - Method in class org.apache.spark.mllib.clustering.LDAModel
Return the topics described by weighted terms.
describeTopics(int) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
 
description() - Method in class org.apache.spark.ExceptionFailure
 
description() - Method in class org.apache.spark.sql.catalog.Column
 
description() - Method in class org.apache.spark.sql.catalog.Database
 
description() - Method in class org.apache.spark.sql.catalog.Function
 
description() - Method in class org.apache.spark.sql.catalog.Table
 
description() - Method in class org.apache.spark.sql.streaming.SinkProgress
 
description() - Method in class org.apache.spark.sql.streaming.SourceProgress
 
description() - Method in class org.apache.spark.status.api.v1.JobData
 
description() - Method in class org.apache.spark.status.api.v1.StageData
 
description() - Method in class org.apache.spark.status.api.v1.streaming.OutputOperationInfo
 
description() - Method in class org.apache.spark.status.LiveStage
 
description() - Method in class org.apache.spark.storage.StorageLevel
 
description() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
 
DESER_CPU_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
 
DESER_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
 
DeserializationStream - Class in org.apache.spark.serializer
:: DeveloperApi :: A stream for reading serialized objects.
DeserializationStream() - Constructor for class org.apache.spark.serializer.DeserializationStream
 
deserialize(Object) - Method in class org.apache.spark.mllib.linalg.VectorUDT
 
deserialize(ByteBuffer, ClassLoader, ClassTag<T>) - Method in class org.apache.spark.serializer.DummySerializerInstance
 
deserialize(ByteBuffer, ClassTag<T>) - Method in class org.apache.spark.serializer.DummySerializerInstance
 
deserialize(ByteBuffer, ClassTag<T>) - Method in class org.apache.spark.serializer.SerializerInstance
 
deserialize(ByteBuffer, ClassLoader, ClassTag<T>) - Method in class org.apache.spark.serializer.SerializerInstance
 
deserialize(byte[]) - Static method in class org.apache.spark.util.Utils
Deserialize an object using Java serialization
deserialize(byte[], ClassLoader) - Static method in class org.apache.spark.util.Utils
Deserialize an object using Java serialization and the given ClassLoader
deserialized() - Method in class org.apache.spark.storage.StorageLevel
 
DeserializedMemoryEntry<T> - Class in org.apache.spark.storage.memory
 
DeserializedMemoryEntry(Object, long, ClassTag<T>) - Constructor for class org.apache.spark.storage.memory.DeserializedMemoryEntry
 
DeserializedValuesHolder<T> - Class in org.apache.spark.storage.memory
A holder for storing the deserialized values.
DeserializedValuesHolder(ClassTag<T>) - Constructor for class org.apache.spark.storage.memory.DeserializedValuesHolder
 
deserializeLongValue(byte[]) - Static method in class org.apache.spark.util.Utils
Deserialize a Long value (used for PythonPartitioner)
deserializeOffset(String) - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.ContinuousReader
Deserialize a JSON string into an Offset of the implementation-defined offset type.
deserializeOffset(String) - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.MicroBatchReader
Deserialize a JSON string into an Offset of the implementation-defined offset type.
DeserializerLock - Class in org.apache.spark.sql.hive
Object to synchronize on when calling org.apache.hadoop.hive.serde2.Deserializer#initialize.
DeserializerLock() - Constructor for class org.apache.spark.sql.hive.DeserializerLock
 
deserializeStream(InputStream) - Method in class org.apache.spark.serializer.DummySerializerInstance
 
deserializeStream(InputStream) - Method in class org.apache.spark.serializer.SerializerInstance
 
deserializeViaNestedStream(InputStream, SerializerInstance, Function1<DeserializationStream, BoxedUnit>) - Static method in class org.apache.spark.util.Utils
Deserialize via nested stream using specific serializer
destroy() - Method in class org.apache.spark.broadcast.Broadcast
Destroy all data and metadata related to this broadcast variable.
details() - Method in class org.apache.spark.scheduler.StageInfo
 
details() - Method in class org.apache.spark.status.api.v1.StageData
 
DETERMINATE() - Static method in class org.apache.spark.rdd.DeterministicLevel
 
determineBounds(ArrayBuffer<Tuple2<K, Object>>, int, Ordering<K>, ClassTag<K>) - Static method in class org.apache.spark.RangePartitioner
Determines the bounds for range partitioning from candidates with weights indicating how many items each represents.
DetermineTableStats - Class in org.apache.spark.sql.hive
 
DetermineTableStats(SparkSession) - Constructor for class org.apache.spark.sql.hive.DetermineTableStats
 
deterministic() - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
Returns true iff this function is deterministic, i.e.
deterministic() - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
Returns true iff the UDF is deterministic, i.e.
DeterministicLevel - Class in org.apache.spark.rdd
The deterministic level of RDD's output (i.e.
DeterministicLevel() - Constructor for class org.apache.spark.rdd.DeterministicLevel
 
deviance(double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
 
deviance(double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
 
deviance(double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
 
deviance(double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
 
deviance() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
The deviance for the fitted model.
devianceResiduals() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
The weighted residuals, the usual residuals rescaled by the square root of the instance weights.
dfToCols(Dataset<Row>) - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
dfToRowRDD(Dataset<Row>) - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
dgemm(double, DenseMatrix<Object>, DenseMatrix<Object>, double, DenseMatrix<Object>) - Static method in class org.apache.spark.ml.ann.BreezeUtil
DGEMM: C := alpha * A * B + beta * C
dgemv(double, DenseMatrix<Object>, DenseVector<Object>, double, DenseVector<Object>) - Static method in class org.apache.spark.ml.ann.BreezeUtil
DGEMV: y := alpha * A * x + beta * y
diag(Vector) - Static method in class org.apache.spark.ml.linalg.DenseMatrix
Generate a diagonal matrix in DenseMatrix format from the supplied values.
diag(Vector) - Static method in class org.apache.spark.ml.linalg.Matrices
Generate a diagonal matrix in Matrix format from the supplied values.
diag(Vector) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
Generate a diagonal matrix in DenseMatrix format from the supplied values.
diag(Vector) - Static method in class org.apache.spark.mllib.linalg.Matrices
Generate a diagonal matrix in Matrix format from the supplied values.
diff(RDD<Tuple2<Object, VD>>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
diff(VertexRDD<VD>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
diff(RDD<Tuple2<Object, VD>>) - Method in class org.apache.spark.graphx.VertexRDD
For each vertex present in both this and other, diff returns only those vertices with differing values; for values that are different, keeps the values from other.
diff(VertexRDD<VD>) - Method in class org.apache.spark.graphx.VertexRDD
For each vertex present in both this and other, diff returns only those vertices with differing values; for values that are different, keeps the values from other.
DifferentiableLossAggregator<Datum,Agg extends DifferentiableLossAggregator<Datum,Agg>> - Interface in org.apache.spark.ml.optim.aggregator
A parent trait for aggregators used in fitting MLlib models.
DifferentiableRegularization<T> - Interface in org.apache.spark.ml.optim.loss
A Breeze diff function which represents a cost function for differentiable regularization of parameters.
dim() - Method in interface org.apache.spark.ml.optim.aggregator.DifferentiableLossAggregator
The dimension of the gradient array.
dir() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
 
directory(File) - Method in class org.apache.spark.launcher.SparkLauncher
Sets the working directory of spark-submit.
disableOutputSpecValidation() - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
Allows for the spark.hadoop.validateOutputSpecs checks to be disabled on a case-by-case basis; see SPARK-4835 for more details.
disconnect() - Method in interface org.apache.spark.launcher.SparkAppHandle
Disconnects the handle from the application, without stopping it.
DISK_BYTES_SPILLED() - Static method in class org.apache.spark.InternalAccumulator
 
DISK_ONLY - Static variable in class org.apache.spark.api.java.StorageLevels
 
DISK_ONLY() - Static method in class org.apache.spark.storage.StorageLevel
 
DISK_ONLY_2 - Static variable in class org.apache.spark.api.java.StorageLevels
 
DISK_ONLY_2() - Static method in class org.apache.spark.storage.StorageLevel
 
DISK_SPILL() - Static method in class org.apache.spark.status.TaskIndexNames
 
DiskBlockData - Class in org.apache.spark.storage
 
DiskBlockData(long, long, File, long) - Constructor for class org.apache.spark.storage.DiskBlockData
 
diskBytesSpilled() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
diskBytesSpilled() - Method in class org.apache.spark.status.api.v1.StageData
 
diskBytesSpilled() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
diskBytesSpilled() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 
diskSize() - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
 
diskSize() - Method in class org.apache.spark.storage.BlockStatus
 
diskSize() - Method in class org.apache.spark.storage.BlockUpdatedInfo
 
diskSize() - Method in class org.apache.spark.storage.RDDInfo
 
diskUsed() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
diskUsed() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
 
diskUsed() - Method in class org.apache.spark.status.api.v1.RDDPartitionInfo
 
diskUsed() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
 
diskUsed() - Method in class org.apache.spark.status.LiveExecutor
 
diskUsed() - Method in class org.apache.spark.status.LiveRDD
 
diskUsed() - Method in class org.apache.spark.status.LiveRDDDistribution
 
diskUsed() - Method in class org.apache.spark.status.LiveRDDPartition
 
dispersion() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
The dispersion of the fitted model.
dispose() - Method in interface org.apache.spark.storage.BlockData
 
dispose() - Method in class org.apache.spark.storage.DiskBlockData
 
dispose(ByteBuffer) - Static method in class org.apache.spark.storage.StorageUtils
Attempt to clean up a ByteBuffer if it is direct or memory-mapped.
distanceMeasure() - Method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
param for distance measure to be used in evaluation (supports "squaredEuclidean" (default), "cosine")
distanceMeasure() - Method in interface org.apache.spark.ml.param.shared.HasDistanceMeasure
Param for The distance measure.
distanceMeasure() - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
 
distanceMeasure() - Method in class org.apache.spark.mllib.clustering.KMeansModel
 
distinct() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return a new RDD containing the distinct elements in this RDD.
distinct(int) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return a new RDD containing the distinct elements in this RDD.
distinct() - Method in class org.apache.spark.api.java.JavaPairRDD
Return a new RDD containing the distinct elements in this RDD.
distinct(int) - Method in class org.apache.spark.api.java.JavaPairRDD
Return a new RDD containing the distinct elements in this RDD.
distinct() - Method in class org.apache.spark.api.java.JavaRDD
Return a new RDD containing the distinct elements in this RDD.
distinct(int) - Method in class org.apache.spark.api.java.JavaRDD
Return a new RDD containing the distinct elements in this RDD.
distinct(int, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
Return a new RDD containing the distinct elements in this RDD.
distinct() - Method in class org.apache.spark.rdd.RDD
Return a new RDD containing the distinct elements in this RDD.
distinct() - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset that contains only the unique rows from this Dataset.
distinct(Column...) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
Creates a Column for this UDAF using the distinct values of the given Columns as input arguments.
distinct(Seq<Column>) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
Creates a Column for this UDAF using the distinct values of the given Columns as input arguments.
DistributedLDAModel - Class in org.apache.spark.ml.clustering
Distributed model fitted by LDA.
DistributedLDAModel - Class in org.apache.spark.mllib.clustering
Distributed LDA model.
DistributedMatrix - Interface in org.apache.spark.mllib.linalg.distributed
Represents a distributively stored matrix backed by one or more RDDs.
Distribution - Interface in org.apache.spark.sql.sources.v2.reader.partitioning
An interface to represent data distribution requirement, which specifies how the records should be distributed among the data partitions (one InputPartitionReader outputs data for one partition).
distribution(LiveExecutor) - Method in class org.apache.spark.status.LiveRDD
 
distributionOpt(LiveExecutor) - Method in class org.apache.spark.status.LiveRDD
 
div(Decimal, Decimal) - Method in class org.apache.spark.sql.types.Decimal.DecimalIsFractional$
 
div(Duration) - Method in class org.apache.spark.streaming.Duration
 
divide(Object) - Method in class org.apache.spark.sql.Column
Division this expression by another expression.
doc() - Method in class org.apache.spark.ml.param.Param
 
docConcentration() - Method in interface org.apache.spark.ml.clustering.LDAParams
Concentration parameter (commonly named "alpha") for the prior placed on documents' distributions over topics ("theta").
docConcentration() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
 
docConcentration() - Method in class org.apache.spark.mllib.clustering.LDAModel
Concentration parameter (commonly named "alpha") for the prior placed on documents' distributions over topics ("theta").
docConcentration() - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
 
DocumentFrequencyAggregator(int) - Constructor for class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
 
DocumentFrequencyAggregator() - Constructor for class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
 
doesDirectoryContainAnyNewFiles(File, long) - Static method in class org.apache.spark.util.Utils
Determines if a directory contains any files newer than cutoff seconds.
doFetchFile(String, File, String, SparkConf, org.apache.spark.SecurityManager, Configuration) - Static method in class org.apache.spark.util.Utils
Download a file or directory to target directory.
doPostEvent(SparkListenerInterface, SparkListenerEvent) - Method in interface org.apache.spark.scheduler.SparkListenerBus
 
doPostEvent(L, E) - Method in interface org.apache.spark.util.ListenerBus
Post an event to the specified listener.
Dot - Class in org.apache.spark.ml.feature
 
Dot() - Constructor for class org.apache.spark.ml.feature.Dot
 
dot(Vector, Vector) - Static method in class org.apache.spark.ml.linalg.BLAS
dot(x, y)
dot(Vector, Vector) - Static method in class org.apache.spark.mllib.linalg.BLAS
dot(x, y)
doTest(DStream<Tuple2<StatCounter, StatCounter>>) - Method in interface org.apache.spark.mllib.stat.test.StreamingTestMethod
Perform streaming 2-sample statistical significance testing.
doTest(DStream<Tuple2<StatCounter, StatCounter>>) - Static method in class org.apache.spark.mllib.stat.test.StudentTTest
 
doTest(DStream<Tuple2<StatCounter, StatCounter>>) - Static method in class org.apache.spark.mllib.stat.test.WelchTTest
 
DOUBLE() - Static method in class org.apache.spark.sql.Encoders
An encoder for nullable double type.
doubleAccumulator(double) - Method in class org.apache.spark.api.java.JavaSparkContext
Deprecated.
use sc().doubleAccumulator(). Since 2.0.0.
doubleAccumulator(double, String) - Method in class org.apache.spark.api.java.JavaSparkContext
Deprecated.
use sc().doubleAccumulator(String). Since 2.0.0.
doubleAccumulator() - Method in class org.apache.spark.SparkContext
Create and register a double accumulator, which starts with 0 and accumulates inputs by add.
doubleAccumulator(String) - Method in class org.apache.spark.SparkContext
Create and register a double accumulator, which starts with 0 and accumulates inputs by add.
DoubleAccumulator - Class in org.apache.spark.util
An accumulator for computing sum, count, and averages for double precision floating numbers.
DoubleAccumulator() - Constructor for class org.apache.spark.util.DoubleAccumulator
 
DoubleAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.DoubleAccumulatorParam$
Deprecated.
 
DoubleArrayArrayParam - Class in org.apache.spark.ml.param
:: DeveloperApi :: Specialized version of Param[Array[Array[Double}] for Java.
DoubleArrayArrayParam(Params, String, String, Function1<double[][], Object>) - Constructor for class org.apache.spark.ml.param.DoubleArrayArrayParam
 
DoubleArrayArrayParam(Params, String, String) - Constructor for class org.apache.spark.ml.param.DoubleArrayArrayParam
 
DoubleArrayParam - Class in org.apache.spark.ml.param
:: DeveloperApi :: Specialized version of Param[Array[Double} for Java.
DoubleArrayParam(Params, String, String, Function1<double[], Object>) - Constructor for class org.apache.spark.ml.param.DoubleArrayParam
 
DoubleArrayParam(Params, String, String) - Constructor for class org.apache.spark.ml.param.DoubleArrayParam
 
DoubleFlatMapFunction<T> - Interface in org.apache.spark.api.java.function
A function that returns zero or more records of type Double from each input record.
DoubleFunction<T> - Interface in org.apache.spark.api.java.function
A function that returns Doubles, and can be used to construct DoubleRDDs.
DoubleParam - Class in org.apache.spark.ml.param
:: DeveloperApi :: Specialized version of Param[Double] for Java.
DoubleParam(String, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.DoubleParam
 
DoubleParam(String, String, String) - Constructor for class org.apache.spark.ml.param.DoubleParam
 
DoubleParam(Identifiable, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.DoubleParam
 
DoubleParam(Identifiable, String, String) - Constructor for class org.apache.spark.ml.param.DoubleParam
 
DoubleRDDFunctions - Class in org.apache.spark.rdd
Extra functions available on RDDs of Doubles through an implicit conversion.
DoubleRDDFunctions(RDD<Object>) - Constructor for class org.apache.spark.rdd.DoubleRDDFunctions
 
doubleRDDToDoubleRDDFunctions(RDD<Object>) - Static method in class org.apache.spark.rdd.RDD
 
DoubleType - Static variable in class org.apache.spark.sql.types.DataTypes
Gets the DoubleType object.
DoubleType - Class in org.apache.spark.sql.types
The data type representing Double values.
DoubleType() - Constructor for class org.apache.spark.sql.types.DoubleType
 
driver() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SetupDriver
 
DRIVER_EXTRA_CLASSPATH - Static variable in class org.apache.spark.launcher.SparkLauncher
Configuration key for the driver class path.
DRIVER_EXTRA_JAVA_OPTIONS - Static variable in class org.apache.spark.launcher.SparkLauncher
Configuration key for the driver VM options.
DRIVER_EXTRA_LIBRARY_PATH - Static variable in class org.apache.spark.launcher.SparkLauncher
Configuration key for the driver native library path.
DRIVER_MEMORY - Static variable in class org.apache.spark.launcher.SparkLauncher
Configuration key for the driver memory.
DRIVER_WAL_BATCHING_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
DRIVER_WAL_BATCHING_TIMEOUT_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
DRIVER_WAL_CLASS_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
DRIVER_WAL_CLOSE_AFTER_WRITE_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
DRIVER_WAL_MAX_FAILURES_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
DRIVER_WAL_ROLLING_INTERVAL_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
driverLogs() - Method in class org.apache.spark.scheduler.SparkListenerApplicationStart
 
drop() - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that drops rows containing any null or NaN values.
drop(String) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that drops rows containing null or NaN values.
drop(String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that drops rows containing any null or NaN values in the specified columns.
drop(Seq<String>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
(Scala-specific) Returns a new DataFrame that drops rows containing any null or NaN values in the specified columns.
drop(String, String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that drops rows containing null or NaN values in the specified columns.
drop(String, Seq<String>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
(Scala-specific) Returns a new DataFrame that drops rows containing null or NaN values in the specified columns.
drop(int) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that drops rows containing less than minNonNulls non-null and non-NaN values.
drop(int, String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that drops rows containing less than minNonNulls non-null and non-NaN values in the specified columns.
drop(int, Seq<String>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
(Scala-specific) Returns a new DataFrame that drops rows containing less than minNonNulls non-null and non-NaN values in the specified columns.
drop(String...) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with columns dropped.
drop(String) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with a column dropped.
drop(Seq<String>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with columns dropped.
drop(Column) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with a column dropped.
dropDatabase(String, boolean, boolean) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Drop the specified database, if it exists.
dropDuplicates(String, String...) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with duplicate rows removed, considering only the subset of columns.
dropDuplicates() - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset that contains only the unique rows from this Dataset.
dropDuplicates(Seq<String>) - Method in class org.apache.spark.sql.Dataset
(Scala-specific) Returns a new Dataset with duplicate rows removed, considering only the subset of columns.
dropDuplicates(String[]) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with duplicate rows removed, considering only the subset of columns.
dropDuplicates(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with duplicate rows removed, considering only the subset of columns.
dropFromMemory(BlockId, Function0<Either<Object, org.apache.spark.util.io.ChunkedByteBuffer>>, ClassTag<T>) - Method in interface org.apache.spark.storage.memory.BlockEvictionHandler
Drop a block from memory, possibly putting it on disk if applicable.
dropFunction(String, String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Drop an existing function in the database.
dropGlobalTempView(String) - Method in class org.apache.spark.sql.catalog.Catalog
Drops the global temporary view with the given view name in the catalog.
dropLast() - Method in class org.apache.spark.ml.feature.OneHotEncoder
Deprecated.
Whether to drop the last category in the encoded vector (default: true)
dropLast() - Method in interface org.apache.spark.ml.feature.OneHotEncoderBase
Whether to drop the last category in the encoded vector (default: true)
dropPartitions(String, String, Seq<Map<String, String>>, boolean, boolean, boolean) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Drop one or many partitions in the given table, assuming they exist.
dropTable(String, String, boolean, boolean) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Drop the specified table.
dropTempTable(String) - Method in class org.apache.spark.sql.SQLContext
 
dropTempView(String) - Method in class org.apache.spark.sql.catalog.Catalog
Drops the local temporary view with the given view name in the catalog.
dspmv(int, double, DenseVector, DenseVector, double, DenseVector) - Static method in class org.apache.spark.ml.linalg.BLAS
y := alpha*A*x + beta*y
Dst - Static variable in class org.apache.spark.graphx.TripletFields
Expose the destination and edge fields but not the source field.
dstAttr() - Method in class org.apache.spark.graphx.EdgeContext
The vertex attribute of the edge's destination vertex.
dstAttr() - Method in class org.apache.spark.graphx.EdgeTriplet
The destination vertex attribute
dstAttr() - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
 
dstCol() - Method in interface org.apache.spark.ml.clustering.PowerIterationClusteringParams
Name of the input column for destination vertex IDs.
dstId() - Method in class org.apache.spark.graphx.Edge
 
dstId() - Method in class org.apache.spark.graphx.EdgeContext
The vertex id of the edge's destination vertex.
dstId() - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
 
dstream() - Method in class org.apache.spark.streaming.api.java.JavaDStream
 
dstream() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
 
dstream() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
 
DStream<T> - Class in org.apache.spark.streaming.dstream
A Discretized Stream (DStream), the basic abstraction in Spark Streaming, is a continuous sequence of RDDs (of the same type) representing a continuous stream of data (see org.apache.spark.rdd.RDD in the Spark core documentation for more details on RDDs).
DStream(StreamingContext, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.DStream
 
dtypes() - Method in class org.apache.spark.sql.Dataset
Returns all column names and their data types as an array.
DummySerializerInstance - Class in org.apache.spark.serializer
Unfortunately, we need a serializer instance in order to construct a DiskBlockObjectWriter.
duration() - Method in class org.apache.spark.scheduler.TaskInfo
 
duration() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
 
duration() - Method in class org.apache.spark.status.api.v1.streaming.OutputOperationInfo
 
duration() - Method in class org.apache.spark.status.api.v1.TaskData
 
DURATION() - Static method in class org.apache.spark.status.TaskIndexNames
 
Duration - Class in org.apache.spark.streaming
 
Duration(long) - Constructor for class org.apache.spark.streaming.Duration
 
duration() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
Return the duration of this output operation.
durationMs() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
 
Durations - Class in org.apache.spark.streaming
 
Durations() - Constructor for class org.apache.spark.streaming.Durations
 

E

Edge<ED> - Class in org.apache.spark.graphx
A single directed edge consisting of a source id, target id, and the data associated with the edge.
Edge(long, long, ED) - Constructor for class org.apache.spark.graphx.Edge
 
EdgeActiveness - Enum in org.apache.spark.graphx.impl
Criteria for filtering edges based on activeness.
EdgeContext<VD,ED,A> - Class in org.apache.spark.graphx
Represents an edge along with its neighboring vertices and allows sending messages along the edge.
EdgeContext() - Constructor for class org.apache.spark.graphx.EdgeContext
 
EdgeDirection - Class in org.apache.spark.graphx
The direction of a directed edge relative to a vertex.
EdgeDirection() - Constructor for class org.apache.spark.graphx.EdgeDirection
 
edgeListFile(SparkContext, String, boolean, int, StorageLevel, StorageLevel) - Static method in class org.apache.spark.graphx.GraphLoader
Loads a graph from an edge list formatted file where each line contains two integers: a source id and a target id.
EdgeOnly - Static variable in class org.apache.spark.graphx.TripletFields
Expose only the edge field and not the source or destination field.
EdgePartition1D$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.EdgePartition1D$
 
EdgePartition2D$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.EdgePartition2D$
 
EdgeRDD<ED> - Class in org.apache.spark.graphx
EdgeRDD[ED, VD] extends RDD[Edge[ED} by storing the edges in columnar format on each partition for performance.
EdgeRDD(SparkContext, Seq<Dependency<?>>) - Constructor for class org.apache.spark.graphx.EdgeRDD
 
EdgeRDDImpl<ED,VD> - Class in org.apache.spark.graphx.impl
 
edges() - Method in class org.apache.spark.graphx.Graph
An RDD containing the edges and their associated attributes.
edges() - Method in class org.apache.spark.graphx.impl.GraphImpl
 
EdgeTriplet<VD,ED> - Class in org.apache.spark.graphx
An edge triplet represents an edge along with the vertex attributes of its neighboring vertices.
EdgeTriplet() - Constructor for class org.apache.spark.graphx.EdgeTriplet
 
EigenValueDecomposition - Class in org.apache.spark.mllib.linalg
Compute eigen-decomposition.
EigenValueDecomposition() - Constructor for class org.apache.spark.mllib.linalg.EigenValueDecomposition
 
Either() - Static method in class org.apache.spark.graphx.EdgeDirection
Edges originating from *or* arriving at a vertex of interest.
elasticNetParam() - Method in interface org.apache.spark.ml.param.shared.HasElasticNetParam
Param for the ElasticNet mixing parameter, in range [0, 1].
elem(String, Function1<Object, Object>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
elem(Parsers) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
element_at(Column, Object) - Static method in class org.apache.spark.sql.functions
Returns element of array at given index in value if column is array.
elementType() - Method in class org.apache.spark.sql.types.ArrayType
 
ElementwiseProduct - Class in org.apache.spark.ml.feature
Outputs the Hadamard product (i.e., the element-wise product) of each input vector with a provided "weight" vector.
ElementwiseProduct(String) - Constructor for class org.apache.spark.ml.feature.ElementwiseProduct
 
ElementwiseProduct() - Constructor for class org.apache.spark.ml.feature.ElementwiseProduct
 
ElementwiseProduct - Class in org.apache.spark.mllib.feature
Outputs the Hadamard product (i.e., the element-wise product) of each input vector with a provided "weight" vector.
ElementwiseProduct(Vector) - Constructor for class org.apache.spark.mllib.feature.ElementwiseProduct
 
elems() - Method in class org.apache.spark.status.api.v1.StackTrace
 
EMLDAOptimizer - Class in org.apache.spark.mllib.clustering
:: DeveloperApi ::
EMLDAOptimizer() - Constructor for class org.apache.spark.mllib.clustering.EMLDAOptimizer
 
empty() - Static method in class org.apache.spark.api.java.Optional
 
empty() - Static method in class org.apache.spark.ml.param.ParamMap
Returns an empty param map.
empty() - Method in class org.apache.spark.mllib.fpm.PrefixSpan.Prefix$
An empty Prefix instance.
empty() - Static method in class org.apache.spark.sql.sources.v2.DataSourceOptions
 
empty() - Static method in class org.apache.spark.sql.types.Metadata
Returns an empty Metadata.
empty() - Static method in class org.apache.spark.storage.BlockStatus
 
EMPTY_USER_GROUPS() - Static method in class org.apache.spark.util.Utils
 
emptyDataFrame() - Method in class org.apache.spark.sql.SparkSession
Returns a DataFrame with no rows or columns.
emptyDataFrame() - Method in class org.apache.spark.sql.SQLContext
Returns a DataFrame with no rows or columns.
emptyDataset(Encoder<T>) - Method in class org.apache.spark.sql.SparkSession
:: Experimental :: Creates a new Dataset of type T containing zero elements.
emptyNode(int) - Static method in class org.apache.spark.mllib.tree.model.Node
Return a node with the given node id (but nothing else set).
emptyRDD() - Method in class org.apache.spark.api.java.JavaSparkContext
Get an RDD that has no partitions or elements.
emptyRDD(ClassTag<T>) - Method in class org.apache.spark.SparkContext
Get an RDD that has no partitions or elements.
EmptyTaskCommitMessage$() - Constructor for class org.apache.spark.internal.io.FileCommitProtocol.EmptyTaskCommitMessage$
 
enableBatchRead() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsScanColumnarBatch
Returns true if the concrete data source reader can read data in batch according to the scan properties like required columns, pushes filters, etc.
enableHiveSupport() - Method in class org.apache.spark.sql.SparkSession.Builder
Enables Hive support, including connectivity to a persistent Hive metastore, support for Hive serdes, and Hive user-defined functions.
enableReceiverLog(SparkConf) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
encode(Column, String) - Static method in class org.apache.spark.sql.functions
Computes the first argument into a binary from a string using the provided character set (one of 'US-ASCII', 'ISO-8859-1', 'UTF-8', 'UTF-16BE', 'UTF-16LE', 'UTF-16').
encodeFileNameToURIRawPath(String) - Static method in class org.apache.spark.util.Utils
A file name may contain some invalid URI characters, such as " ".
Encoder<T> - Interface in org.apache.spark.sql
:: Experimental :: Used to convert a JVM object of type T to and from the internal Spark SQL representation.
Encoders - Class in org.apache.spark.sql
:: Experimental :: Methods for creating an Encoder.
Encoders() - Constructor for class org.apache.spark.sql.Encoders
 
endOffset() - Method in class org.apache.spark.sql.streaming.SourceProgress
 
endOffset() - Method in exception org.apache.spark.sql.streaming.StreamingQueryException
 
endsWith(Column) - Method in class org.apache.spark.sql.Column
String ends with.
endsWith(String) - Method in class org.apache.spark.sql.Column
String ends with another string literal.
endTime() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
 
endTime() - Method in class org.apache.spark.status.api.v1.streaming.OutputOperationInfo
 
endTime() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
 
EnsembleCombiningStrategy - Class in org.apache.spark.mllib.tree.configuration
Enum to select ensemble combining strategy for base learners
EnsembleCombiningStrategy() - Constructor for class org.apache.spark.mllib.tree.configuration.EnsembleCombiningStrategy
 
EnsembleModelReadWrite - Class in org.apache.spark.ml.tree
 
EnsembleModelReadWrite() - Constructor for class org.apache.spark.ml.tree.EnsembleModelReadWrite
 
EnsembleModelReadWrite.EnsembleNodeData - Class in org.apache.spark.ml.tree
Info for one Node in a tree ensemble
EnsembleModelReadWrite.EnsembleNodeData$ - Class in org.apache.spark.ml.tree
 
EnsembleNodeData(int, DecisionTreeModelReadWrite.NodeData) - Constructor for class org.apache.spark.ml.tree.EnsembleModelReadWrite.EnsembleNodeData
 
EnsembleNodeData$() - Constructor for class org.apache.spark.ml.tree.EnsembleModelReadWrite.EnsembleNodeData$
 
entries() - Method in class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
 
Entropy - Class in org.apache.spark.mllib.tree.impurity
Class for calculating entropy during multiclass classification.
Entropy() - Constructor for class org.apache.spark.mllib.tree.impurity.Entropy
 
entrySet() - Method in class org.apache.spark.api.java.JavaUtils.SerializableMapWrapper
 
EnumUtil - Class in org.apache.spark.util
 
EnumUtil() - Constructor for class org.apache.spark.util.EnumUtil
 
environmentDetails() - Method in class org.apache.spark.scheduler.SparkListenerEnvironmentUpdate
 
environmentUpdateFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
environmentUpdateToJson(SparkListenerEnvironmentUpdate) - Static method in class org.apache.spark.util.JsonProtocol
 
EPSILON() - Static method in class org.apache.spark.ml.impl.Utils
 
epsilon() - Method in interface org.apache.spark.ml.regression.LinearRegressionParams
The shape parameter to control the amount of robustness.
eqNullSafe(Object) - Method in class org.apache.spark.sql.Column
Equality test that is safe for null values.
EqualNullSafe - Class in org.apache.spark.sql.sources
Performs equality comparison, similar to EqualTo.
EqualNullSafe(String, Object) - Constructor for class org.apache.spark.sql.sources.EqualNullSafe
 
equals(Object) - Method in class org.apache.spark.api.java.Optional
 
equals(Object) - Static method in class org.apache.spark.ExpireDeadHosts
 
equals(Object) - Method in class org.apache.spark.graphx.EdgeDirection
 
equals(Object) - Method in class org.apache.spark.HashPartitioner
 
equals(Object) - Method in class org.apache.spark.ml.attribute.AttributeGroup
 
equals(Object) - Method in class org.apache.spark.ml.attribute.BinaryAttribute
 
equals(Object) - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
equals(Object) - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
equals(Object) - Static method in class org.apache.spark.ml.feature.Dot
 
equals(Object) - Method in class org.apache.spark.ml.linalg.DenseMatrix
 
equals(Object) - Method in class org.apache.spark.ml.linalg.DenseVector
 
equals(Object) - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
equals(Object) - Method in class org.apache.spark.ml.linalg.SparseVector
 
equals(Object) - Method in interface org.apache.spark.ml.linalg.Vector
 
equals(Object) - Method in class org.apache.spark.ml.param.Param
 
equals(Object) - Method in class org.apache.spark.ml.tree.CategoricalSplit
 
equals(Object) - Method in class org.apache.spark.ml.tree.ContinuousSplit
 
equals(Object) - Method in class org.apache.spark.mllib.linalg.DenseMatrix
 
equals(Object) - Method in class org.apache.spark.mllib.linalg.DenseVector
 
equals(Object) - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
equals(Object) - Method in class org.apache.spark.mllib.linalg.SparseVector
 
equals(Object) - Method in interface org.apache.spark.mllib.linalg.Vector
 
equals(Object) - Method in class org.apache.spark.mllib.linalg.VectorUDT
 
equals(Object) - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
 
equals(Object) - Method in class org.apache.spark.mllib.tree.model.Predict
 
equals(Object) - Method in class org.apache.spark.partial.BoundedDouble
 
equals(Object) - Method in interface org.apache.spark.Partition
 
equals(Object) - Method in class org.apache.spark.RangePartitioner
 
equals(Object) - Static method in class org.apache.spark.Resubmitted
 
equals(Object) - Static method in class org.apache.spark.rpc.netty.OnStart
 
equals(Object) - Static method in class org.apache.spark.rpc.netty.OnStop
 
equals(Object) - Static method in class org.apache.spark.scheduler.AllJobsCancelled
 
equals(Object) - Method in class org.apache.spark.scheduler.cluster.ExecutorInfo
 
equals(Object) - Method in class org.apache.spark.scheduler.InputFormatInfo
 
equals(Object) - Static method in class org.apache.spark.scheduler.JobSucceeded
 
equals(Object) - Static method in class org.apache.spark.scheduler.ResubmitFailedStages
 
equals(Object) - Method in class org.apache.spark.scheduler.SplitInfo
 
equals(Object) - Static method in class org.apache.spark.scheduler.StopCoordinator
 
equals(Object) - Method in class org.apache.spark.sql.Column
 
equals(Object) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
equals(Object) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
equals(Object) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
equals(Object) - Method in interface org.apache.spark.sql.Row
 
equals(Object) - Method in class org.apache.spark.sql.sources.In
 
equals(Object) - Method in class org.apache.spark.sql.sources.v2.reader.streaming.Offset
Equality based on JSON string representation.
equals(Object) - Static method in class org.apache.spark.sql.types.BinaryType
 
equals(Object) - Static method in class org.apache.spark.sql.types.BooleanType
 
equals(Object) - Static method in class org.apache.spark.sql.types.ByteType
 
equals(Object) - Static method in class org.apache.spark.sql.types.CalendarIntervalType
 
equals(Object) - Static method in class org.apache.spark.sql.types.DateType
 
equals(Object) - Method in class org.apache.spark.sql.types.Decimal
 
equals(Object) - Static method in class org.apache.spark.sql.types.DoubleType
 
equals(Object) - Static method in class org.apache.spark.sql.types.FloatType
 
equals(Object) - Static method in class org.apache.spark.sql.types.IntegerType
 
equals(Object) - Static method in class org.apache.spark.sql.types.LongType
 
equals(Object) - Method in class org.apache.spark.sql.types.Metadata
 
equals(Object) - Static method in class org.apache.spark.sql.types.NullType
 
equals(Object) - Static method in class org.apache.spark.sql.types.ShortType
 
equals(Object) - Static method in class org.apache.spark.sql.types.StringType
 
equals(Object) - Method in class org.apache.spark.sql.types.StructType
 
equals(Object) - Static method in class org.apache.spark.sql.types.TimestampType
 
equals(Object) - Static method in class org.apache.spark.StopMapOutputTracker
 
equals(Object) - Method in class org.apache.spark.storage.BlockManagerId
 
equals(Object) - Method in class org.apache.spark.storage.StorageLevel
 
equals(Object) - Static method in class org.apache.spark.streaming.kinesis.DefaultCredentials
 
equals(Object) - Static method in class org.apache.spark.streaming.scheduler.AllReceiverIds
 
equals(Object) - Static method in class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
 
equals(Object) - Static method in class org.apache.spark.streaming.scheduler.StopAllReceivers
 
equals(Object) - Static method in class org.apache.spark.Success
 
equals(Object) - Static method in class org.apache.spark.TaskResultLost
 
equals(Object) - Static method in class org.apache.spark.TaskSchedulerIsSet
 
equals(Object) - Static method in class org.apache.spark.UnknownReason
 
equalsStructurally(DataType, DataType, boolean) - Static method in class org.apache.spark.sql.types.DataType
Returns true if the two data types share the same "shape", i.e.
equalTo(Object) - Method in class org.apache.spark.sql.Column
Equality test.
EqualTo - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff the attribute evaluates to a value equal to value.
EqualTo(String, Object) - Constructor for class org.apache.spark.sql.sources.EqualTo
 
err(String) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
ERROR() - Static method in class org.apache.spark.status.TaskIndexNames
 
ErrorHandlingReadableChannel(ReadableByteChannel, ReadableByteChannel) - Constructor for class org.apache.spark.security.CryptoStreamUtils.ErrorHandlingReadableChannel
 
errorMessage() - Method in class org.apache.spark.status.api.v1.TaskData
 
errorMessage() - Method in class org.apache.spark.status.LiveTask
 
estimate(double[]) - Method in class org.apache.spark.mllib.stat.KernelDensity
Estimates probability density function at the given array of points.
estimate(Object) - Static method in class org.apache.spark.util.SizeEstimator
Estimate the number of bytes that the given object takes up on the JVM heap.
estimateCount(Object) - Method in class org.apache.spark.util.sketch.CountMinSketch
Returns the estimated frequency of item.
estimatedDocConcentration() - Method in class org.apache.spark.ml.clustering.LDAModel
Value for docConcentration estimated from data.
estimatedSize() - Method in class org.apache.spark.storage.memory.DeserializedValuesHolder
 
estimatedSize() - Method in class org.apache.spark.storage.memory.SerializedValuesHolder
 
estimatedSize() - Method in interface org.apache.spark.storage.memory.ValuesHolder
 
estimatedSize() - Method in interface org.apache.spark.util.KnownSizeEstimation
 
estimateStatistics() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsReportStatistics
Returns the estimated statistics of this data source.
Estimator<M extends Model<M>> - Class in org.apache.spark.ml
:: DeveloperApi :: Abstract class for estimators that fit models to data.
Estimator() - Constructor for class org.apache.spark.ml.Estimator
 
estimator() - Method in interface org.apache.spark.ml.tuning.ValidatorParams
param for the estimator to be validated
estimatorParamMaps() - Method in interface org.apache.spark.ml.tuning.ValidatorParams
param for estimator param maps
eval() - Method in interface org.apache.spark.ml.ann.ActivationFunction
Implements a function
eval(DenseMatrix<Object>, DenseMatrix<Object>) - Method in interface org.apache.spark.ml.ann.LayerModel
Evaluates the data (process the data through the layer).
evaluate(Dataset<?>) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
Evaluates the model on a test dataset.
evaluate(Dataset<?>) - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
 
evaluate(Dataset<?>) - Method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
evaluate(Dataset<?>, ParamMap) - Method in class org.apache.spark.ml.evaluation.Evaluator
Evaluates model output and returns a scalar metric.
evaluate(Dataset<?>) - Method in class org.apache.spark.ml.evaluation.Evaluator
Evaluates model output and returns a scalar metric.
evaluate(Dataset<?>) - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
 
evaluate(Dataset<?>) - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
 
evaluate(Dataset<?>) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
Evaluate the model on the given dataset, returning a summary of the results.
evaluate(Dataset<?>) - Method in class org.apache.spark.ml.regression.LinearRegressionModel
Evaluates the model on a test dataset.
evaluate(Row) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
Calculates the final result of this UserDefinedAggregateFunction based on the given aggregation buffer.
evaluateEachIteration(Dataset<?>) - Method in class org.apache.spark.ml.classification.GBTClassificationModel
Method to compute error or loss for every iteration of gradient boosting.
evaluateEachIteration(Dataset<?>, String) - Method in class org.apache.spark.ml.regression.GBTRegressionModel
Method to compute error or loss for every iteration of gradient boosting.
evaluateEachIteration(RDD<LabeledPoint>, DecisionTreeRegressionModel[], double[], Loss, Enumeration.Value) - Static method in class org.apache.spark.ml.tree.impl.GradientBoostedTrees
Method to compute error or loss for every iteration of gradient boosting.
evaluateEachIteration(RDD<LabeledPoint>, Loss) - Method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
Method to compute error or loss for every iteration of gradient boosting.
Evaluator - Class in org.apache.spark.ml.evaluation
:: DeveloperApi :: Abstract class for evaluators that compute metrics from predictions.
Evaluator() - Constructor for class org.apache.spark.ml.evaluation.Evaluator
 
evaluator() - Method in interface org.apache.spark.ml.tuning.ValidatorParams
param for the evaluator used to select hyper-parameters that maximize the validated metric
eventRates() - Method in class org.apache.spark.status.api.v1.streaming.ReceiverInfo
 
eventTime() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
 
EventTimeTimeout() - Static method in class org.apache.spark.sql.streaming.GroupStateTimeout
Timeout based on event-time.
except(Dataset<T>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset containing rows in this Dataset but not in another Dataset.
exceptAll(Dataset<T>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset containing rows in this Dataset but not in another Dataset while preserving the duplicates.
exception() - Method in class org.apache.spark.ExceptionFailure
 
exception() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationWriterThread
Contains the exception thrown while writing the parent iterator to the external process.
exception() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Returns the StreamingQueryException if the query was terminated by an exception.
exception() - Method in class org.apache.spark.sql.streaming.StreamingQueryListener.QueryTerminatedEvent
 
ExceptionFailure - Class in org.apache.spark
:: DeveloperApi :: Task failed due to a runtime exception.
ExceptionFailure(String, String, StackTraceElement[], String, Option<ThrowableSerializationWrapper>, Seq<AccumulableInfo>, Seq<AccumulatorV2<?, ?>>) - Constructor for class org.apache.spark.ExceptionFailure
 
exceptionFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
exceptionString(Throwable) - Static method in class org.apache.spark.util.Utils
Return a nice string representation of the exception.
exceptionToJson(Exception) - Static method in class org.apache.spark.util.JsonProtocol
 
EXEC_CPU_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
 
EXEC_RUN_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
 
execId() - Method in class org.apache.spark.ExecutorLostFailure
 
execId() - Method in class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
 
execId() - Method in class org.apache.spark.storage.BlockManagerMessages.RemoveExecutor
 
executeAndGetOutput(Seq<String>, File, Map<String, String>, boolean) - Static method in class org.apache.spark.util.Utils
Execute a command and get its output, throwing an exception if it yields a code other than 0.
executeCommand(Seq<String>, File, Map<String, String>, boolean) - Static method in class org.apache.spark.util.Utils
Execute a command and return the process running the command.
executionId() - Method in interface org.apache.spark.sql.hive.execution.SaveAsHiveFile
 
ExecutionListenerManager - Class in org.apache.spark.sql.util
:: Experimental ::
executor() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask
 
EXECUTOR() - Static method in class org.apache.spark.status.TaskIndexNames
 
EXECUTOR_CORES - Static variable in class org.apache.spark.launcher.SparkLauncher
Configuration key for the number of executor CPU cores.
EXECUTOR_CPU_TIME() - Static method in class org.apache.spark.InternalAccumulator
 
EXECUTOR_DESERIALIZE_CPU_TIME() - Static method in class org.apache.spark.InternalAccumulator
 
EXECUTOR_DESERIALIZE_TIME() - Static method in class org.apache.spark.InternalAccumulator
 
EXECUTOR_EXTRA_CLASSPATH - Static variable in class org.apache.spark.launcher.SparkLauncher
Configuration key for the executor class path.
EXECUTOR_EXTRA_JAVA_OPTIONS - Static variable in class org.apache.spark.launcher.SparkLauncher
Configuration key for the executor VM options.
EXECUTOR_EXTRA_LIBRARY_PATH - Static variable in class org.apache.spark.launcher.SparkLauncher
Configuration key for the executor native library path.
EXECUTOR_MEMORY - Static variable in class org.apache.spark.launcher.SparkLauncher
Configuration key for the executor memory.
EXECUTOR_RUN_TIME() - Static method in class org.apache.spark.InternalAccumulator
 
executorAddedFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
executorAddedToJson(SparkListenerExecutorAdded) - Static method in class org.apache.spark.util.JsonProtocol
 
ExecutorAllocationClient - Interface in org.apache.spark
A client that communicates with the cluster manager to request or kill executors.
executorCpuTime() - Method in class org.apache.spark.status.api.v1.StageData
 
executorCpuTime() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
executorCpuTime() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 
executorDeserializeCpuTime() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
executorDeserializeCpuTime() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 
executorDeserializeTime() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
executorDeserializeTime() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 
executorFailures() - Method in class org.apache.spark.scheduler.SparkListenerNodeBlacklisted
 
executorFailures() - Method in class org.apache.spark.scheduler.SparkListenerNodeBlacklistedForStage
 
executorHeartbeatReceived(String, Tuple2<Object, Seq<AccumulatorV2<?, ?>>>[], BlockManagerId) - Method in interface org.apache.spark.scheduler.TaskScheduler
Update metrics for in-progress tasks and let the master know that the BlockManager is still alive.
executorHost() - Method in class org.apache.spark.scheduler.cluster.ExecutorInfo
 
executorHost() - Method in class org.apache.spark.status.api.v1.streaming.ReceiverInfo
 
executorId() - Method in class org.apache.spark.ExecutorRegistered
 
executorId() - Method in class org.apache.spark.ExecutorRemoved
 
executorId() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.GetExecutorLossReason
 
executorId() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor
 
executorId() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor
 
executorId() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate
 
executorId() - Method in class org.apache.spark.scheduler.SparkListenerExecutorAdded
 
executorId() - Method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklisted
 
executorId() - Method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklistedForStage
 
executorId() - Method in class org.apache.spark.scheduler.SparkListenerExecutorRemoved
 
executorId() - Method in class org.apache.spark.scheduler.SparkListenerExecutorUnblacklisted
 
executorId() - Method in class org.apache.spark.scheduler.TaskInfo
 
executorId() - Method in class org.apache.spark.SparkEnv
 
executorId() - Method in class org.apache.spark.status.api.v1.streaming.ReceiverInfo
 
executorId() - Method in class org.apache.spark.status.api.v1.TaskData
 
executorId() - Method in class org.apache.spark.status.LiveExecutor
 
executorId() - Method in class org.apache.spark.status.LiveRDDDistribution
 
executorId() - Method in class org.apache.spark.storage.BlockManagerId
 
executorId() - Method in class org.apache.spark.storage.BlockManagerMessages.GetExecutorEndpointRef
 
executorId() - Method in class org.apache.spark.storage.BlockManagerMessages.HasCachedBlocks
 
executorId() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
 
executorId() - Method in class org.apache.spark.ui.storage.ExecutorStreamSummary
 
executorIds() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillExecutors
 
ExecutorInfo - Class in org.apache.spark.scheduler.cluster
:: DeveloperApi :: Stores information about an executor to pass from the scheduler to SparkListeners.
ExecutorInfo(String, int, Map<String, String>) - Constructor for class org.apache.spark.scheduler.cluster.ExecutorInfo
 
executorInfo() - Method in class org.apache.spark.scheduler.SparkListenerExecutorAdded
 
executorInfoFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
executorInfoToJson(ExecutorInfo) - Static method in class org.apache.spark.util.JsonProtocol
 
ExecutorKilled - Class in org.apache.spark.scheduler
 
ExecutorKilled() - Constructor for class org.apache.spark.scheduler.ExecutorKilled
 
executorLogs() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
executorLogs() - Method in class org.apache.spark.status.LiveExecutor
 
executorLost(String, String, ExecutorLossReason) - Method in interface org.apache.spark.scheduler.Schedulable
 
executorLost(String, ExecutorLossReason) - Method in interface org.apache.spark.scheduler.TaskScheduler
Process a lost executor
ExecutorLostFailure - Class in org.apache.spark
:: DeveloperApi :: The task failed because the executor that it was running on was lost.
ExecutorLostFailure(String, boolean, Option<String>) - Constructor for class org.apache.spark.ExecutorLostFailure
 
executorMetricsUpdateFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
executorMetricsUpdateToJson(SparkListenerExecutorMetricsUpdate) - Static method in class org.apache.spark.util.JsonProtocol
 
executorPct() - Method in class org.apache.spark.scheduler.RuntimePercentage
 
ExecutorPlugin - Interface in org.apache.spark
A plugin which can be automatically instantiated within each Spark executor.
executorRef() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor
 
ExecutorRegistered - Class in org.apache.spark
 
ExecutorRegistered(String) - Constructor for class org.apache.spark.ExecutorRegistered
 
ExecutorRemoved - Class in org.apache.spark
 
ExecutorRemoved(String) - Constructor for class org.apache.spark.ExecutorRemoved
 
executorRemovedFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
executorRemovedToJson(SparkListenerExecutorRemoved) - Static method in class org.apache.spark.util.JsonProtocol
 
executorRunTime() - Method in class org.apache.spark.status.api.v1.StageData
 
executorRunTime() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
executorRunTime() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 
executors() - Method in class org.apache.spark.status.api.v1.RDDPartitionInfo
 
executors() - Method in class org.apache.spark.status.LiveRDDPartition
 
ExecutorStageSummary - Class in org.apache.spark.status.api.v1
 
ExecutorStreamSummary - Class in org.apache.spark.ui.storage
 
ExecutorStreamSummary(Seq<org.apache.spark.status.StreamBlockData>) - Constructor for class org.apache.spark.ui.storage.ExecutorStreamSummary
 
executorSummaries() - Method in class org.apache.spark.status.LiveStage
 
ExecutorSummary - Class in org.apache.spark.status.api.v1
 
executorSummary() - Method in class org.apache.spark.status.api.v1.StageData
 
executorSummary(String) - Method in class org.apache.spark.status.LiveStage
 
exists() - Method in interface org.apache.spark.sql.streaming.GroupState
Whether state exists or not.
exists(String) - Static method in class org.apache.spark.sql.types.UDTRegistration
Queries if a given user class is already registered or not.
exists() - Method in class org.apache.spark.streaming.State
Whether the state already exists
exitCausedByApp() - Method in class org.apache.spark.ExecutorLostFailure
 
exitFn() - Method in interface org.apache.spark.util.CommandLineUtils
 
exp(Column) - Static method in class org.apache.spark.sql.functions
Computes the exponential of the given value.
exp(String) - Static method in class org.apache.spark.sql.functions
Computes the exponential of the given column.
ExpectationAggregator - Class in org.apache.spark.ml.clustering
ExpectationAggregator computes the partial expectation results.
ExpectationAggregator(int, Broadcast<double[]>, Broadcast<Tuple2<DenseVector, DenseVector>[]>) - Constructor for class org.apache.spark.ml.clustering.ExpectationAggregator
 
ExpectationSum - Class in org.apache.spark.mllib.clustering
 
ExpectationSum(double, double[], DenseVector<Object>[], DenseMatrix<Object>[]) - Constructor for class org.apache.spark.mllib.clustering.ExpectationSum
 
expectedFpp() - Method in class org.apache.spark.util.sketch.BloomFilter
Returns the probability that BloomFilter.mightContain(Object) erroneously return true for an object that has not actually been put in the BloomFilter.
experimental() - Method in class org.apache.spark.sql.SparkSession
:: Experimental :: A collection of methods that are considered experimental, but can be used to hook into the query planner for advanced functionality.
experimental() - Method in class org.apache.spark.sql.SQLContext
:: Experimental :: A collection of methods that are considered experimental, but can be used to hook into the query planner for advanced functionality.
ExperimentalMethods - Class in org.apache.spark.sql
:: Experimental :: Holder for experimental methods for the bravest.
ExpireDeadHosts - Class in org.apache.spark
 
ExpireDeadHosts() - Constructor for class org.apache.spark.ExpireDeadHosts
 
expiryTime() - Method in class org.apache.spark.scheduler.BlacklistedExecutor
 
explain(boolean) - Method in class org.apache.spark.sql.Column
Prints the expression to the console for debugging purposes.
explain(boolean) - Method in class org.apache.spark.sql.Dataset
Prints the plans (logical and physical) to the console for debugging purposes.
explain() - Method in class org.apache.spark.sql.Dataset
Prints the physical plan to the console for debugging purposes.
explain() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Prints the physical plan to the console for debugging purposes.
explain(boolean) - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Prints the physical plan to the console for debugging purposes.
explainedVariance() - Method in class org.apache.spark.ml.feature.PCAModel
 
explainedVariance() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
Returns the explained variance regression score.
explainedVariance() - Method in class org.apache.spark.mllib.evaluation.RegressionMetrics
Returns the variance explained by regression.
explainedVariance() - Method in class org.apache.spark.mllib.feature.PCAModel
 
explainParam(Param<?>) - Method in interface org.apache.spark.ml.param.Params
Explains a param.
explainParams() - Method in interface org.apache.spark.ml.param.Params
Explains all params of this instance.
explode(Seq<Column>, Function1<Row, TraversableOnce<A>>, TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.Dataset
Deprecated.
use flatMap() or select() with functions.explode() instead. Since 2.0.0.
explode(String, String, Function1<A, TraversableOnce<B>>, TypeTags.TypeTag<B>) - Method in class org.apache.spark.sql.Dataset
Deprecated.
use flatMap() or select() with functions.explode() instead. Since 2.0.0.
explode(Column) - Static method in class org.apache.spark.sql.functions
Creates a new row for each element in the given array or map column.
explode_outer(Column) - Static method in class org.apache.spark.sql.functions
Creates a new row for each element in the given array or map column.
expm1(Column) - Static method in class org.apache.spark.sql.functions
Computes the exponential of the given value minus one.
expm1(String) - Static method in class org.apache.spark.sql.functions
Computes the exponential of the given column minus one.
ExponentialGenerator - Class in org.apache.spark.mllib.random
:: DeveloperApi :: Generates i.i.d.
ExponentialGenerator(double) - Constructor for class org.apache.spark.mllib.random.ExponentialGenerator
 
exponentialJavaRDD(JavaSparkContext, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Java-friendly version of RandomRDDs.exponentialRDD.
exponentialJavaRDD(JavaSparkContext, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.exponentialJavaRDD with the default seed.
exponentialJavaRDD(JavaSparkContext, double, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.exponentialJavaRDD with the default number of partitions and the default seed.
exponentialJavaVectorRDD(JavaSparkContext, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Java-friendly version of RandomRDDs.exponentialVectorRDD.
exponentialJavaVectorRDD(JavaSparkContext, double, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.exponentialJavaVectorRDD with the default seed.
exponentialJavaVectorRDD(JavaSparkContext, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.exponentialJavaVectorRDD with the default number of partitions and the default seed.
exponentialRDD(SparkContext, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Generates an RDD comprised of i.i.d. samples from the exponential distribution with the input mean.
exponentialVectorRDD(SparkContext, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from the exponential distribution with the input mean.
expr() - Method in class org.apache.spark.sql.Column
 
expr(String) - Static method in class org.apache.spark.sql.functions
Parses the expression string into the column that it represents, similar to Dataset.selectExpr(java.lang.String...).
Expression$() - Constructor for class org.apache.spark.sql.types.DecimalType.Expression$
 
extensionsForCompressionCodecNames() - Static method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
externalBlockStoreSize() - Method in class org.apache.spark.storage.RDDInfo
 
ExternalClusterManager - Interface in org.apache.spark.scheduler
A cluster manager interface to plugin external scheduler.
extractDistribution(Function1<BatchInfo, Option<Object>>) - Method in class org.apache.spark.streaming.scheduler.StatsReportListener
 
extractDoubleDistribution(Seq<Tuple2<TaskInfo, TaskMetrics>>, Function2<TaskInfo, TaskMetrics, Object>) - Static method in class org.apache.spark.scheduler.StatsReportListener
 
extractFn() - Method in class org.apache.spark.ui.JettyUtils.ServletParams
 
extractHostPortFromSparkUrl(String) - Static method in class org.apache.spark.util.Utils
Return a pair of host and port extracted from the sparkUrl.
extractLongDistribution(Seq<Tuple2<TaskInfo, TaskMetrics>>, Function2<TaskInfo, TaskMetrics, Object>) - Static method in class org.apache.spark.scheduler.StatsReportListener
 
extractParamMap(ParamMap) - Method in interface org.apache.spark.ml.param.Params
Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.
extractParamMap() - Method in interface org.apache.spark.ml.param.Params
extractParamMap with no extra values.
extractWeightedLabeledPoints(Dataset<?>) - Method in interface org.apache.spark.ml.regression.IsotonicRegressionBase
Extracts (label, feature, weight) from input dataset.
extraOptimizations() - Method in class org.apache.spark.sql.ExperimentalMethods
 
extraStrategies() - Method in class org.apache.spark.sql.ExperimentalMethods
Allows extra strategies to be injected into the query planner at runtime.
eye(int) - Static method in class org.apache.spark.ml.linalg.DenseMatrix
Generate an Identity Matrix in DenseMatrix format.
eye(int) - Static method in class org.apache.spark.ml.linalg.Matrices
Generate a dense Identity Matrix in Matrix format.
eye(int) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
Generate an Identity Matrix in DenseMatrix format.
eye(int) - Static method in class org.apache.spark.mllib.linalg.Matrices
Generate a dense Identity Matrix in Matrix format.

F

f() - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
 
f1Measure() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
Returns document-based f1-measure averaged by the number of documents
f1Measure(double) - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
Returns f1-measure for a given label (category)
factorial(Column) - Static method in class org.apache.spark.sql.functions
Computes the factorial of the given value.
failed() - Method in class org.apache.spark.scheduler.TaskInfo
 
FAILED() - Static method in class org.apache.spark.TaskState
 
failedStages() - Method in class org.apache.spark.status.LiveJob
 
failedTasks() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
failedTasks() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
failedTasks() - Method in class org.apache.spark.status.LiveExecutor
 
failedTasks() - Method in class org.apache.spark.status.LiveExecutorStageSummary
 
failedTasks() - Method in class org.apache.spark.status.LiveJob
 
failedTasks() - Method in class org.apache.spark.status.LiveStage
 
failure(String) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
failureReason() - Method in class org.apache.spark.scheduler.StageInfo
If the stage failed, the reason why.
failureReason() - Method in class org.apache.spark.status.api.v1.StageData
 
failureReason() - Method in class org.apache.spark.status.api.v1.streaming.OutputOperationInfo
 
failureReason() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
 
failureReasonCell(String, int, boolean) - Static method in class org.apache.spark.streaming.ui.UIUtils
 
FAIR() - Static method in class org.apache.spark.scheduler.SchedulingMode
 
FAKE_HIVE_VERSION() - Static method in class org.apache.spark.sql.hive.HiveUtils
 
FalsePositiveRate - Class in org.apache.spark.mllib.evaluation.binary
False positive rate.
FalsePositiveRate() - Constructor for class org.apache.spark.mllib.evaluation.binary.FalsePositiveRate
 
falsePositiveRate(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns false positive rate for a given label (category)
falsePositiveRateByLabel() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns false positive rate for each label (category).
family() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
Param for the name of family which is a description of the label distribution to be used in the model.
family() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
Param for the name of family which is a description of the error distribution to be used in the model.
Family$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Family$
 
FamilyAndLink$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.FamilyAndLink$
 
fdr() - Method in interface org.apache.spark.ml.feature.ChiSqSelectorParams
The upper bound of the expected false discovery rate.
fdr() - Method in class org.apache.spark.mllib.feature.ChiSqSelector
 
feature() - Method in class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$.Data
 
feature() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData
 
feature() - Method in class org.apache.spark.mllib.tree.model.Split
 
FeatureHasher - Class in org.apache.spark.ml.feature
Feature hashing projects a set of categorical or numerical features into a feature vector of specified dimension (typically substantially smaller than that of the original feature space).
FeatureHasher(String) - Constructor for class org.apache.spark.ml.feature.FeatureHasher
 
FeatureHasher() - Constructor for class org.apache.spark.ml.feature.FeatureHasher
 
featureImportances() - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
Estimate of the importance of each feature.
featureImportances() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
Estimate of the importance of each feature.
featureImportances() - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
Estimate of the importance of each feature.
featureImportances() - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
Estimate of the importance of each feature.
featureImportances() - Method in class org.apache.spark.ml.regression.GBTRegressionModel
Estimate of the importance of each feature.
featureImportances() - Method in class org.apache.spark.ml.regression.RandomForestRegressionModel
Estimate of the importance of each feature.
featureIndex() - Method in interface org.apache.spark.ml.regression.IsotonicRegressionBase
Param for the index of the feature if featuresCol is a vector column (default: 0), no effect otherwise.
featureIndex() - Method in class org.apache.spark.ml.tree.CategoricalSplit
 
featureIndex() - Method in class org.apache.spark.ml.tree.ContinuousSplit
 
featureIndex() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData
 
featureIndex() - Method in interface org.apache.spark.ml.tree.Split
Index of feature which this split tests
features() - Method in class org.apache.spark.ml.feature.LabeledPoint
 
features() - Method in class org.apache.spark.mllib.regression.LabeledPoint
 
featuresCol() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Field in "predictions" which gives the features of each instance as a vector.
featuresCol() - Method in class org.apache.spark.ml.classification.LogisticRegressionSummaryImpl
 
featuresCol() - Method in class org.apache.spark.ml.clustering.ClusteringSummary
 
featuresCol() - Method in interface org.apache.spark.ml.param.shared.HasFeaturesCol
Param for features column name.
featuresCol() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
 
featureSubsetStrategy() - Method in interface org.apache.spark.ml.tree.TreeEnsembleParams
The number of features to consider for splits at each tree node.
featureSum() - Method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette.ClusterStats
 
FeatureType - Class in org.apache.spark.mllib.tree.configuration
Enum to describe whether a feature is "continuous" or "categorical"
FeatureType() - Constructor for class org.apache.spark.mllib.tree.configuration.FeatureType
 
featureType() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData
 
featureType() - Method in class org.apache.spark.mllib.tree.model.Split
 
FETCH_WAIT_TIME() - Method in class org.apache.spark.InternalAccumulator.shuffleRead$
 
FetchFailed - Class in org.apache.spark
:: DeveloperApi :: Task failed to fetch shuffle data from a remote node.
FetchFailed(BlockManagerId, int, int, int, String) - Constructor for class org.apache.spark.FetchFailed
 
fetchFile(String, File, SparkConf, org.apache.spark.SecurityManager, Configuration, long, boolean) - Static method in class org.apache.spark.util.Utils
Download a file or directory to target directory.
fetchPct() - Method in class org.apache.spark.scheduler.RuntimePercentage
 
fetchWaitTime() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
 
fetchWaitTime() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
 
field() - Method in class org.apache.spark.storage.BroadcastBlockId
 
fieldIndex(String) - Method in interface org.apache.spark.sql.Row
Returns the index of a given field name.
fieldIndex(String) - Method in class org.apache.spark.sql.types.StructType
Returns the index of a given field.
fieldNames() - Method in class org.apache.spark.sql.types.StructType
Returns all field names in an array.
fields() - Method in class org.apache.spark.sql.types.StructType
 
FIFO() - Static method in class org.apache.spark.scheduler.SchedulingMode
 
FILE_FORMAT() - Static method in class org.apache.spark.sql.hive.execution.HiveOptions
 
FileBasedTopologyMapper - Class in org.apache.spark.storage
A simple file based topology mapper.
FileBasedTopologyMapper(SparkConf) - Constructor for class org.apache.spark.storage.FileBasedTopologyMapper
 
FileCommitProtocol - Class in org.apache.spark.internal.io
An interface to define how a single Spark job commits its outputs.
FileCommitProtocol() - Constructor for class org.apache.spark.internal.io.FileCommitProtocol
 
FileCommitProtocol.EmptyTaskCommitMessage$ - Class in org.apache.spark.internal.io
 
FileCommitProtocol.TaskCommitMessage - Class in org.apache.spark.internal.io
 
fileFormat() - Method in class org.apache.spark.sql.hive.execution.HiveOptions
 
files() - Method in class org.apache.spark.SparkContext
 
fileStream(String, Class<K>, Class<V>, Class<F>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream that monitors a Hadoop-compatible filesystem for new files and reads them using the given key-value types and input format.
fileStream(String, Class<K>, Class<V>, Class<F>, Function<Path, Boolean>, boolean) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream that monitors a Hadoop-compatible filesystem for new files and reads them using the given key-value types and input format.
fileStream(String, Class<K>, Class<V>, Class<F>, Function<Path, Boolean>, boolean, Configuration) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream that monitors a Hadoop-compatible filesystem for new files and reads them using the given key-value types and input format.
fileStream(String, ClassTag<K>, ClassTag<V>, ClassTag<F>) - Method in class org.apache.spark.streaming.StreamingContext
Create an input stream that monitors a Hadoop-compatible filesystem for new files and reads them using the given key-value types and input format.
fileStream(String, Function1<Path, Object>, boolean, ClassTag<K>, ClassTag<V>, ClassTag<F>) - Method in class org.apache.spark.streaming.StreamingContext
Create an input stream that monitors a Hadoop-compatible filesystem for new files and reads them using the given key-value types and input format.
fileStream(String, Function1<Path, Object>, boolean, Configuration, ClassTag<K>, ClassTag<V>, ClassTag<F>) - Method in class org.apache.spark.streaming.StreamingContext
Create an input stream that monitors a Hadoop-compatible filesystem for new files and reads them using the given key-value types and input format.
fill(long) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that replaces null or NaN values in numeric columns with value.
fill(double) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that replaces null or NaN values in numeric columns with value.
fill(String) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that replaces null values in string columns with value.
fill(long, String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that replaces null or NaN values in specified numeric columns.
fill(double, String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that replaces null or NaN values in specified numeric columns.
fill(long, Seq<String>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
(Scala-specific) Returns a new DataFrame that replaces null or NaN values in specified numeric columns.
fill(double, Seq<String>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
(Scala-specific) Returns a new DataFrame that replaces null or NaN values in specified numeric columns.
fill(String, String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that replaces null values in specified string columns.
fill(String, Seq<String>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
(Scala-specific) Returns a new DataFrame that replaces null values in specified string columns.
fill(boolean) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that replaces null values in boolean columns with value.
fill(boolean, Seq<String>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
(Scala-specific) Returns a new DataFrame that replaces null values in specified boolean columns.
fill(boolean, String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that replaces null values in specified boolean columns.
fill(Map<String, Object>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Returns a new DataFrame that replaces null values.
fill(Map<String, Object>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
(Scala-specific) Returns a new DataFrame that replaces null values.
filter(Function<Double, Boolean>) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return a new RDD containing only the elements that satisfy a predicate.
filter(Function<Tuple2<K, V>, Boolean>) - Method in class org.apache.spark.api.java.JavaPairRDD
Return a new RDD containing only the elements that satisfy a predicate.
filter(Function<T, Boolean>) - Method in class org.apache.spark.api.java.JavaRDD
Return a new RDD containing only the elements that satisfy a predicate.
filter(Function1<Graph<VD, ED>, Graph<VD2, ED2>>, Function1<EdgeTriplet<VD2, ED2>, Object>, Function2<Object, VD2, Object>, ClassTag<VD2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.GraphOps
Filter the graph by computing some values to filter on, and applying the predicates.
filter(Function1<EdgeTriplet<VD, ED>, Object>, Function2<Object, VD, Object>) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
filter(Function1<Tuple2<Object, VD>, Object>) - Method in class org.apache.spark.graphx.VertexRDD
Restricts the vertex set to the set of vertices satisfying the given predicate.
filter(Params) - Method in class org.apache.spark.ml.param.ParamMap
Filters this param map for the given parent.
filter(Function1<T, Object>) - Method in class org.apache.spark.rdd.RDD
Return a new RDD containing only the elements that satisfy a predicate.
filter(Column) - Method in class org.apache.spark.sql.Dataset
Filters rows using the given condition.
filter(String) - Method in class org.apache.spark.sql.Dataset
Filters rows using the given SQL expression.
filter(Function1<T, Object>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: (Scala-specific) Returns a new Dataset that only contains elements where func returns true.
filter(FilterFunction<T>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: (Java-specific) Returns a new Dataset that only contains elements where func returns true.
Filter - Class in org.apache.spark.sql.sources
A filter predicate for data sources.
Filter() - Constructor for class org.apache.spark.sql.sources.Filter
 
filter() - Method in class org.apache.spark.storage.BlockManagerMessages.GetMatchingBlockIds
 
filter(Function<T, Boolean>) - Method in class org.apache.spark.streaming.api.java.JavaDStream
Return a new DStream containing only the elements that satisfy a predicate.
filter(Function<Tuple2<K, V>, Boolean>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream containing only the elements that satisfy a predicate.
filter(Function1<T, Object>) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream containing only the elements that satisfy a predicate.
filterByRange(K, K) - Method in class org.apache.spark.rdd.OrderedRDDFunctions
Returns an RDD containing only the elements in the inclusive range lower to upper.
FilterFunction<T> - Interface in org.apache.spark.api.java.function
Base interface for a function used in Dataset's filter function.
filterName() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
 
filterParams() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
 
finalStorageLevel() - Method in interface org.apache.spark.ml.recommendation.ALSParams
Param for StorageLevel for ALS model factors.
findClass(String) - Method in class org.apache.spark.util.ParentClassLoader
 
findFrequentSequentialPatterns(Dataset<?>) - Method in class org.apache.spark.ml.fpm.PrefixSpan
:: Experimental :: Finds the complete set of frequent sequential patterns in the input sequences of itemsets.
findListenersByClass(ClassTag<T>) - Method in interface org.apache.spark.util.ListenerBus
 
findMissingPartitions() - Method in class org.apache.spark.ShuffleStatus
Returns the sequence of partition ids that are missing (i.e.
findSynonyms(String, int) - Method in class org.apache.spark.ml.feature.Word2VecModel
Find "num" number of words closest in similarity to the given word, not including the word itself.
findSynonyms(Vector, int) - Method in class org.apache.spark.ml.feature.Word2VecModel
Find "num" number of words whose vector representation is most similar to the supplied vector.
findSynonyms(String, int) - Method in class org.apache.spark.mllib.feature.Word2VecModel
Find synonyms of a word; do not include the word itself in results.
findSynonyms(Vector, int) - Method in class org.apache.spark.mllib.feature.Word2VecModel
Find synonyms of the vector representation of a word, possibly including any words in the model vocabulary whose vector respresentation is the supplied vector.
findSynonymsArray(Vector, int) - Method in class org.apache.spark.ml.feature.Word2VecModel
Find "num" number of words whose vector representation is most similar to the supplied vector.
findSynonymsArray(String, int) - Method in class org.apache.spark.ml.feature.Word2VecModel
Find "num" number of words closest in similarity to the given word, not including the word itself.
finish(BUF) - Method in class org.apache.spark.sql.expressions.Aggregator
Transform the output of the reduction.
finished() - Method in class org.apache.spark.scheduler.TaskInfo
 
FINISHED() - Static method in class org.apache.spark.TaskState
 
finishTime() - Method in class org.apache.spark.scheduler.TaskInfo
The time when the task has completed successfully (including the time to remotely fetch results, if necessary).
first() - Method in class org.apache.spark.api.java.JavaDoubleRDD
 
first() - Method in class org.apache.spark.api.java.JavaPairRDD
 
first() - Method in interface org.apache.spark.api.java.JavaRDDLike
Return the first element in this RDD.
first() - Method in class org.apache.spark.rdd.RDD
Return the first element in this RDD.
first() - Method in class org.apache.spark.sql.Dataset
Returns the first row.
first(Column, boolean) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the first value in a group.
first(String, boolean) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the first value of a column in a group.
first(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the first value in a group.
first(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the first value of a column in a group.
firstFailureReason() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
 
firstLaunchTime() - Method in class org.apache.spark.status.LiveStage
 
firstTaskLaunchedTime() - Method in class org.apache.spark.status.api.v1.StageData
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.classification.OneVsRest
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.clustering.GaussianMixture
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.clustering.KMeans
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.clustering.LDA
 
fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Method in class org.apache.spark.ml.Estimator
Fits a single model to the input data with optional parameters.
fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Method in class org.apache.spark.ml.Estimator
Fits a single model to the input data with optional parameters.
fit(Dataset<?>, ParamMap) - Method in class org.apache.spark.ml.Estimator
Fits a single model to the input data with provided parameter map.
fit(Dataset<?>) - Method in class org.apache.spark.ml.Estimator
Fits a model to the input data.
fit(Dataset<?>, ParamMap[]) - Method in class org.apache.spark.ml.Estimator
Fits multiple models to the input data with multiple sets of parameters.
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.ChiSqSelector
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.CountVectorizer
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.IDF
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.Imputer
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.MaxAbsScaler
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.MinMaxScaler
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.PCA
Computes a PCAModel that contains the principal components of the input vectors.
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.RFormula
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.StandardScaler
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.StringIndexer
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.VectorIndexer
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.Word2Vec
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.fpm.FPGrowth
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.Pipeline
Fits the pipeline to the input dataset with additional parameters.
fit(Dataset<?>) - Method in class org.apache.spark.ml.Predictor
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.recommendation.ALS
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.regression.IsotonicRegression
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.tuning.CrossValidator
 
fit(Dataset<?>) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
 
fit(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.feature.ChiSqSelector
Returns a ChiSquared feature selector.
fit(RDD<Vector>) - Method in class org.apache.spark.mllib.feature.IDF
Computes the inverse document frequency.
fit(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.feature.IDF
Computes the inverse document frequency.
fit(RDD<Vector>) - Method in class org.apache.spark.mllib.feature.PCA
Computes a PCAModel that contains the principal components of the input vectors.
fit(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.feature.PCA
Java-friendly version of fit().
fit(RDD<Vector>) - Method in class org.apache.spark.mllib.feature.StandardScaler
Computes the mean and variance and stores as a model to be used for later scaling.
fit(RDD<S>) - Method in class org.apache.spark.mllib.feature.Word2Vec
Computes the vector representation of each word in vocabulary.
fit(JavaRDD<S>) - Method in class org.apache.spark.mllib.feature.Word2Vec
Computes the vector representation of each word in vocabulary (Java version).
fitIntercept() - Method in interface org.apache.spark.ml.param.shared.HasFitIntercept
Param for whether to fit an intercept term.
Fixed$() - Constructor for class org.apache.spark.sql.types.DecimalType.Fixed$
 
flatMap(FlatMapFunction<T, U>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results.
flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results.
flatMap(Function1<T, TraversableOnce<U>>, Encoder<U>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: (Scala-specific) Returns a new Dataset by first applying a function to all elements of this Dataset, and then flattening the results.
flatMap(FlatMapFunction<T, U>, Encoder<U>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: (Java-specific) Returns a new Dataset by first applying a function to all elements of this Dataset, and then flattening the results.
flatMap(FlatMapFunction<T, U>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream by applying a function to all elements of this DStream, and then flattening the results
flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream by applying a function to all elements of this DStream, and then flattening the results
FlatMapFunction<T,R> - Interface in org.apache.spark.api.java.function
A function that returns zero or more output records from each input record.
FlatMapFunction2<T1,T2,R> - Interface in org.apache.spark.api.java.function
A function that takes two inputs and returns zero or more output records.
flatMapGroups(Function2<K, Iterator<V>, TraversableOnce<U>>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
(Scala-specific) Applies the given function to each group of data.
flatMapGroups(FlatMapGroupsFunction<K, V, U>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
(Java-specific) Applies the given function to each group of data.
FlatMapGroupsFunction<K,V,R> - Interface in org.apache.spark.api.java.function
A function that returns zero or more output records from each grouping key and its values.
flatMapGroupsWithState(OutputMode, GroupStateTimeout, Function3<K, Iterator<V>, GroupState<S>, Iterator<U>>, Encoder<S>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
::Experimental:: (Scala-specific) Applies the given function to each group of data, while maintaining a user-defined per-group state.
flatMapGroupsWithState(FlatMapGroupsWithStateFunction<K, V, S, U>, OutputMode, Encoder<S>, Encoder<U>, GroupStateTimeout) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
::Experimental:: (Java-specific) Applies the given function to each group of data, while maintaining a user-defined per-group state.
FlatMapGroupsWithStateFunction<K,V,S,R> - Interface in org.apache.spark.api.java.function
::Experimental:: Base interface for a map function used in org.apache.spark.sql.KeyValueGroupedDataset.flatMapGroupsWithState( FlatMapGroupsWithStateFunction, org.apache.spark.sql.streaming.OutputMode, org.apache.spark.sql.Encoder, org.apache.spark.sql.Encoder)
flatMapToDouble(DoubleFlatMapFunction<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results.
flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results.
flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream by applying a function to all elements of this DStream, and then flattening the results
flatMapValues(Function<V, Iterable<U>>) - Method in class org.apache.spark.api.java.JavaPairRDD
Pass each value in the key-value pair RDD through a flatMap function without changing the keys; this also retains the original RDD's partitioning.
flatMapValues(Function1<V, TraversableOnce<U>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Pass each value in the key-value pair RDD through a flatMap function without changing the keys; this also retains the original RDD's partitioning.
flatMapValues(Function<V, Iterable<U>>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying a flatmap function to the value of each key-value pairs in 'this' DStream without changing the key.
flatMapValues(Function1<V, TraversableOnce<U>>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying a flatmap function to the value of each key-value pairs in 'this' DStream without changing the key.
flatten(Column) - Static method in class org.apache.spark.sql.functions
Creates a single array from an array of arrays.
FLOAT() - Static method in class org.apache.spark.sql.Encoders
An encoder for nullable float type.
FloatAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.FloatAccumulatorParam$
Deprecated.
 
FloatParam - Class in org.apache.spark.ml.param
:: DeveloperApi :: Specialized version of Param[Float] for Java.
FloatParam(String, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.FloatParam
 
FloatParam(String, String, String) - Constructor for class org.apache.spark.ml.param.FloatParam
 
FloatParam(Identifiable, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.FloatParam
 
FloatParam(Identifiable, String, String) - Constructor for class org.apache.spark.ml.param.FloatParam
 
FloatType - Static variable in class org.apache.spark.sql.types.DataTypes
Gets the FloatType object.
FloatType - Class in org.apache.spark.sql.types
The data type representing Float values.
FloatType() - Constructor for class org.apache.spark.sql.types.FloatType
 
floor(Column) - Static method in class org.apache.spark.sql.functions
Computes the floor of the given value.
floor(String) - Static method in class org.apache.spark.sql.functions
Computes the floor of the given column.
floor() - Method in class org.apache.spark.sql.types.Decimal
 
floor(Duration) - Method in class org.apache.spark.streaming.Time
 
floor(Duration, Time) - Method in class org.apache.spark.streaming.Time
 
flush() - Method in class org.apache.spark.io.SnappyOutputStreamWrapper
 
flush() - Method in class org.apache.spark.serializer.SerializationStream
 
flush() - Method in class org.apache.spark.storage.TimeTrackingOutputStream
 
fMeasure(double, double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns f-measure for a given label (category)
fMeasure(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns f1-measure for a given label (category)
fMeasure() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Deprecated.
Use accuracy. Since 2.0.0.
fMeasureByLabel(double) - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns f-measure for each label (category).
fMeasureByLabel() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns f1-measure for each label (category).
fMeasureByThreshold() - Method in interface org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
Returns a dataframe with two fields (threshold, F-Measure) curve with beta = 1.0.
fMeasureByThreshold(double) - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
Returns the (threshold, F-Measure) curve.
fMeasureByThreshold() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
Returns the (threshold, F-Measure) curve with beta = 1.0.
fold(T, Function2<T, T, T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Aggregate the elements of each partition, and then the results for all the partitions, using a given associative function and a neutral "zero value".
fold(T, Function2<T, T, T>) - Method in class org.apache.spark.rdd.RDD
Aggregate the elements of each partition, and then the results for all the partitions, using a given associative function and a neutral "zero value".
foldByKey(V, Partitioner, Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
Merge the values for each key using an associative function and a neutral "zero value" which may be added to the result an arbitrary number of times, and must not change the result (e.g ., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
foldByKey(V, int, Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
Merge the values for each key using an associative function and a neutral "zero value" which may be added to the result an arbitrary number of times, and must not change the result (e.g ., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
foldByKey(V, Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
Merge the values for each key using an associative function and a neutral "zero value" which may be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
foldByKey(V, Partitioner, Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Merge the values for each key using an associative function and a neutral "zero value" which may be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
foldByKey(V, int, Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Merge the values for each key using an associative function and a neutral "zero value" which may be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
foldByKey(V, Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Merge the values for each key using an associative function and a neutral "zero value" which may be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
forceIndexLabel() - Method in interface org.apache.spark.ml.feature.RFormulaBase
Force to index label whether it is numeric or string type.
foreach(VoidFunction<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Applies a function f to all elements of this RDD.
foreach(Function1<T, BoxedUnit>) - Method in class org.apache.spark.rdd.RDD
Applies a function f to all elements of this RDD.
foreach(Function1<T, BoxedUnit>) - Method in class org.apache.spark.sql.Dataset
Applies a function f to all rows.
foreach(ForeachFunction<T>) - Method in class org.apache.spark.sql.Dataset
(Java-specific) Runs func on each element of this Dataset.
foreach(ForeachWriter<T>) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Sets the output of the streaming query to be processed using the provided writer object.
foreachActive(Function3<Object, Object, Object, BoxedUnit>) - Method in class org.apache.spark.ml.linalg.DenseMatrix
 
foreachActive(Function2<Object, Object, BoxedUnit>) - Method in class org.apache.spark.ml.linalg.DenseVector
 
foreachActive(Function3<Object, Object, Object, BoxedUnit>) - Method in interface org.apache.spark.ml.linalg.Matrix
Applies a function f to all the active elements of dense and sparse matrix.
foreachActive(Function3<Object, Object, Object, BoxedUnit>) - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
foreachActive(Function2<Object, Object, BoxedUnit>) - Method in class org.apache.spark.ml.linalg.SparseVector
 
foreachActive(Function2<Object, Object, BoxedUnit>) - Method in interface org.apache.spark.ml.linalg.Vector
Applies a function f to all the active elements of dense and sparse vector.
foreachActive(Function2<Object, Object, BoxedUnit>) - Method in class org.apache.spark.mllib.linalg.DenseVector
 
foreachActive(Function3<Object, Object, Object, BoxedUnit>) - Method in interface org.apache.spark.mllib.linalg.Matrix
Applies a function f to all the active elements of dense and sparse matrix.
foreachActive(Function2<Object, Object, BoxedUnit>) - Method in class org.apache.spark.mllib.linalg.SparseVector
 
foreachActive(Function2<Object, Object, BoxedUnit>) - Method in interface org.apache.spark.mllib.linalg.Vector
Applies a function f to all the active elements of dense and sparse vector.
foreachAsync(VoidFunction<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
The asynchronous version of the foreach action, which applies a function f to all the elements of this RDD.
foreachAsync(Function1<T, BoxedUnit>) - Method in class org.apache.spark.rdd.AsyncRDDActions
Applies a function f to all elements of this RDD.
foreachBatch(Function2<Dataset<T>, Object, BoxedUnit>) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
:: Experimental ::
foreachBatch(VoidFunction2<Dataset<T>, Long>) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
:: Experimental ::
ForeachFunction<T> - Interface in org.apache.spark.api.java.function
Base interface for a function used in Dataset's foreach function.
foreachPartition(VoidFunction<Iterator<T>>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Applies a function f to each partition of this RDD.
foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Method in class org.apache.spark.rdd.RDD
Applies a function f to each partition of this RDD.
foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Method in class org.apache.spark.sql.Dataset
Applies a function f to each partition of this Dataset.
foreachPartition(ForeachPartitionFunction<T>) - Method in class org.apache.spark.sql.Dataset
(Java-specific) Runs func on each partition of this Dataset.
foreachPartitionAsync(VoidFunction<Iterator<T>>) - Method in interface org.apache.spark.api.java.JavaRDDLike
The asynchronous version of the foreachPartition action, which applies a function f to each partition of this RDD.
foreachPartitionAsync(Function1<Iterator<T>, BoxedUnit>) - Method in class org.apache.spark.rdd.AsyncRDDActions
Applies a function f to each partition of this RDD.
ForeachPartitionFunction<T> - Interface in org.apache.spark.api.java.function
Base interface for a function used in Dataset's foreachPartition function.
foreachRDD(VoidFunction<R>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Apply a function to each RDD in this DStream.
foreachRDD(VoidFunction2<R, Time>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Apply a function to each RDD in this DStream.
foreachRDD(Function1<RDD<T>, BoxedUnit>) - Method in class org.apache.spark.streaming.dstream.DStream
Apply a function to each RDD in this DStream.
foreachRDD(Function2<RDD<T>, Time, BoxedUnit>) - Method in class org.apache.spark.streaming.dstream.DStream
Apply a function to each RDD in this DStream.
ForeachWriter<T> - Class in org.apache.spark.sql
The abstract class for writing custom logic to process data generated by a query.
ForeachWriter() - Constructor for class org.apache.spark.sql.ForeachWriter
 
format() - Method in class org.apache.spark.ml.clustering.InternalKMeansModelWriter
 
format() - Method in class org.apache.spark.ml.clustering.PMMLKMeansModelWriter
 
format() - Method in class org.apache.spark.ml.regression.InternalLinearRegressionModelWriter
 
format() - Method in class org.apache.spark.ml.regression.PMMLLinearRegressionModelWriter
 
format(String) - Method in class org.apache.spark.ml.util.GeneralMLWriter
Specifies the format of ML export (e.g.
format() - Method in interface org.apache.spark.ml.util.MLFormatRegister
The string that represents the format that this format provider uses.
format(String) - Method in class org.apache.spark.sql.DataFrameReader
Specifies the input data source format.
format(String) - Method in class org.apache.spark.sql.DataFrameWriter
Specifies the underlying output data source.
format(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Specifies the input data source format.
format(String) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Specifies the underlying output data source.
format_number(Column, int) - Static method in class org.apache.spark.sql.functions
Formats numeric column x to a format like '#,###,###.##', rounded to d decimal places with HALF_EVEN round mode, and returns the result as a string column.
format_string(String, Column...) - Static method in class org.apache.spark.sql.functions
Formats the arguments in printf-style and returns the result as a string column.
format_string(String, Seq<Column>) - Static method in class org.apache.spark.sql.functions
Formats the arguments in printf-style and returns the result as a string column.
formatBatchTime(long, long, boolean, TimeZone) - Static method in class org.apache.spark.streaming.ui.UIUtils
If batchInterval is less than 1 second, format batchTime with milliseconds.
formatDate(Date) - Static method in class org.apache.spark.ui.UIUtils
 
formatDate(long) - Static method in class org.apache.spark.ui.UIUtils
 
formatDuration(long) - Static method in class org.apache.spark.ui.UIUtils
 
formatDurationVerbose(long) - Static method in class org.apache.spark.ui.UIUtils
Generate a verbose human-readable string representing a duration such as "5 second 35 ms"
formatNumber(double) - Static method in class org.apache.spark.ui.UIUtils
Generate a human-readable string representing a number (e.g.
formatVersion() - Method in interface org.apache.spark.mllib.util.Saveable
Current version of model save/load format.
formula() - Method in interface org.apache.spark.ml.feature.RFormulaBase
R formula parameter.
forward(DenseMatrix<Object>, boolean) - Method in interface org.apache.spark.ml.ann.TopologyModel
Forward propagation
FPGrowth - Class in org.apache.spark.ml.fpm
:: Experimental :: A parallel FP-growth algorithm to mine frequent itemsets.
FPGrowth(String) - Constructor for class org.apache.spark.ml.fpm.FPGrowth
 
FPGrowth() - Constructor for class org.apache.spark.ml.fpm.FPGrowth
 
FPGrowth - Class in org.apache.spark.mllib.fpm
A parallel FP-growth algorithm to mine frequent itemsets.
FPGrowth() - Constructor for class org.apache.spark.mllib.fpm.FPGrowth
Constructs a default instance with default parameters {minSupport: 0.3, numPartitions: same as the input data}.
FPGrowth.FreqItemset<Item> - Class in org.apache.spark.mllib.fpm
Frequent itemset.
FPGrowthModel - Class in org.apache.spark.ml.fpm
:: Experimental :: Model fitted by FPGrowth.
FPGrowthModel<Item> - Class in org.apache.spark.mllib.fpm
Model trained by FPGrowth, which holds frequent itemsets.
FPGrowthModel(RDD<FPGrowth.FreqItemset<Item>>, Map<Item, Object>, ClassTag<Item>) - Constructor for class org.apache.spark.mllib.fpm.FPGrowthModel
 
FPGrowthModel(RDD<FPGrowth.FreqItemset<Item>>, ClassTag<Item>) - Constructor for class org.apache.spark.mllib.fpm.FPGrowthModel
 
FPGrowthModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.fpm
 
FPGrowthParams - Interface in org.apache.spark.ml.fpm
Common params for FPGrowth and FPGrowthModel
fpr() - Method in interface org.apache.spark.ml.feature.ChiSqSelectorParams
The highest p-value for features to be kept.
fpr() - Method in class org.apache.spark.mllib.feature.ChiSqSelector
 
freq() - Method in class org.apache.spark.mllib.fpm.FPGrowth.FreqItemset
 
freq() - Method in class org.apache.spark.mllib.fpm.PrefixSpan.FreqSequence
 
freqItems(String[], double) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Finding frequent items for columns, possibly with false positives.
freqItems(String[]) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Finding frequent items for columns, possibly with false positives.
freqItems(Seq<String>, double) - Method in class org.apache.spark.sql.DataFrameStatFunctions
(Scala-specific) Finding frequent items for columns, possibly with false positives.
freqItems(Seq<String>) - Method in class org.apache.spark.sql.DataFrameStatFunctions
(Scala-specific) Finding frequent items for columns, possibly with false positives.
FreqItemset(Object, long) - Constructor for class org.apache.spark.mllib.fpm.FPGrowth.FreqItemset
 
freqItemsets() - Method in class org.apache.spark.ml.fpm.FPGrowthModel
 
freqItemsets() - Method in class org.apache.spark.mllib.fpm.FPGrowthModel
 
FreqSequence(Object[], long) - Constructor for class org.apache.spark.mllib.fpm.PrefixSpan.FreqSequence
 
freqSequences() - Method in class org.apache.spark.mllib.fpm.PrefixSpanModel
 
from_json(Column, StructType, Map<String, String>) - Static method in class org.apache.spark.sql.functions
(Scala-specific) Parses a column containing a JSON string into a StructType with the specified schema.
from_json(Column, DataType, Map<String, String>) - Static method in class org.apache.spark.sql.functions
(Scala-specific) Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType with the specified schema.
from_json(Column, StructType, Map<String, String>) - Static method in class org.apache.spark.sql.functions
(Java-specific) Parses a column containing a JSON string into a StructType with the specified schema.
from_json(Column, DataType, Map<String, String>) - Static method in class org.apache.spark.sql.functions
(Java-specific) Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType with the specified schema.
from_json(Column, StructType) - Static method in class org.apache.spark.sql.functions
Parses a column containing a JSON string into a StructType with the specified schema.
from_json(Column, DataType) - Static method in class org.apache.spark.sql.functions
Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType with the specified schema.
from_json(Column, String, Map<String, String>) - Static method in class org.apache.spark.sql.functions
(Java-specific) Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType with the specified schema.
from_json(Column, String, Map<String, String>) - Static method in class org.apache.spark.sql.functions
(Scala-specific) Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType with the specified schema.
from_json(Column, Column) - Static method in class org.apache.spark.sql.functions
(Scala-specific) Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType of StructTypes with the specified schema.
from_json(Column, Column, Map<String, String>) - Static method in class org.apache.spark.sql.functions
(Java-specific) Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType of StructTypes with the specified schema.
from_unixtime(Column) - Static method in class org.apache.spark.sql.functions
Converts the number of seconds from unix epoch (1970-01-01 00:00:00 UTC) to a string representing the timestamp of that moment in the current system time zone in the yyyy-MM-dd HH:mm:ss format.
from_unixtime(Column, String) - Static method in class org.apache.spark.sql.functions
Converts the number of seconds from unix epoch (1970-01-01 00:00:00 UTC) to a string representing the timestamp of that moment in the current system time zone in the given format.
from_utc_timestamp(Column, String) - Static method in class org.apache.spark.sql.functions
Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a time in UTC, and renders that time as a timestamp in the given time zone.
from_utc_timestamp(Column, Column) - Static method in class org.apache.spark.sql.functions
Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a time in UTC, and renders that time as a timestamp in the given time zone.
fromCOO(int, int, Iterable<Tuple3<Object, Object, Object>>) - Static method in class org.apache.spark.ml.linalg.SparseMatrix
Generate a SparseMatrix from Coordinate List (COO) format.
fromCOO(int, int, Iterable<Tuple3<Object, Object, Object>>) - Static method in class org.apache.spark.mllib.linalg.SparseMatrix
Generate a SparseMatrix from Coordinate List (COO) format.
fromDDL(String) - Static method in class org.apache.spark.sql.types.DataType
 
fromDDL(String) - Static method in class org.apache.spark.sql.types.StructType
Creates StructType for a given DDL-formatted string, which is a comma separated list of field definitions, e.g., a INT, b STRING.
fromDecimal(Object) - Static method in class org.apache.spark.sql.types.Decimal
 
fromDStream(DStream<T>, ClassTag<T>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
Convert a scala DStream to a Java-friendly JavaDStream.
fromEdgePartitions(RDD<Tuple2<Object, EdgePartition<ED, VD>>>, VD, StorageLevel, StorageLevel, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
Create a graph from EdgePartitions, setting referenced vertices to defaultVertexAttr.
fromEdges(RDD<Edge<ED>>, ClassTag<ED>, ClassTag<VD>) - Static method in class org.apache.spark.graphx.EdgeRDD
Creates an EdgeRDD from a set of edges.
fromEdges(RDD<Edge<ED>>, VD, StorageLevel, StorageLevel, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.Graph
Construct a graph from a collection of edges.
fromEdges(EdgeRDD<?>, int, VD, ClassTag<VD>) - Static method in class org.apache.spark.graphx.VertexRDD
Constructs a VertexRDD containing all vertices referred to in edges.
fromEdgeTuples(RDD<Tuple2<Object, Object>>, VD, Option<PartitionStrategy>, StorageLevel, StorageLevel, ClassTag<VD>) - Static method in class org.apache.spark.graphx.Graph
Construct a graph from a collection of edges encoded as vertex id pairs.
fromExistingRDDs(VertexRDD<VD>, EdgeRDD<ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
Create a graph from a VertexRDD and an EdgeRDD with the same replicated vertex type as the vertices.
fromInputDStream(InputDStream<T>, ClassTag<T>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
Convert a scala InputDStream to a Java-friendly JavaInputDStream.
fromInputDStream(InputDStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
Convert a scala InputDStream of pairs to a Java-friendly JavaPairInputDStream.
fromInt(int) - Method in interface org.apache.spark.sql.types.Decimal.DecimalIsConflicted
 
fromJavaDStream(JavaDStream<Tuple2<K, V>>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
 
fromJavaRDD(JavaRDD<Tuple2<K, V>>) - Static method in class org.apache.spark.api.java.JavaPairRDD
Convert a JavaRDD of key-value pairs to JavaPairRDD.
fromJson(String) - Static method in class org.apache.spark.ml.linalg.JsonMatrixConverter
Parses the JSON representation of a Matrix into a Matrix.
fromJson(String) - Static method in class org.apache.spark.ml.linalg.JsonVectorConverter
Parses the JSON representation of a vector into a Vector.
fromJson(String) - Static method in class org.apache.spark.mllib.linalg.Vectors
Parses the JSON representation of a vector into a Vector.
fromJson(String) - Static method in class org.apache.spark.sql.types.DataType
 
fromJson(String) - Static method in class org.apache.spark.sql.types.Metadata
Creates a Metadata instance from JSON.
fromKinesisInitialPosition(InitialPositionInStream) - Static method in class org.apache.spark.streaming.kinesis.KinesisInitialPositions
Returns instance of [[KinesisInitialPosition]] based on the passed [[InitialPositionInStream]].
fromMetadata(Metadata) - Method in interface org.apache.spark.ml.attribute.AttributeFactory
Creates an Attribute from a Metadata instance.
fromML(DenseMatrix) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
Convert new linalg type to spark.mllib type.
fromML(DenseVector) - Static method in class org.apache.spark.mllib.linalg.DenseVector
Convert new linalg type to spark.mllib type.
fromML(Matrix) - Static method in class org.apache.spark.mllib.linalg.Matrices
Convert new linalg type to spark.mllib type.
fromML(SparseMatrix) - Static method in class org.apache.spark.mllib.linalg.SparseMatrix
Convert new linalg type to spark.mllib type.
fromML(SparseVector) - Static method in class org.apache.spark.mllib.linalg.SparseVector
Convert new linalg type to spark.mllib type.
fromML(Vector) - Static method in class org.apache.spark.mllib.linalg.Vectors
Convert new linalg type to spark.mllib type.
fromName(String) - Static method in class org.apache.spark.ml.attribute.AttributeType
Gets the AttributeType object from its name.
fromNullable(T) - Static method in class org.apache.spark.api.java.Optional
 
fromOld(Node, Map<Object, Object>) - Static method in class org.apache.spark.ml.tree.Node
Create a new Node from the old Node format, recursively creating child nodes as needed.
fromPairDStream(DStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
 
fromPairRDD(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.mllib.rdd.MLPairRDDFunctions
Implicit conversion from a pair RDD to MLPairRDDFunctions.
fromParams(GeneralizedLinearRegressionBase) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Family$
Gets the Family object based on param family and variancePower.
fromParams(GeneralizedLinearRegressionBase) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Link$
Gets the Link object based on param family, link and linkPower.
fromRDD(RDD<Object>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
 
fromRDD(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.api.java.JavaPairRDD
 
fromRDD(RDD<T>, ClassTag<T>) - Static method in class org.apache.spark.api.java.JavaRDD
 
fromRDD(RDD<T>, ClassTag<T>) - Static method in class org.apache.spark.mllib.rdd.RDDFunctions
Implicit conversion from an RDD to RDDFunctions.
fromRdd(RDD<?>) - Static method in class org.apache.spark.storage.RDDInfo
 
fromReceiverInputDStream(ReceiverInputDStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
Convert a scala ReceiverInputDStream to a Java-friendly JavaReceiverInputDStream.
fromReceiverInputDStream(ReceiverInputDStream<T>, ClassTag<T>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
Convert a scala ReceiverInputDStream to a Java-friendly JavaReceiverInputDStream.
fromSparkContext(SparkContext) - Static method in class org.apache.spark.api.java.JavaSparkContext
 
fromStage(Stage, int, Option<Object>, TaskMetrics, Seq<Seq<TaskLocation>>) - Static method in class org.apache.spark.scheduler.StageInfo
Construct a StageInfo from a Stage.
fromString(String) - Static method in enum org.apache.spark.JobExecutionStatus
 
fromString(String) - Static method in class org.apache.spark.mllib.tree.impurity.Impurities
 
fromString(String) - Static method in class org.apache.spark.mllib.tree.loss.Losses
 
fromString(String) - Static method in enum org.apache.spark.status.api.v1.ApplicationStatus
 
fromString(String) - Static method in enum org.apache.spark.status.api.v1.StageStatus
 
fromString(String) - Static method in enum org.apache.spark.status.api.v1.streaming.BatchStatus
 
fromString(String) - Static method in enum org.apache.spark.status.api.v1.TaskSorting
 
fromString(String) - Static method in class org.apache.spark.storage.StorageLevel
:: DeveloperApi :: Return the StorageLevel object with the specified name.
fromStructField(StructField) - Static method in class org.apache.spark.ml.attribute.Attribute
 
fromStructField(StructField) - Method in interface org.apache.spark.ml.attribute.AttributeFactory
Creates an Attribute from a StructField instance.
fromStructField(StructField) - Static method in class org.apache.spark.ml.attribute.AttributeGroup
Creates an attribute group from a StructField instance.
fromStructField(StructField) - Static method in class org.apache.spark.ml.attribute.BinaryAttribute
 
fromStructField(StructField) - Static method in class org.apache.spark.ml.attribute.NominalAttribute
 
fromStructField(StructField) - Static method in class org.apache.spark.ml.attribute.NumericAttribute
 
fullOuterJoin(JavaPairRDD<K, W>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
Perform a full outer join of this and other.
fullOuterJoin(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
Perform a full outer join of this and other.
fullOuterJoin(JavaPairRDD<K, W>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
Perform a full outer join of this and other.
fullOuterJoin(RDD<Tuple2<K, W>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
Perform a full outer join of this and other.
fullOuterJoin(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Perform a full outer join of this and other.
fullOuterJoin(RDD<Tuple2<K, W>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
Perform a full outer join of this and other.
fullOuterJoin(JavaPairDStream<K, W>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'full outer join' between RDDs of this DStream and other DStream.
fullOuterJoin(JavaPairDStream<K, W>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'full outer join' between RDDs of this DStream and other DStream.
fullOuterJoin(JavaPairDStream<K, W>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'full outer join' between RDDs of this DStream and other DStream.
fullOuterJoin(DStream<Tuple2<K, W>>, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'full outer join' between RDDs of this DStream and other DStream.
fullOuterJoin(DStream<Tuple2<K, W>>, int, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'full outer join' between RDDs of this DStream and other DStream.
fullOuterJoin(DStream<Tuple2<K, W>>, Partitioner, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'full outer join' between RDDs of this DStream and other DStream.
fullStackTrace() - Method in class org.apache.spark.ExceptionFailure
 
Function<T1,R> - Interface in org.apache.spark.api.java.function
Base interface for functions whose return types do not create special RDDs.
Function - Class in org.apache.spark.sql.catalog
A user-defined function in Spark, as returned by listFunctions method in Catalog.
Function(String, String, String, String, boolean) - Constructor for class org.apache.spark.sql.catalog.Function
 
function(Function4<Time, KeyType, Option<ValueType>, State<StateType>, Option<MappedType>>) - Static method in class org.apache.spark.streaming.StateSpec
Create a StateSpec for setting all the specifications of the mapWithState operation on a pair DStream.
function(Function3<KeyType, Option<ValueType>, State<StateType>, MappedType>) - Static method in class org.apache.spark.streaming.StateSpec
Create a StateSpec for setting all the specifications of the mapWithState operation on a pair DStream.
function(Function4<Time, KeyType, Optional<ValueType>, State<StateType>, Optional<MappedType>>) - Static method in class org.apache.spark.streaming.StateSpec
Create a StateSpec for setting all the specifications of the mapWithState operation on a JavaPairDStream.
function(Function3<KeyType, Optional<ValueType>, State<StateType>, MappedType>) - Static method in class org.apache.spark.streaming.StateSpec
Create a StateSpec for setting all the specifications of the mapWithState operation on a JavaPairDStream.
Function0<R> - Interface in org.apache.spark.api.java.function
A zero-argument function that returns an R.
Function2<T1,T2,R> - Interface in org.apache.spark.api.java.function
A two-argument function that takes arguments of type T1 and T2 and returns an R.
Function3<T1,T2,T3,R> - Interface in org.apache.spark.api.java.function
A three-argument function that takes arguments of type T1, T2 and T3 and returns an R.
Function4<T1,T2,T3,T4,R> - Interface in org.apache.spark.api.java.function
A four-argument function that takes arguments of type T1, T2, T3 and T4 and returns an R.
functionExists(String) - Method in class org.apache.spark.sql.catalog.Catalog
Check if the function with the specified name exists.
functionExists(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
Check if the function with the specified name exists in the specified database.
functionExists(String, String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Return whether a function exists in the specified database.
functions - Class in org.apache.spark.sql
Commonly used functions available for DataFrame operations.
functions() - Constructor for class org.apache.spark.sql.functions
 
FutureAction<T> - Interface in org.apache.spark
A future for the result of an action to support cancellation.
futureExecutionContext() - Static method in class org.apache.spark.rdd.AsyncRDDActions
 
fwe() - Method in interface org.apache.spark.ml.feature.ChiSqSelectorParams
The upper bound of the expected family-wise error rate.
fwe() - Method in class org.apache.spark.mllib.feature.ChiSqSelector
 

G

gain() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
 
gain() - Method in class org.apache.spark.ml.tree.InternalNode
 
gain() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
 
Gamma$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
 
gamma1() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
 
gamma2() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
 
gamma6() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
 
gamma7() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
 
GammaGenerator - Class in org.apache.spark.mllib.random
:: DeveloperApi :: Generates i.i.d.
GammaGenerator(double, double) - Constructor for class org.apache.spark.mllib.random.GammaGenerator
 
gammaJavaRDD(JavaSparkContext, double, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Java-friendly version of RandomRDDs.gammaRDD.
gammaJavaRDD(JavaSparkContext, double, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.gammaJavaRDD with the default seed.
gammaJavaRDD(JavaSparkContext, double, double, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.gammaJavaRDD with the default number of partitions and the default seed.
gammaJavaVectorRDD(JavaSparkContext, double, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Java-friendly version of RandomRDDs.gammaVectorRDD.
gammaJavaVectorRDD(JavaSparkContext, double, double, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.gammaJavaVectorRDD with the default seed.
gammaJavaVectorRDD(JavaSparkContext, double, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.gammaJavaVectorRDD with the default number of partitions and the default seed.
gammaRDD(SparkContext, double, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Generates an RDD comprised of i.i.d. samples from the gamma distribution with the input shape and scale.
gammaVectorRDD(SparkContext, double, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from the gamma distribution with the input shape and scale.
gapply(RelationalGroupedDataset, byte[], byte[], Object[], StructType) - Static method in class org.apache.spark.sql.api.r.SQLUtils
The helper function for gapply() on R side.
gaps() - Method in class org.apache.spark.ml.feature.RegexTokenizer
Indicates whether regex splits on gaps (true) or matches tokens (false).
GAUGE() - Static method in class org.apache.spark.metrics.sink.StatsdMetricType
 
Gaussian$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
 
GaussianMixture - Class in org.apache.spark.ml.clustering
Gaussian Mixture clustering.
GaussianMixture(String) - Constructor for class org.apache.spark.ml.clustering.GaussianMixture
 
GaussianMixture() - Constructor for class org.apache.spark.ml.clustering.GaussianMixture
 
GaussianMixture - Class in org.apache.spark.mllib.clustering
This class performs expectation maximization for multivariate Gaussian Mixture Models (GMMs).
GaussianMixture() - Constructor for class org.apache.spark.mllib.clustering.GaussianMixture
Constructs a default instance.
GaussianMixtureModel - Class in org.apache.spark.ml.clustering
Multivariate Gaussian Mixture Model (GMM) consisting of k Gaussians, where points are drawn from each Gaussian i with probability weights(i).
GaussianMixtureModel - Class in org.apache.spark.mllib.clustering
Multivariate Gaussian Mixture Model (GMM) consisting of k Gaussians, where points are drawn from each Gaussian i=1..k with probability w(i); mu(i) and sigma(i) are the respective mean and covariance for each Gaussian distribution i=1..k.
GaussianMixtureModel(double[], MultivariateGaussian[]) - Constructor for class org.apache.spark.mllib.clustering.GaussianMixtureModel
 
GaussianMixtureParams - Interface in org.apache.spark.ml.clustering
Common params for GaussianMixture and GaussianMixtureModel
GaussianMixtureSummary - Class in org.apache.spark.ml.clustering
:: Experimental :: Summary of GaussianMixture.
gaussians() - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
 
gaussians() - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
 
gaussiansDF() - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
Retrieve Gaussian distributions as a DataFrame.
GBTClassificationModel - Class in org.apache.spark.ml.classification
Gradient-Boosted Trees (GBTs) (http://en.wikipedia.org/wiki/Gradient_boosting) model for classification.
GBTClassificationModel(String, DecisionTreeRegressionModel[], double[]) - Constructor for class org.apache.spark.ml.classification.GBTClassificationModel
Construct a GBTClassificationModel
GBTClassifier - Class in org.apache.spark.ml.classification
Gradient-Boosted Trees (GBTs) (http://en.wikipedia.org/wiki/Gradient_boosting) learning algorithm for classification.
GBTClassifier(String) - Constructor for class org.apache.spark.ml.classification.GBTClassifier
 
GBTClassifier() - Constructor for class org.apache.spark.ml.classification.GBTClassifier
 
GBTClassifierParams - Interface in org.apache.spark.ml.tree
 
GBTParams - Interface in org.apache.spark.ml.tree
Parameters for Gradient-Boosted Tree algorithms.
GBTRegressionModel - Class in org.apache.spark.ml.regression
Gradient-Boosted Trees (GBTs) model for regression.
GBTRegressionModel(String, DecisionTreeRegressionModel[], double[]) - Constructor for class org.apache.spark.ml.regression.GBTRegressionModel
Construct a GBTRegressionModel
GBTRegressor - Class in org.apache.spark.ml.regression
Gradient-Boosted Trees (GBTs) learning algorithm for regression.
GBTRegressor(String) - Constructor for class org.apache.spark.ml.regression.GBTRegressor
 
GBTRegressor() - Constructor for class org.apache.spark.ml.regression.GBTRegressor
 
GBTRegressorParams - Interface in org.apache.spark.ml.tree
 
GC_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
 
GC_TIME() - Static method in class org.apache.spark.ui.ToolTips
 
gemm(double, Matrix, DenseMatrix, double, DenseMatrix) - Static method in class org.apache.spark.ml.linalg.BLAS
C := alpha * A * B + beta * C
gemm(double, Matrix, DenseMatrix, double, DenseMatrix) - Static method in class org.apache.spark.mllib.linalg.BLAS
C := alpha * A * B + beta * C
gemv(double, Matrix, Vector, double, DenseVector) - Static method in class org.apache.spark.ml.linalg.BLAS
y := alpha * A * x + beta * y
gemv(double, Matrix, Vector, double, DenseVector) - Static method in class org.apache.spark.mllib.linalg.BLAS
y := alpha * A * x + beta * y
GeneralizedLinearAlgorithm<M extends GeneralizedLinearModel> - Class in org.apache.spark.mllib.regression
:: DeveloperApi :: GeneralizedLinearAlgorithm implements methods to train a Generalized Linear Model (GLM).
GeneralizedLinearAlgorithm() - Constructor for class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
 
GeneralizedLinearModel - Class in org.apache.spark.mllib.regression
:: DeveloperApi :: GeneralizedLinearModel (GLM) represents a model trained using GeneralizedLinearAlgorithm.
GeneralizedLinearModel(Vector, double) - Constructor for class org.apache.spark.mllib.regression.GeneralizedLinearModel
 
GeneralizedLinearRegression - Class in org.apache.spark.ml.regression
:: Experimental ::
GeneralizedLinearRegression(String) - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression
 
GeneralizedLinearRegression() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression
 
GeneralizedLinearRegression.Binomial$ - Class in org.apache.spark.ml.regression
Binomial exponential family distribution.
GeneralizedLinearRegression.CLogLog$ - Class in org.apache.spark.ml.regression
 
GeneralizedLinearRegression.Family$ - Class in org.apache.spark.ml.regression
 
GeneralizedLinearRegression.FamilyAndLink$ - Class in org.apache.spark.ml.regression
 
GeneralizedLinearRegression.Gamma$ - Class in org.apache.spark.ml.regression
Gamma exponential family distribution.
GeneralizedLinearRegression.Gaussian$ - Class in org.apache.spark.ml.regression
Gaussian exponential family distribution.
GeneralizedLinearRegression.Identity$ - Class in org.apache.spark.ml.regression
 
GeneralizedLinearRegression.Inverse$ - Class in org.apache.spark.ml.regression
 
GeneralizedLinearRegression.Link$ - Class in org.apache.spark.ml.regression
 
GeneralizedLinearRegression.Log$ - Class in org.apache.spark.ml.regression
 
GeneralizedLinearRegression.Logit$ - Class in org.apache.spark.ml.regression
 
GeneralizedLinearRegression.Poisson$ - Class in org.apache.spark.ml.regression
Poisson exponential family distribution.
GeneralizedLinearRegression.Probit$ - Class in org.apache.spark.ml.regression
 
GeneralizedLinearRegression.Sqrt$ - Class in org.apache.spark.ml.regression
 
GeneralizedLinearRegression.Tweedie$ - Class in org.apache.spark.ml.regression
 
GeneralizedLinearRegressionBase - Interface in org.apache.spark.ml.regression
Params for Generalized Linear Regression.
GeneralizedLinearRegressionModel - Class in org.apache.spark.ml.regression
:: Experimental :: Model produced by GeneralizedLinearRegression.
GeneralizedLinearRegressionSummary - Class in org.apache.spark.ml.regression
:: Experimental :: Summary of GeneralizedLinearRegression model and predictions.
GeneralizedLinearRegressionTrainingSummary - Class in org.apache.spark.ml.regression
:: Experimental :: Summary of GeneralizedLinearRegression fitting and model.
GeneralMLWritable - Interface in org.apache.spark.ml.util
Trait for classes that provide GeneralMLWriter.
GeneralMLWriter - Class in org.apache.spark.ml.util
A ML Writer which delegates based on the requested format.
GeneralMLWriter(PipelineStage) - Constructor for class org.apache.spark.ml.util.GeneralMLWriter
 
generateAssociationRules(double) - Method in class org.apache.spark.mllib.fpm.FPGrowthModel
Generates association rules for the Items in freqItemsets.
generateKMeansRDD(SparkContext, int, int, int, double, int) - Static method in class org.apache.spark.mllib.util.KMeansDataGenerator
Generate an RDD containing test data for KMeans.
generateLinearInput(double, double[], int, int, double) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
For compatibility, the generated data without specifying the mean and variance will have zero mean and variance of (1.0/3.0) since the original output range is [-1, 1] with uniform distribution, and the variance of uniform distribution is (b - a)^2^ / 12 which will be (1.0/3.0)
generateLinearInput(double, double[], double[], double[], int, int, double) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
 
generateLinearInput(double, double[], double[], double[], int, int, double, double) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
 
generateLinearInputAsList(double, double[], int, int, double) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
Return a Java List of synthetic data randomly generated according to a multi collinear model.
generateLinearRDD(SparkContext, int, int, double, int, double) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
Generate an RDD containing sample data for Linear Regression models - including Ridge, Lasso, and unregularized variants.
generateLogisticRDD(SparkContext, int, int, double, int, double) - Static method in class org.apache.spark.mllib.util.LogisticRegressionDataGenerator
Generate an RDD containing test data for LogisticRegression.
generateRandomEdges(int, int, int, long) - Static method in class org.apache.spark.graphx.util.GraphGenerators
 
generateRolledOverFileSuffix() - Method in interface org.apache.spark.util.logging.RollingPolicy
Get the desired name of the rollover file
geq(Object) - Method in class org.apache.spark.sql.Column
Greater than or equal to an expression.
get(Object) - Method in class org.apache.spark.api.java.JavaUtils.SerializableMapWrapper
 
get() - Method in class org.apache.spark.api.java.Optional
 
get() - Static method in class org.apache.spark.BarrierTaskContext
:: Experimental :: Returns the currently active BarrierTaskContext.
get() - Method in interface org.apache.spark.FutureAction
Blocks and returns the result of this job.
get(String) - Method in interface org.apache.spark.internal.config.ConfigProvider
 
get(Param<T>) - Method in class org.apache.spark.ml.param.ParamMap
Optionally returns the value associated with a param.
get(Param<T>) - Method in interface org.apache.spark.ml.param.Params
Optionally returns the user-supplied value of a param.
get(String) - Method in class org.apache.spark.SparkConf
Get a parameter; throws a NoSuchElementException if it's not set
get(String, String) - Method in class org.apache.spark.SparkConf
Get a parameter, falling back to a default if not set
get() - Static method in class org.apache.spark.SparkEnv
Returns the SparkEnv.
get(String) - Static method in class org.apache.spark.SparkFiles
Get the absolute path of a file added through SparkContext.addFile().
get(String) - Static method in class org.apache.spark.sql.jdbc.JdbcDialects
Fetch the JdbcDialect class corresponding to a given database url.
get(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i.
get(String) - Method in class org.apache.spark.sql.RuntimeConfig
Returns the value of Spark runtime configuration property for the given key.
get(String, String) - Method in class org.apache.spark.sql.RuntimeConfig
Returns the value of Spark runtime configuration property for the given key.
get(String) - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
Returns the option value to which the specified key is mapped, case-insensitively.
get() - Method in interface org.apache.spark.sql.sources.v2.reader.InputPartitionReader
Return the current record.
get() - Method in interface org.apache.spark.sql.streaming.GroupState
Get the state value if it exists, or throw NoSuchElementException.
get(UUID) - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
Returns the query if there is an active query with the given id, or null.
get(String) - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
Returns the query if there is an active query with the given id, or null.
get(int, DataType) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
get(int, DataType) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
get() - Method in class org.apache.spark.streaming.State
Get the state if it exists, otherwise it will throw java.util.NoSuchElementException.
get() - Static method in class org.apache.spark.TaskContext
Return the currently active TaskContext.
get(long) - Static method in class org.apache.spark.util.AccumulatorContext
Returns the AccumulatorV2 registered with the given ID, if any.
get_json_object(Column, String) - Static method in class org.apache.spark.sql.functions
Extracts json object from a json string based on json path specified, and returns json string of the extracted json object.
getAcceptanceResults(RDD<Tuple2<K, V>>, boolean, Map<K, Object>, Option<Map<K, Object>>, long) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
Count the number of items instantly accepted and generate the waitlist for each stratum.
getActive() - Static method in class org.apache.spark.streaming.StreamingContext
:: Experimental ::
getActiveJobIds() - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
Returns an array containing the ids of all active jobs.
getActiveJobIds() - Method in class org.apache.spark.SparkStatusTracker
Returns an array containing the ids of all active jobs.
getActiveOrCreate(Function0<StreamingContext>) - Static method in class org.apache.spark.streaming.StreamingContext
:: Experimental ::
getActiveOrCreate(String, Function0<StreamingContext>, Configuration, boolean) - Static method in class org.apache.spark.streaming.StreamingContext
:: Experimental ::
getActiveSession() - Static method in class org.apache.spark.sql.SparkSession
Returns the active SparkSession for the current thread, returned by the builder.
getActiveStageIds() - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
Returns an array containing the ids of all active stages.
getActiveStageIds() - Method in class org.apache.spark.SparkStatusTracker
Returns an array containing the ids of all active stages.
getAggregationDepth() - Method in interface org.apache.spark.ml.param.shared.HasAggregationDepth
 
getAlgo() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
getAll() - Method in class org.apache.spark.SparkConf
Get all parameters as a list of pairs
getAll() - Method in class org.apache.spark.sql.RuntimeConfig
Returns all properties set in this conf.
getAllConfs() - Method in class org.apache.spark.sql.SQLContext
Return all the configuration properties that have been set (i.e.
getAllPools() - Method in class org.apache.spark.SparkContext
:: DeveloperApi :: Return pools for fair scheduler
getAllPrefLocs(RDD<?>) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer.PartitionLocations
 
GetAllReceiverInfo - Class in org.apache.spark.streaming.scheduler
 
GetAllReceiverInfo() - Constructor for class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
 
getAllWithPrefix(String) - Method in class org.apache.spark.SparkConf
Get all parameters that start with prefix
getAlpha() - Method in interface org.apache.spark.ml.recommendation.ALSParams
 
getAlpha() - Method in class org.apache.spark.mllib.clustering.LDA
Alias for getDocConcentration
getAnyValAs(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i.
getAppId() - Method in interface org.apache.spark.launcher.SparkAppHandle
Returns the application ID, or null if not yet known.
getAppId() - Method in class org.apache.spark.SparkConf
Returns the Spark application id, valid in the Driver after TaskScheduler registration and from the start in the Executor.
getApplicationInfo(String) - Method in interface org.apache.spark.status.api.v1.UIRoot
 
getApplicationInfoList() - Method in interface org.apache.spark.status.api.v1.UIRoot
 
getArray(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
getArray(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getArray(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getArray(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the array type value for rowId.
getAs(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i.
getAs(String) - Method in interface org.apache.spark.sql.Row
Returns the value of a given fieldName.
getAssociationRulesFromFP(Dataset<?>, String, String, double, Map<T, Object>, ClassTag<T>) - Static method in class org.apache.spark.ml.fpm.AssociationRules
Computes the association rules with confidence above minConfidence.
getAsymmetricAlpha() - Method in class org.apache.spark.mllib.clustering.LDA
Alias for getAsymmetricDocConcentration
getAsymmetricDocConcentration() - Method in class org.apache.spark.mllib.clustering.LDA
Concentration parameter (commonly named "alpha") for the prior placed on documents' distributions over topics ("theta").
getAttr(String) - Method in class org.apache.spark.ml.attribute.AttributeGroup
Gets an attribute by its name.
getAttr(int) - Method in class org.apache.spark.ml.attribute.AttributeGroup
Gets an attribute by its index.
getAvroSchema() - Method in class org.apache.spark.SparkConf
Gets all the avro schemas in the configuration used in the generic Avro record serializer
getBatchingTimeout(SparkConf) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
How long we will wait for the wrappedLog in the BatchedWriteAheadLog to write the records before we fail the write attempt to unblock receivers.
getBernoulliSamplingFunction(RDD<Tuple2<K, V>>, Map<K, Object>, boolean, long) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
Return the per partition sampling function used for sampling without replacement.
getBeta() - Method in class org.apache.spark.mllib.clustering.LDA
Alias for getTopicConcentration
getBinary() - Method in interface org.apache.spark.ml.feature.CountVectorizerParams
 
getBinary() - Method in class org.apache.spark.ml.feature.HashingTF
 
getBinary(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
getBinary(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getBinary(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getBinary(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the binary type value for rowId.
getBinaryWritable(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getBinaryWritableConstantObjectInspector(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getBlockSize() - Method in interface org.apache.spark.ml.classification.MultilayerPerceptronParams
 
GetBlockStatus(BlockId, boolean) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetBlockStatus
 
GetBlockStatus$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetBlockStatus$
 
getBoolean(String, boolean) - Method in class org.apache.spark.SparkConf
Get a parameter as a boolean, falling back to a default if not set
getBoolean(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i as a primitive boolean.
getBoolean(String, boolean) - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
Returns the boolean value to which the specified key is mapped, or defaultValue if there is no mapping for the key.
getBoolean(String) - Method in class org.apache.spark.sql.types.Metadata
Gets a Boolean.
getBoolean(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
getBoolean(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getBoolean(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getBoolean(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the boolean type value for rowId.
getBooleanArray(String) - Method in class org.apache.spark.sql.types.Metadata
Gets a Boolean array.
getBooleans(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Gets boolean type values from [rowId, rowId + count).
getBooleanWritable(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getBooleanWritableConstantObjectInspector(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getBucketLength() - Method in interface org.apache.spark.ml.feature.BucketedRandomProjectionLSHParams
 
getBuilder() - Method in class org.apache.spark.storage.memory.DeserializedValuesHolder
 
getBuilder() - Method in class org.apache.spark.storage.memory.SerializedValuesHolder
 
getBuilder() - Method in interface org.apache.spark.storage.memory.ValuesHolder
Note: After this method is called, the ValuesHolder is invalid, we can't store data and get estimate size again.
getByte(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i as a primitive byte.
getByte(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
getByte(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getByte(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getByte(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the byte type value for rowId.
getBytes(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Gets byte type values from [rowId, rowId + count).
getByteWritable(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getByteWritableConstantObjectInspector(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getCachedBlockManagerId(BlockManagerId) - Static method in class org.apache.spark.storage.BlockManagerId
 
getCachedMetadata(String) - Static method in class org.apache.spark.rdd.HadoopRDD
The three methods below are helpers for accessing the local map, a property of the SparkEnv of the local process.
getCacheNodeIds() - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
 
getCallSite(Function1<String, Object>) - Static method in class org.apache.spark.util.Utils
When called inside a class in the spark package, returns the name of the user code class (outside the spark package) that called into Spark, as well as which Spark method they called.
getCaseSensitive() - Method in class org.apache.spark.ml.feature.StopWordsRemover
 
getCatalystType(int, String, int, MetadataBuilder) - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
 
getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
 
getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
 
getCatalystType(int, String, int, MetadataBuilder) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
Get the custom datatype mapping for the given jdbc meta information.
getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
 
getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
 
getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
 
getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
getCategoricalCols() - Method in class org.apache.spark.ml.feature.FeatureHasher
 
getCategoricalFeatures(StructField) - Static method in class org.apache.spark.ml.util.MetadataUtils
Examine a schema to identify categorical (Binary and Nominal) features.
getCategoricalFeaturesInfo() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
getCensorCol() - Method in interface org.apache.spark.ml.regression.AFTSurvivalRegressionParams
 
getCheckpointDir() - Method in class org.apache.spark.api.java.JavaSparkContext
 
getCheckpointDir() - Method in class org.apache.spark.SparkContext
 
getCheckpointFile() - Method in interface org.apache.spark.api.java.JavaRDDLike
Gets the name of the file to which this RDD was checkpointed
getCheckpointFile() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
getCheckpointFile() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
getCheckpointFile() - Method in class org.apache.spark.rdd.RDD
Gets the name of the directory to which this RDD was checkpointed.
getCheckpointFiles() - Method in class org.apache.spark.graphx.Graph
Gets the name of the files to which this Graph was checkpointed.
getCheckpointFiles() - Method in class org.apache.spark.graphx.impl.GraphImpl
 
getCheckpointFiles() - Method in class org.apache.spark.ml.clustering.DistributedLDAModel
:: DeveloperApi ::
getCheckpointInterval() - Method in interface org.apache.spark.ml.param.shared.HasCheckpointInterval
 
getCheckpointInterval() - Method in class org.apache.spark.mllib.clustering.LDA
Period (in iterations) between checkpoints.
getCheckpointInterval() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
getChild(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
getClassifier() - Method in interface org.apache.spark.ml.classification.OneVsRestParams
 
getColdStartStrategy() - Method in interface org.apache.spark.ml.recommendation.ALSModelParams
 
getCollectSubModels() - Method in interface org.apache.spark.ml.param.shared.HasCollectSubModels
 
getCombOp() - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
Returns the function used combine results returned by seqOp from different partitions.
getComment() - Method in class org.apache.spark.sql.types.StructField
Return the comment of this StructField.
getConf() - Method in class org.apache.spark.api.java.JavaSparkContext
Return a copy of this JavaSparkContext's configuration.
getConf() - Method in interface org.apache.spark.input.Configurable
 
getConf() - Method in class org.apache.spark.rdd.HadoopRDD
 
getConf() - Method in class org.apache.spark.rdd.NewHadoopRDD
 
getConf() - Method in class org.apache.spark.SparkContext
Return a copy of this SparkContext's configuration.
getConf(String, String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns the configuration for the given key in the current session.
getConf(String) - Method in class org.apache.spark.sql.SQLContext
Return the value of Spark SQL configuration property for the given key.
getConf(String, String) - Method in class org.apache.spark.sql.SQLContext
Return the value of Spark SQL configuration property for the given key.
getConfiguration() - Method in class org.apache.spark.input.PortableDataStream
 
getConfiguredLocalDirs(SparkConf) - Static method in class org.apache.spark.util.Utils
Return the configured local directories where Spark can write files.
getConnection() - Method in interface org.apache.spark.rdd.JdbcRDD.ConnectionFactory
 
getContextOrSparkClassLoader() - Static method in class org.apache.spark.util.Utils
Get the Context ClassLoader on this thread or, if not present, the ClassLoader that loaded Spark.
getConvergenceTol() - Method in class org.apache.spark.mllib.clustering.GaussianMixture
Return the largest change in log-likelihood at which convergence is considered to have occurred.
getCorrelationFromName(String) - Static method in class org.apache.spark.mllib.stat.correlation.Correlations
 
getCount() - Method in class org.apache.spark.storage.CountingWritableChannel
 
getCurrentProcessingTimeMs() - Method in interface org.apache.spark.sql.streaming.GroupState
Get the current processing time as milliseconds in epoch time.
getCurrentUserGroups(SparkConf, String) - Static method in class org.apache.spark.util.Utils
 
getCurrentUserName() - Static method in class org.apache.spark.util.Utils
Returns the current user name.
getCurrentWatermarkMs() - Method in interface org.apache.spark.sql.streaming.GroupState
Get the current event time watermark as milliseconds in epoch time.
getData(Row) - Static method in class org.apache.spark.ml.image.ImageSchema
Gets the image data
getDatabase(String) - Method in class org.apache.spark.sql.catalog.Catalog
Get the database with the specified name.
getDatabase(String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns the metadata for specified database, throwing an exception if it doesn't exist
getDate(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i of date type as java.sql.Date.
getDateWritable(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getDateWritableConstantObjectInspector(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getDecimal(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i of decimal type as java.math.BigDecimal.
getDecimal(int, int, int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
getDecimal(int, int, int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getDecimal(int, int, int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getDecimal(int, int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the decimal type value for rowId.
getDecimalWritable(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getDecimalWritableConstantObjectInspector(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getDefault(Param<T>) - Method in interface org.apache.spark.ml.param.Params
Gets the default value of a parameter.
getDefaultPropertiesFile(Map<String, String>) - Static method in class org.apache.spark.util.Utils
Return the path of the default Spark properties file.
getDefaultSession() - Static method in class org.apache.spark.sql.SparkSession
Returns the default SparkSession that is returned by the builder.
getDegree() - Method in class org.apache.spark.ml.feature.PolynomialExpansion
 
getDenseSizeInBytes() - Method in interface org.apache.spark.ml.linalg.Matrix
Gets the size of the dense representation of this `Matrix`.
getDependencies() - Method in class org.apache.spark.rdd.CoGroupedRDD
 
getDependencies() - Method in class org.apache.spark.rdd.ShuffledRDD
 
getDependencies() - Method in class org.apache.spark.rdd.UnionRDD
 
getDeprecatedConfig(String, Map<String, String>) - Static method in class org.apache.spark.SparkConf
Looks for available deprecated keys for the given config option, and return the first value available.
getDistanceMeasure() - Method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
getDistanceMeasure() - Method in interface org.apache.spark.ml.param.shared.HasDistanceMeasure
 
getDistanceMeasure() - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
The distance suite used by the algorithm.
getDistanceMeasure() - Method in class org.apache.spark.mllib.clustering.KMeans
The distance suite used by the algorithm.
getDistributions() - Method in class org.apache.spark.status.LiveRDD
 
getDocConcentration() - Method in interface org.apache.spark.ml.clustering.LDAParams
 
getDocConcentration() - Method in class org.apache.spark.mllib.clustering.LDA
Concentration parameter (commonly named "alpha") for the prior placed on documents' distributions over topics ("theta").
getDouble(String, double) - Method in class org.apache.spark.SparkConf
Get a parameter as a double, falling back to a default if not ste
getDouble(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i as a primitive double.
getDouble(String, double) - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
Returns the double value to which the specified key is mapped, or defaultValue if there is no mapping for the key.
getDouble(String) - Method in class org.apache.spark.sql.types.Metadata
Gets a Double.
getDouble(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
getDouble(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getDouble(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getDouble(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the double type value for rowId.
getDoubleArray(String) - Method in class org.apache.spark.sql.types.Metadata
Gets a Double array.
getDoubles(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Gets double type values from [rowId, rowId + count).
getDoubleWritable(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getDoubleWritableConstantObjectInspector(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getDriverLogUrls() - Method in interface org.apache.spark.scheduler.SchedulerBackend
Get the URLs for the driver logs.
getDropLast() - Method in class org.apache.spark.ml.feature.OneHotEncoder
Deprecated.
 
getDropLast() - Method in interface org.apache.spark.ml.feature.OneHotEncoderBase
 
getDstCol() - Method in interface org.apache.spark.ml.clustering.PowerIterationClusteringParams
 
getDynamicAllocationInitialExecutors(SparkConf) - Static method in class org.apache.spark.util.Utils
Return the initial number of executors for dynamic allocation.
getElasticNetParam() - Method in interface org.apache.spark.ml.param.shared.HasElasticNetParam
 
getEncryptionEnabled(JavaSparkContext) - Static method in class org.apache.spark.api.r.RUtils
 
getEndOffset() - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.MicroBatchReader
Return the specified (if explicitly set through setOffsetRange) or inferred end offset for this reader.
getEndTimeEpoch() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
 
getEpsilon() - Method in interface org.apache.spark.ml.regression.LinearRegressionParams
 
getEpsilon() - Method in class org.apache.spark.mllib.clustering.KMeans
The distance threshold within which we've consider centers to have converged.
getEstimator() - Method in interface org.apache.spark.ml.tuning.ValidatorParams
 
getEstimatorParamMaps() - Method in interface org.apache.spark.ml.tuning.ValidatorParams
 
getEvaluator() - Method in interface org.apache.spark.ml.tuning.ValidatorParams
 
getExecutionContext() - Method in interface org.apache.spark.ml.param.shared.HasParallelism
Create a new execution context with a thread-pool that has a maximum number of threads set to the value of parallelism.
GetExecutorEndpointRef(String) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetExecutorEndpointRef
 
GetExecutorEndpointRef$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetExecutorEndpointRef$
 
getExecutorEnv() - Method in class org.apache.spark.SparkConf
Get all executor environment variables set on this SparkConf
getExecutorIds() - Method in interface org.apache.spark.ExecutorAllocationClient
Get the list of currently active executors
getExecutorInfos() - Method in class org.apache.spark.SparkStatusTracker
Returns information of all known executors, including host, port, cacheSize, numRunningTasks and memory metrics.
GetExecutorLossReason(String) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.GetExecutorLossReason
 
GetExecutorLossReason$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.GetExecutorLossReason$
 
getExecutorMemoryStatus() - Method in class org.apache.spark.SparkContext
Return a map from the slave to the max memory available for caching and the remaining memory available for caching.
getExternalScratchDir(URI, Configuration, String) - Method in interface org.apache.spark.sql.hive.execution.SaveAsHiveFile
 
getExternalTmpPath(SparkSession, Configuration, Path) - Method in interface org.apache.spark.sql.hive.execution.SaveAsHiveFile
 
getExtTmpPathRelTo(Path, Configuration, String) - Method in interface org.apache.spark.sql.hive.execution.SaveAsHiveFile
 
getFamily() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
 
getFamily() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
 
getFdr() - Method in interface org.apache.spark.ml.feature.ChiSqSelectorParams
 
getFeatureIndex() - Method in interface org.apache.spark.ml.regression.IsotonicRegressionBase
 
getFeatureIndicesFromNames(StructField, String[]) - Static method in class org.apache.spark.ml.util.MetadataUtils
Takes a Vector column and a list of feature names, and returns the corresponding list of feature indices in the column, in order.
getFeaturesAndLabels(RFormulaModel, Dataset<?>) - Static method in class org.apache.spark.ml.r.RWrapperUtils
Get the feature names and original labels from the schema of DataFrame transformed by RFormulaModel.
getFeaturesCol() - Method in interface org.apache.spark.ml.param.shared.HasFeaturesCol
 
getFeatureSubsetStrategy() - Method in interface org.apache.spark.ml.tree.TreeEnsembleParams
 
getField(String) - Method in class org.apache.spark.sql.Column
An expression that gets a field by name in a StructType.
getFileLength(File, SparkConf) - Static method in class org.apache.spark.util.Utils
Return the file length, if the file is compressed it returns the uncompressed file length.
getFileReader(String, Option<Configuration>, boolean) - Static method in class org.apache.spark.sql.hive.orc.OrcFileOperator
Retrieves an ORC file reader from a given path.
getFileSegmentLocations(String, long, long, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
Get the locations of the HDFS blocks containing the given file segment.
getFileSystemForPath(Path, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
 
getFinalStorageLevel() - Method in interface org.apache.spark.ml.recommendation.ALSParams
 
getFinalValue() - Method in class org.apache.spark.partial.PartialResult
Blocking method to wait for and return the final value.
getFitIntercept() - Method in interface org.apache.spark.ml.param.shared.HasFitIntercept
 
getFloat(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i as a primitive float.
getFloat(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
getFloat(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getFloat(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getFloat(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the float type value for rowId.
getFloats(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Gets float type values from [rowId, rowId + count).
getFloatWritable(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getFloatWritableConstantObjectInspector(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getForceIndexLabel() - Method in interface org.apache.spark.ml.feature.RFormulaBase
 
getFormattedClassName(Object) - Static method in class org.apache.spark.util.Utils
Return the class name of the given object, removing all dollar signs
getFormula() - Method in interface org.apache.spark.ml.feature.RFormulaBase
 
getFpr() - Method in interface org.apache.spark.ml.feature.ChiSqSelectorParams
 
getFunction(String) - Method in class org.apache.spark.sql.catalog.Catalog
Get the function with the specified name.
getFunction(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
Get the function with the specified name.
getFunction(String, String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Return an existing function in the database, assuming it exists.
getFunctionOption(String, String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Return an existing function in the database, or None if it doesn't exist.
getFwe() - Method in interface org.apache.spark.ml.feature.ChiSqSelectorParams
 
getGaps() - Method in class org.apache.spark.ml.feature.RegexTokenizer
 
getGroups(String) - Method in interface org.apache.spark.security.GroupMappingServiceProvider
Get the groups the user belongs to.
getHadoopFileSystem(URI, Configuration) - Static method in class org.apache.spark.util.Utils
Return a Hadoop FileSystem with the scheme encoded in the given path.
getHadoopFileSystem(String, Configuration) - Static method in class org.apache.spark.util.Utils
Return a Hadoop FileSystem with the scheme encoded in the given path.
getHandleInvalid() - Method in interface org.apache.spark.ml.param.shared.HasHandleInvalid
 
getHeight(Row) - Static method in class org.apache.spark.ml.image.ImageSchema
Gets the height of the image
getHiveWriteCompression(TableDesc, SQLConf) - Static method in class org.apache.spark.sql.hive.execution.HiveOptions
 
getImplicitPrefs() - Method in interface org.apache.spark.ml.recommendation.ALSParams
 
getImpurity() - Method in interface org.apache.spark.ml.tree.TreeClassifierParams
 
getImpurity() - Method in interface org.apache.spark.ml.tree.TreeRegressorParams
 
getImpurity() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
getIndices() - Method in class org.apache.spark.ml.feature.VectorSlicer
 
getInitializationMode() - Method in class org.apache.spark.mllib.clustering.KMeans
The initialization algorithm.
getInitializationSteps() - Method in class org.apache.spark.mllib.clustering.KMeans
Number of steps for the k-means|| initialization mode
getInitialModel() - Method in class org.apache.spark.mllib.clustering.GaussianMixture
Return the user supplied initial GMM, if supplied
getInitialPositionInStream(int) - Method in class org.apache.spark.streaming.kinesis.KinesisUtilsPythonHelper
 
getInitialTargetExecutorNumber(SparkConf, int) - Static method in class org.apache.spark.scheduler.cluster.SchedulerBackendUtils
Getting the initial target number of executors depends on whether dynamic allocation is enabled.
getInitialWeights() - Method in interface org.apache.spark.ml.classification.MultilayerPerceptronParams
 
getInitMode() - Method in interface org.apache.spark.ml.clustering.KMeansParams
 
getInitMode() - Method in interface org.apache.spark.ml.clustering.PowerIterationClusteringParams
 
getInitSteps() - Method in interface org.apache.spark.ml.clustering.KMeansParams
 
getInputCol() - Method in interface org.apache.spark.ml.param.shared.HasInputCol
 
getInputCols() - Method in interface org.apache.spark.ml.param.shared.HasInputCols
 
getInputFilePath() - Static method in class org.apache.spark.rdd.InputFileBlockHolder
Returns the holding file name or empty string if it is unknown.
getInputStream(String, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
 
getInt(String, int) - Method in class org.apache.spark.SparkConf
Get a parameter as an integer, falling back to a default if not set
getInt(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i as a primitive int.
getInt(String, int) - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
Returns the integer value to which the specified key is mapped, or defaultValue if there is no mapping for the key.
getInt(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
getInt(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getInt(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getInt(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the int type value for rowId.
getIntermediateStorageLevel() - Method in interface org.apache.spark.ml.recommendation.ALSParams
 
getInterval(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getInterval(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getInterval(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the calendar interval type value for rowId.
getInts(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Gets int type values from [rowId, rowId + count).
getIntWritable(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getIntWritableConstantObjectInspector(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getInverse() - Method in class org.apache.spark.ml.feature.DCT
 
getIsotonic() - Method in interface org.apache.spark.ml.regression.IsotonicRegressionBase
 
getItem(Object) - Method in class org.apache.spark.sql.Column
An expression that gets an item at position ordinal out of an array, or gets a value by key key in a MapType.
getItemCol() - Method in interface org.apache.spark.ml.recommendation.ALSModelParams
 
getItemsCol() - Method in interface org.apache.spark.ml.fpm.FPGrowthParams
 
getIteratorSize(Iterator<?>) - Static method in class org.apache.spark.util.Utils
Counts the number of elements of an iterator using a while loop rather than calling TraversableOnce.size() because it uses a for loop, which is slightly slower in the current version of Scala.
getIteratorZipWithIndex(Iterator<T>, long) - Static method in class org.apache.spark.util.Utils
Generate a zipWithIndex iterator, avoid index value overflowing problem in scala's zipWithIndex
getJavaMap(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i of array type as a java.util.Map.
getJavaSparkContext(SparkSession) - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
getJDBCType(DataType) - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
 
getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
 
getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
 
getJDBCType(DataType) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
Retrieve the jdbc / sql type for a given datatype.
getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
 
getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
 
getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
 
getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
getJobIdsForGroup(String) - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
Return a list of all known jobs in a particular job group.
getJobIdsForGroup(String) - Method in class org.apache.spark.SparkStatusTracker
Return a list of all known jobs in a particular job group.
getJobInfo(int) - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
Returns job information, or null if the job info could not be found or was garbage collected.
getJobInfo(int) - Method in class org.apache.spark.SparkStatusTracker
Returns job information, or None if the job info could not be found or was garbage collected.
getK() - Method in interface org.apache.spark.ml.clustering.BisectingKMeansParams
 
getK() - Method in interface org.apache.spark.ml.clustering.GaussianMixtureParams
 
getK() - Method in interface org.apache.spark.ml.clustering.KMeansParams
 
getK() - Method in interface org.apache.spark.ml.clustering.LDAParams
 
getK() - Method in interface org.apache.spark.ml.clustering.PowerIterationClusteringParams
 
getK() - Method in interface org.apache.spark.ml.feature.PCAParams
 
getK() - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
Gets the desired number of leaf clusters.
getK() - Method in class org.apache.spark.mllib.clustering.GaussianMixture
Return the number of Gaussians in the mixture model
getK() - Method in class org.apache.spark.mllib.clustering.KMeans
Number of clusters to create (k).
getK() - Method in class org.apache.spark.mllib.clustering.LDA
Number of topics to infer, i.e., the number of soft cluster centers.
getKappa() - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
Learning rate: exponential decay rate
getKeepLastCheckpoint() - Method in interface org.apache.spark.ml.clustering.LDAParams
 
getKeepLastCheckpoint() - Method in class org.apache.spark.mllib.clustering.EMLDAOptimizer
If using checkpointing, this indicates whether to keep the last checkpoint (vs clean up).
getLabelCol() - Method in interface org.apache.spark.ml.param.shared.HasLabelCol
 
getLabels() - Method in class org.apache.spark.ml.feature.IndexToString
 
getLambda() - Method in class org.apache.spark.mllib.classification.NaiveBayes
Get the smoothing parameter.
getLastUpdatedEpoch() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
 
getLayers() - Method in interface org.apache.spark.ml.classification.MultilayerPerceptronParams
 
getLDAModel(double[]) - Method in interface org.apache.spark.mllib.clustering.LDAOptimizer
 
getLearningDecay() - Method in interface org.apache.spark.ml.clustering.LDAParams
 
getLearningOffset() - Method in interface org.apache.spark.ml.clustering.LDAParams
 
getLearningRate() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
getLeastGroupHash(String) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
Sorts and gets the least element of the list associated with key in groupHash The returned PartitionGroup is the least loaded of all groups that represent the machine "key"
getLength() - Static method in class org.apache.spark.rdd.InputFileBlockHolder
Returns the length of the block being read, or -1 if it is unknown.
getLink() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
 
getLinkPower() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
 
getLinkPredictionCol() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
 
getList(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i of array type as java.util.List.
getLocalDir(SparkConf) - Static method in class org.apache.spark.util.Utils
Get the path of a temporary directory.
getLocale() - Method in class org.apache.spark.ml.feature.StopWordsRemover
 
getLocalProperty(String) - Method in class org.apache.spark.api.java.JavaSparkContext
Get a local property set in this thread, or null if it is missing.
getLocalProperty(String) - Method in class org.apache.spark.BarrierTaskContext
 
getLocalProperty(String) - Method in class org.apache.spark.SparkContext
Get a local property set in this thread, or null if it is missing.
getLocalProperty(String) - Method in class org.apache.spark.TaskContext
Get a local property set upstream in the driver, or null if it is missing.
getLocalUserJarsForShell(SparkConf) - Static method in class org.apache.spark.util.Utils
Return the local jar files which will be added to REPL's classpath.
GetLocations(BlockId) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetLocations
 
GetLocations$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetLocations$
 
GetLocationsAndStatus(BlockId) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetLocationsAndStatus
 
GetLocationsAndStatus$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetLocationsAndStatus$
 
GetLocationsMultipleBlockIds(BlockId[]) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetLocationsMultipleBlockIds
 
GetLocationsMultipleBlockIds$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetLocationsMultipleBlockIds$
 
getLong(String, long) - Method in class org.apache.spark.SparkConf
Get a parameter as a long, falling back to a default if not set
getLong(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i as a primitive long.
getLong(String, long) - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
Returns the long value to which the specified key is mapped, or defaultValue if there is no mapping for the key.
getLong(String) - Method in class org.apache.spark.sql.types.Metadata
Gets a Long.
getLong(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
getLong(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getLong(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getLong(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the long type value for rowId.
getLongArray(String) - Method in class org.apache.spark.sql.types.Metadata
Gets a Long array.
getLongs(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Gets long type values from [rowId, rowId + count).
getLongWritable(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getLongWritableConstantObjectInspector(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getLoss() - Method in interface org.apache.spark.ml.param.shared.HasLoss
 
getLoss() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
getLossType() - Method in interface org.apache.spark.ml.tree.GBTClassifierParams
 
getLossType() - Method in interface org.apache.spark.ml.tree.GBTRegressorParams
 
getLowerBound(double, long, double) - Static method in class org.apache.spark.util.random.BinomialBounds
Returns a threshold p such that if we conduct n Bernoulli trials with success rate = p, it is very unlikely to have more than fraction * n successes.
getLowerBound(double) - Static method in class org.apache.spark.util.random.PoissonBounds
Returns a lambda such that Pr[X > s] is very small, where X ~ Pois(lambda).
getLowerBoundsOnCoefficients() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
 
getLowerBoundsOnIntercepts() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
 
getMap(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i of map type as a Scala Map.
getMap(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
getMap(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getMap(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getMap(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the map type value for rowId.
GetMatchingBlockIds(Function1<BlockId, Object>, boolean) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetMatchingBlockIds
 
GetMatchingBlockIds$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetMatchingBlockIds$
 
getMax() - Method in interface org.apache.spark.ml.feature.MinMaxScalerParams
 
getMaxBins() - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
 
getMaxBins() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
getMaxCategories() - Method in interface org.apache.spark.ml.feature.VectorIndexerParams
 
getMaxDepth() - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
 
getMaxDepth() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
getMaxDF() - Method in interface org.apache.spark.ml.feature.CountVectorizerParams
 
getMaxFailures(SparkConf, boolean) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
getMaxIter() - Method in interface org.apache.spark.ml.param.shared.HasMaxIter
 
getMaxIterations() - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
Gets the max number of k-means iterations to split clusters.
getMaxIterations() - Method in class org.apache.spark.mllib.clustering.GaussianMixture
Return the maximum number of iterations allowed
getMaxIterations() - Method in class org.apache.spark.mllib.clustering.KMeans
Maximum number of iterations allowed.
getMaxIterations() - Method in class org.apache.spark.mllib.clustering.LDA
Maximum number of iterations allowed.
getMaxLocalProjDBSize() - Method in class org.apache.spark.ml.fpm.PrefixSpan
 
getMaxLocalProjDBSize() - Method in class org.apache.spark.mllib.fpm.PrefixSpan
Gets the maximum number of items allowed in a projected database before local processing.
getMaxMemoryInMB() - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
 
getMaxMemoryInMB() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
getMaxPatternLength() - Method in class org.apache.spark.ml.fpm.PrefixSpan
 
getMaxPatternLength() - Method in class org.apache.spark.mllib.fpm.PrefixSpan
Gets the maximal pattern length (i.e.
getMaxSentenceLength() - Method in interface org.apache.spark.ml.feature.Word2VecBase
 
GetMemoryStatus$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetMemoryStatus$
 
getMessage() - Method in exception org.apache.spark.sql.AnalysisException
 
getMetadata(String) - Method in class org.apache.spark.sql.types.Metadata
Gets a Metadata.
getMetadataArray(String) - Method in class org.apache.spark.sql.types.Metadata
Gets a Metadata array.
getMetricName() - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
 
getMetricName() - Method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
getMetricName() - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
 
getMetricName() - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
 
getMetricsSources(String) - Method in class org.apache.spark.BarrierTaskContext
 
getMetricsSources(String) - Method in class org.apache.spark.TaskContext
::DeveloperApi:: Returns all metrics sources with the given name which are associated with the instance which runs the task.
getMin() - Method in interface org.apache.spark.ml.feature.MinMaxScalerParams
 
getMinConfidence() - Method in interface org.apache.spark.ml.fpm.FPGrowthParams
 
getMinCount() - Method in interface org.apache.spark.ml.feature.Word2VecBase
 
getMinDF() - Method in interface org.apache.spark.ml.feature.CountVectorizerParams
 
getMinDivisibleClusterSize() - Method in interface org.apache.spark.ml.clustering.BisectingKMeansParams
 
getMinDivisibleClusterSize() - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
Gets the minimum number of points (if greater than or equal to 1.0) or the minimum proportion of points (if less than 1.0) of a divisible cluster.
getMinDocFreq() - Method in interface org.apache.spark.ml.feature.IDFBase
 
getMiniBatchFraction() - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
Mini-batch fraction, which sets the fraction of document sampled and used in each iteration
getMinInfoGain() - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
 
getMinInfoGain() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
getMinInstancesPerNode() - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
 
getMinInstancesPerNode() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
getMinSupport() - Method in interface org.apache.spark.ml.fpm.FPGrowthParams
 
getMinSupport() - Method in class org.apache.spark.ml.fpm.PrefixSpan
 
getMinSupport() - Method in class org.apache.spark.mllib.fpm.PrefixSpan
Get the minimal support (i.e.
getMinTF() - Method in interface org.apache.spark.ml.feature.CountVectorizerParams
 
getMinTokenLength() - Method in class org.apache.spark.ml.feature.RegexTokenizer
 
getMissingValue() - Method in interface org.apache.spark.ml.feature.ImputerParams
 
getMode(Row) - Static method in class org.apache.spark.ml.image.ImageSchema
Gets the OpenCV representation as an int
getModelType() - Method in interface org.apache.spark.ml.classification.NaiveBayesParams
 
getModelType() - Method in class org.apache.spark.mllib.classification.NaiveBayes
Get the model type.
getN() - Method in class org.apache.spark.ml.feature.NGram
 
getNames() - Method in class org.apache.spark.ml.feature.VectorSlicer
 
getNChannels(Row) - Static method in class org.apache.spark.ml.image.ImageSchema
Gets the number of channels in the image
getNode(int, Node) - Static method in class org.apache.spark.mllib.tree.model.Node
Traces down from a root node to get the node with the given node index.
getNonnegative() - Method in interface org.apache.spark.ml.recommendation.ALSParams
 
getNumBuckets() - Method in interface org.apache.spark.ml.feature.QuantileDiscretizerBase
 
getNumBucketsArray() - Method in interface org.apache.spark.ml.feature.QuantileDiscretizerBase
 
getNumClasses(StructField) - Static method in class org.apache.spark.ml.util.MetadataUtils
Examine a schema to identify the number of classes in a label column.
getNumClasses() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
getNumFeatures() - Method in class org.apache.spark.ml.feature.FeatureHasher
 
getNumFeatures() - Method in class org.apache.spark.ml.feature.HashingTF
 
getNumFeatures() - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
The dimension of training features.
getNumFolds() - Method in interface org.apache.spark.ml.tuning.CrossValidatorParams
 
getNumHashTables() - Method in interface org.apache.spark.ml.feature.LSHParams
 
getNumItemBlocks() - Method in interface org.apache.spark.ml.recommendation.ALSParams
 
getNumIterations() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
getNumObjFields() - Method in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
 
getNumPartitions() - Method in interface org.apache.spark.api.java.JavaRDDLike
Return the number of partitions in this RDD.
getNumPartitions() - Method in interface org.apache.spark.ml.feature.Word2VecBase
 
getNumPartitions() - Method in interface org.apache.spark.ml.fpm.FPGrowthParams
 
getNumPartitions() - Method in class org.apache.spark.rdd.RDD
Returns the number of partitions of this RDD.
getNumTopFeatures() - Method in interface org.apache.spark.ml.feature.ChiSqSelectorParams
 
getNumTrees() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
Number of trees in ensemble
getNumTrees() - Method in class org.apache.spark.ml.regression.GBTRegressionModel
Number of trees in ensemble
getNumTrees() - Method in interface org.apache.spark.ml.tree.RandomForestParams
 
getNumUserBlocks() - Method in interface org.apache.spark.ml.recommendation.ALSParams
 
getNumValues() - Method in class org.apache.spark.ml.attribute.NominalAttribute
Get the number of values, either from numValues or from values.
getObjectInspector(String, Option<Configuration>) - Static method in class org.apache.spark.sql.hive.orc.OrcFileOperator
 
getObjFieldValues(Object, Object[]) - Method in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
 
getOffset() - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.ContinuousInputPartitionReader
Get the offset of the current record, or the start offset if no records have been read.
getOffsetCol() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
 
getOldBoostingStrategy(Map<Object, Object>, Enumeration.Value) - Method in interface org.apache.spark.ml.tree.GBTParams
(private[ml]) Create a BoostingStrategy instance to use with the old API.
getOldDocConcentration() - Method in interface org.apache.spark.ml.clustering.LDAParams
Get docConcentration used by spark.mllib LDA
getOldImpurity() - Method in interface org.apache.spark.ml.tree.TreeClassifierParams
Convert new impurity to old impurity.
getOldImpurity() - Method in interface org.apache.spark.ml.tree.TreeRegressorParams
Convert new impurity to old impurity.
getOldLossType() - Method in interface org.apache.spark.ml.tree.GBTClassifierParams
(private[ml]) Convert new loss to old loss.
getOldLossType() - Method in interface org.apache.spark.ml.tree.GBTParams
Get old Gradient Boosting Loss type
getOldLossType() - Method in interface org.apache.spark.ml.tree.GBTRegressorParams
(private[ml]) Convert new loss to old loss.
getOldOptimizer() - Method in interface org.apache.spark.ml.clustering.LDAParams
 
getOldStrategy(Map<Object, Object>, int, Enumeration.Value, Impurity, double) - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
(private[ml]) Create a Strategy instance to use with the old API.
getOldStrategy(Map<Object, Object>, int, Enumeration.Value, Impurity) - Method in interface org.apache.spark.ml.tree.TreeEnsembleParams
Create a Strategy instance to use with the old API.
getOldTopicConcentration() - Method in interface org.apache.spark.ml.clustering.LDAParams
Get topicConcentration used by spark.mllib LDA
getOptimizeDocConcentration() - Method in interface org.apache.spark.ml.clustering.LDAParams
 
getOptimizeDocConcentration() - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
Optimize docConcentration, indicates whether docConcentration (Dirichlet parameter for document-topic distribution) will be optimized during training.
getOptimizer() - Method in interface org.apache.spark.ml.clustering.LDAParams
 
getOptimizer() - Method in class org.apache.spark.mllib.clustering.LDA
:: DeveloperApi ::
getOption(String) - Method in class org.apache.spark.SparkConf
Get a parameter as an Option
getOption(String) - Method in class org.apache.spark.sql.RuntimeConfig
Returns the value of Spark runtime configuration property for the given key.
getOption() - Method in interface org.apache.spark.sql.streaming.GroupState
Get the state value as a scala Option.
getOption() - Method in class org.apache.spark.streaming.State
Get the state as a scala.Option.
getOrCreate(SparkConf) - Static method in class org.apache.spark.SparkContext
This function may be used to get or instantiate a SparkContext and register it as a singleton object.
getOrCreate() - Static method in class org.apache.spark.SparkContext
This function may be used to get or instantiate a SparkContext and register it as a singleton object.
getOrCreate() - Method in class org.apache.spark.sql.SparkSession.Builder
Gets an existing SparkSession or, if there is no existing one, creates a new one based on the options set in this builder.
getOrCreate(SparkContext) - Static method in class org.apache.spark.sql.SQLContext
Deprecated.
Use SparkSession.builder instead. Since 2.0.0.
getOrCreate(String, Function0<JavaStreamingContext>) - Static method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Either recreate a StreamingContext from checkpoint data or create a new StreamingContext.
getOrCreate(String, Function0<JavaStreamingContext>, Configuration) - Static method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Either recreate a StreamingContext from checkpoint data or create a new StreamingContext.
getOrCreate(String, Function0<JavaStreamingContext>, Configuration, boolean) - Static method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Either recreate a StreamingContext from checkpoint data or create a new StreamingContext.
getOrCreate(String, Function0<StreamingContext>, Configuration, boolean) - Static method in class org.apache.spark.streaming.StreamingContext
Either recreate a StreamingContext from checkpoint data or create a new StreamingContext.
getOrCreateSparkSession(JavaSparkContext, Map<Object, Object>, boolean) - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
getOrDefault(Param<T>) - Method in interface org.apache.spark.ml.param.Params
Gets the value of a param in the embedded param map or its default value.
getOrElse(Param<T>, T) - Method in class org.apache.spark.ml.param.ParamMap
Returns the value associated with a param or a default value.
getOrigin(Row) - Static method in class org.apache.spark.ml.image.ImageSchema
Gets the origin of the image
getOutputAttrGroupFromData(Dataset<?>, Seq<String>, Seq<String>, boolean) - Static method in class org.apache.spark.ml.feature.OneHotEncoderCommon
This method is called when we want to generate AttributeGroup from actual data for one-hot encoder.
getOutputCol() - Method in interface org.apache.spark.ml.param.shared.HasOutputCol
 
getOutputCols() - Method in interface org.apache.spark.ml.param.shared.HasOutputCols
 
getOutputSize(int) - Method in interface org.apache.spark.ml.ann.Layer
Returns the output size given the input size (not counting the stack size).
getOutputStream(String, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
 
getP() - Method in class org.apache.spark.ml.feature.Normalizer
 
getParallelism() - Method in interface org.apache.spark.ml.param.shared.HasParallelism
 
getParam(String) - Method in interface org.apache.spark.ml.param.Params
Gets a param by its name.
getParents(int) - Method in class org.apache.spark.NarrowDependency
Get the parent partitions for a child partition.
getParents(int) - Method in class org.apache.spark.OneToOneDependency
 
getParents(int) - Method in class org.apache.spark.RangeDependency
 
getPartition(long, long, int) - Method in class org.apache.spark.graphx.PartitionStrategy.CanonicalRandomVertexCut$
 
getPartition(long, long, int) - Method in class org.apache.spark.graphx.PartitionStrategy.EdgePartition1D$
 
getPartition(long, long, int) - Method in class org.apache.spark.graphx.PartitionStrategy.EdgePartition2D$
 
getPartition(long, long, int) - Method in interface org.apache.spark.graphx.PartitionStrategy
Returns the partition number for a given edge.
getPartition(long, long, int) - Method in class org.apache.spark.graphx.PartitionStrategy.RandomVertexCut$
 
getPartition(Object) - Method in class org.apache.spark.HashPartitioner
 
getPartition(Object) - Method in class org.apache.spark.Partitioner
 
getPartition(Object) - Method in class org.apache.spark.RangePartitioner
 
getPartition(String, String, Map<String, String>) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns the specified partition, or throws `NoSuchPartitionException`.
getPartitionId() - Static method in class org.apache.spark.TaskContext
Returns the partition id of currently active TaskContext.
getPartitionNames(CatalogTable, Option<Map<String, String>>) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns the partition names for the given table that match the supplied partition spec.
getPartitionOption(String, String, Map<String, String>) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns the specified partition or None if it does not exist.
getPartitionOption(CatalogTable, Map<String, String>) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns the specified partition or None if it does not exist.
getPartitions() - Method in class org.apache.spark.api.r.BaseRRDD
 
getPartitions() - Method in class org.apache.spark.rdd.CoGroupedRDD
 
getPartitions() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
 
getPartitions() - Method in class org.apache.spark.rdd.HadoopRDD
 
getPartitions() - Method in class org.apache.spark.rdd.JdbcRDD
 
getPartitions() - Method in class org.apache.spark.rdd.NewHadoopRDD
 
getPartitions() - Method in class org.apache.spark.rdd.ShuffledRDD
 
getPartitions() - Method in class org.apache.spark.rdd.UnionRDD
 
getPartitions(String, String, Option<Map<String, String>>) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns the partitions for the given table that match the supplied partition spec.
getPartitions(CatalogTable, Option<Map<String, String>>) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns the partitions for the given table that match the supplied partition spec.
getPartitions() - Method in class org.apache.spark.status.LiveRDD
 
getPartitionsByFilter(CatalogTable, Seq<Expression>) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns partitions filtered by predicates for the given table.
getPath() - Method in class org.apache.spark.input.PortableDataStream
 
getPattern() - Method in class org.apache.spark.ml.feature.RegexTokenizer
 
GetPeers(BlockManagerId) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetPeers
 
GetPeers$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetPeers$
 
getPercentile() - Method in interface org.apache.spark.ml.feature.ChiSqSelectorParams
 
getPersistentRDDs() - Method in class org.apache.spark.api.java.JavaSparkContext
Returns a Java map of JavaRDDs that have marked themselves as persistent via cache() call.
getPersistentRDDs() - Method in class org.apache.spark.SparkContext
Returns an immutable map of RDDs that have marked themselves as persistent via cache() call.
getPmml() - Method in interface org.apache.spark.mllib.pmml.export.PMMLModelExport
 
getPoissonSamplingFunction(RDD<Tuple2<K, V>>, Map<K, Object>, boolean, long, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
Return the per partition sampling function used for sampling with replacement.
getPoolForName(String) - Method in class org.apache.spark.SparkContext
:: DeveloperApi :: Return the pool associated with the given name, if one exists
getPosition() - Method in class org.apache.spark.streaming.kinesis.KinesisInitialPositions.AtTimestamp
 
getPosition() - Method in class org.apache.spark.streaming.kinesis.KinesisInitialPositions.Latest
 
getPosition() - Method in class org.apache.spark.streaming.kinesis.KinesisInitialPositions.TrimHorizon
 
getPredictionCol() - Method in interface org.apache.spark.ml.param.shared.HasPredictionCol
 
getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.HadoopRDD
 
getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.NewHadoopRDD
 
getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.UnionRDD
 
getPrimitiveNullWritableConstantObjectInspector() - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getProbabilityCol() - Method in interface org.apache.spark.ml.param.shared.HasProbabilityCol
 
getProcessName() - Static method in class org.apache.spark.util.Utils
Returns the name of this JVM process.
getPropertiesFromFile(String) - Static method in class org.apache.spark.util.Utils
Load properties present in the given file.
getQuantileCalculationStrategy() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
getQuantileProbabilities() - Method in interface org.apache.spark.ml.regression.AFTSurvivalRegressionParams
 
getQuantilesCol() - Method in interface org.apache.spark.ml.regression.AFTSurvivalRegressionParams
 
getRandomSample(Seq<T>, int, Random) - Static method in class org.apache.spark.storage.BlockReplicationUtils
Get a random sample of size m from the elems
getRank() - Method in interface org.apache.spark.ml.recommendation.ALSParams
 
getRatingCol() - Method in interface org.apache.spark.ml.recommendation.ALSParams
 
getRawPredictionCol() - Method in interface org.apache.spark.ml.param.shared.HasRawPredictionCol
 
getRDDStorageInfo() - Method in class org.apache.spark.SparkContext
:: DeveloperApi :: Return information about what RDDs are cached, if they are in mem or on disk, how much space they take, etc.
getReceiver() - Method in class org.apache.spark.streaming.dstream.ReceiverInputDStream
Gets the receiver object that will be sent to the worker nodes to receive data.
getRegParam() - Method in interface org.apache.spark.ml.param.shared.HasRegParam
 
getRelativeError() - Method in interface org.apache.spark.ml.feature.QuantileDiscretizerBase
 
getResource(String) - Method in class org.apache.spark.util.ChildFirstURLClassLoader
 
getResources(String) - Method in class org.apache.spark.util.ChildFirstURLClassLoader
 
getRollingIntervalSecs(SparkConf, boolean) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
getRootDirectory() - Static method in class org.apache.spark.SparkFiles
Get the root directory that contains files added through SparkContext.addFile().
getRow(int) - Method in class org.apache.spark.sql.vectorized.ColumnarBatch
Returns the row in this batch at `rowId`.
getRuns() - Method in class org.apache.spark.mllib.clustering.KMeans
Deprecated.
This has no effect and always returns 1. Since 2.1.0.
getScalingVec() - Method in class org.apache.spark.ml.feature.ElementwiseProduct
 
getSchedulableByName(String) - Method in interface org.apache.spark.scheduler.Schedulable
 
getSchedulingMode() - Method in class org.apache.spark.SparkContext
Return current scheduling mode
getSchemaQuery(String) - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
 
getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
 
getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
 
getSchemaQuery(String) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
The SQL query that should be used to discover the schema of a table.
getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
 
getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
 
getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
 
getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
getSeed() - Method in interface org.apache.spark.ml.param.shared.HasSeed
 
getSeed() - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
Gets the random seed.
getSeed() - Method in class org.apache.spark.mllib.clustering.GaussianMixture
Return the random seed
getSeed() - Method in class org.apache.spark.mllib.clustering.KMeans
The random seed for cluster initialization.
getSeed() - Method in class org.apache.spark.mllib.clustering.LDA
Random seed for cluster initialization.
getSeed() - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
Random seed for cluster initialization.
getSelectorType() - Method in interface org.apache.spark.ml.feature.ChiSqSelectorParams
 
getSeq(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i of array type as a Scala Seq.
getSeqOp(boolean, Map<K, Object>, org.apache.spark.util.random.StratifiedSamplingUtils.RandomDataGenerator, Option<Map<K, Object>>) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
Returns the function used by aggregate to collect sampling statistics for each partition.
getSequenceCol() - Method in class org.apache.spark.ml.fpm.PrefixSpan
 
getSessionConf(SparkSession) - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
getShort(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i as a primitive short.
getShort(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
getShort(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getShort(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getShort(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the short type value for rowId.
getShorts(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Gets short type values from [rowId, rowId + count).
getShortWritable(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getShortWritableConstantObjectInspector(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getSimpleMessage() - Method in exception org.apache.spark.sql.AnalysisException
 
getSimpleName(Class<?>) - Static method in class org.apache.spark.util.Utils
Safer than Class obj's getSimpleName which may throw Malformed class name error in scala.
getSize() - Method in class org.apache.spark.ml.feature.VectorSizeHint
group getParam
getSizeAsBytes(String) - Method in class org.apache.spark.SparkConf
Get a size parameter as bytes; throws a NoSuchElementException if it's not set.
getSizeAsBytes(String, String) - Method in class org.apache.spark.SparkConf
Get a size parameter as bytes, falling back to a default if not set.
getSizeAsBytes(String, long) - Method in class org.apache.spark.SparkConf
Get a size parameter as bytes, falling back to a default if not set.
getSizeAsGb(String) - Method in class org.apache.spark.SparkConf
Get a size parameter as Gibibytes; throws a NoSuchElementException if it's not set.
getSizeAsGb(String, String) - Method in class org.apache.spark.SparkConf
Get a size parameter as Gibibytes, falling back to a default if not set.
getSizeAsKb(String) - Method in class org.apache.spark.SparkConf
Get a size parameter as Kibibytes; throws a NoSuchElementException if it's not set.
getSizeAsKb(String, String) - Method in class org.apache.spark.SparkConf
Get a size parameter as Kibibytes, falling back to a default if not set.
getSizeAsMb(String) - Method in class org.apache.spark.SparkConf
Get a size parameter as Mebibytes; throws a NoSuchElementException if it's not set.
getSizeAsMb(String, String) - Method in class org.apache.spark.SparkConf
Get a size parameter as Mebibytes, falling back to a default if not set.
getSizeForBlock(int) - Method in interface org.apache.spark.scheduler.MapStatus
Estimated size for the reduce block, in bytes.
getSizeInBytes() - Method in interface org.apache.spark.ml.linalg.Matrix
Gets the current size in bytes of this `Matrix`.
getSlotDescs() - Method in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
 
getSmoothing() - Method in interface org.apache.spark.ml.classification.NaiveBayesParams
 
getSolver() - Method in interface org.apache.spark.ml.param.shared.HasSolver
 
getSortedTaskSetQueue() - Method in interface org.apache.spark.scheduler.Schedulable
 
getSparkClassLoader() - Static method in class org.apache.spark.util.Utils
Get the ClassLoader which loaded Spark.
getSparkHome() - Method in class org.apache.spark.api.java.JavaSparkContext
Get Spark's home location from either a value set through the constructor, or the spark.home Java property, or the SPARK_HOME environment variable (in that order of preference).
getSparkOrYarnConfig(SparkConf, String, String) - Static method in class org.apache.spark.util.Utils
Return the value of a config either through the SparkConf or the Hadoop configuration.
getSparseSizeInBytes(boolean) - Method in interface org.apache.spark.ml.linalg.Matrix
Gets the size of the minimal sparse representation of this `Matrix`.
getSplit() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData
 
getSplits() - Method in class org.apache.spark.ml.feature.Bucketizer
 
getSplitsArray() - Method in class org.apache.spark.ml.feature.Bucketizer
 
getSrcCol() - Method in interface org.apache.spark.ml.clustering.PowerIterationClusteringParams
 
getStageInfo(int) - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
Returns stage information, or null if the stage info could not be found or was garbage collected.
getStageInfo(int) - Method in class org.apache.spark.SparkStatusTracker
Returns stage information, or None if the stage info could not be found or was garbage collected.
getStagePath(String, int, int, String) - Method in class org.apache.spark.ml.Pipeline.SharedReadWrite$
Get path for saving the given stage.
getStages() - Method in class org.apache.spark.ml.Pipeline
 
getStagingDir(Path, Configuration, String) - Method in interface org.apache.spark.sql.hive.execution.SaveAsHiveFile
 
getStandardization() - Method in interface org.apache.spark.ml.param.shared.HasStandardization
 
getStartOffset() - Static method in class org.apache.spark.rdd.InputFileBlockHolder
Returns the starting offset of the block currently being read, or -1 if it is unknown.
getStartOffset() - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.ContinuousReader
Return the specified or inferred start offset for this reader.
getStartOffset() - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.MicroBatchReader
Returns the specified (if explicitly set through setOffsetRange) or inferred start offset for this reader.
getStartTimeEpoch() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
 
getState() - Method in interface org.apache.spark.launcher.SparkAppHandle
Returns the current application state.
getState() - Method in interface org.apache.spark.sql.hive.client.HiveClient
Return the associated Hive SessionState of this HiveClientImpl
getState() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
:: DeveloperApi ::
getState() - Method in class org.apache.spark.streaming.StreamingContext
:: DeveloperApi ::
getStatement() - Method in class org.apache.spark.ml.feature.SQLTransformer
 
getStderr(Process, long) - Static method in class org.apache.spark.util.Utils
Return the stderr of a process after waiting for the process to terminate.
getStepSize() - Method in interface org.apache.spark.ml.param.shared.HasStepSize
 
getStopWords() - Method in class org.apache.spark.ml.feature.StopWordsRemover
 
getStorageLevel() - Method in interface org.apache.spark.api.java.JavaRDDLike
Get the RDD's current storage level, or StorageLevel.NONE if none is set.
getStorageLevel() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
getStorageLevel() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
getStorageLevel() - Method in class org.apache.spark.rdd.RDD
Get the RDD's current storage level, or StorageLevel.NONE if none is set.
GetStorageStatus$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetStorageStatus$
 
getStrategy() - Method in interface org.apache.spark.ml.feature.ImputerParams
 
getString(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i as a String object.
getString(String) - Method in class org.apache.spark.sql.types.Metadata
Gets a String.
getStringArray(String) - Method in class org.apache.spark.sql.types.Metadata
Gets a String array.
getStringIndexerOrderType() - Method in interface org.apache.spark.ml.feature.RFormulaBase
 
getStringOrderType() - Method in interface org.apache.spark.ml.feature.StringIndexerBase
 
getStringWritable(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getStringWritableConstantObjectInspector(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getStruct(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i of struct type as a Row object.
getStruct(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getStruct(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getStruct(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the struct type value for rowId.
getSubsamplingRate() - Method in interface org.apache.spark.ml.clustering.LDAParams
 
getSubsamplingRate() - Method in interface org.apache.spark.ml.tree.TreeEnsembleParams
 
getSubsamplingRate() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
getSystemProperties() - Static method in class org.apache.spark.util.Utils
Returns the system properties map that is thread-safe to iterator over.
getTable(String) - Method in class org.apache.spark.sql.catalog.Catalog
Get the table or view with the specified name.
getTable(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
Get the table or view with the specified name in the specified database.
getTable(String, String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns the specified table, or throws `NoSuchTableException`.
getTableExistsQuery(String) - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
 
getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
 
getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
 
getTableExistsQuery(String) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
Get the SQL query that should be used to find if the given table exists.
getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
 
getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
 
getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
 
getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
getTableNames(SparkSession, String) - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
getTableOption(String, String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns the metadata for the specified table or None if it doesn't exist.
getTables(SparkSession, String) - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
getTaskInfos() - Method in class org.apache.spark.BarrierTaskContext
:: Experimental :: Returns BarrierTaskInfo for all tasks in this barrier stage, ordered by partition ID.
getTau0() - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
A (positive) learning parameter that downweights early iterations.
getThreadDump() - Static method in class org.apache.spark.util.Utils
Return a thread dump of all threads' stacktraces.
getThreadDumpForThread(long) - Static method in class org.apache.spark.util.Utils
 
getThreshold() - Method in class org.apache.spark.ml.classification.LogisticRegression
 
getThreshold() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
 
getThreshold() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
Get threshold for binary classification.
getThreshold() - Method in class org.apache.spark.ml.feature.Binarizer
 
getThreshold() - Method in interface org.apache.spark.ml.param.shared.HasThreshold
 
getThreshold() - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
Returns the threshold (if any) used for converting raw prediction scores into 0/1 predictions.
getThreshold() - Method in class org.apache.spark.mllib.classification.SVMModel
Returns the threshold (if any) used for converting raw prediction scores into 0/1 predictions.
getThresholds() - Method in class org.apache.spark.ml.classification.LogisticRegression
 
getThresholds() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
 
getThresholds() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
Get thresholds for binary or multiclass classification.
getThresholds() - Method in interface org.apache.spark.ml.param.shared.HasThresholds
 
getTimeAsMs(String) - Method in class org.apache.spark.SparkConf
Get a time parameter as milliseconds; throws a NoSuchElementException if it's not set.
getTimeAsMs(String, String) - Method in class org.apache.spark.SparkConf
Get a time parameter as milliseconds, falling back to a default if not set.
getTimeAsSeconds(String) - Method in class org.apache.spark.SparkConf
Get a time parameter as seconds; throws a NoSuchElementException if it's not set.
getTimeAsSeconds(String, String) - Method in class org.apache.spark.SparkConf
Get a time parameter as seconds, falling back to a default if not set.
getTimeMillis() - Method in interface org.apache.spark.util.Clock
 
getTimer(L) - Method in interface org.apache.spark.util.ListenerBus
Returns a CodaHale metrics Timer for measuring the listener's event processing time.
getTimestamp(int) - Method in interface org.apache.spark.sql.Row
Returns the value at position i of date type as java.sql.Timestamp.
getTimestamp() - Method in class org.apache.spark.streaming.kinesis.KinesisInitialPositions.AtTimestamp
 
getTimestampWritable(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getTimestampWritableConstantObjectInspector(Object) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
getTimeZoneOffset() - Static method in class org.apache.spark.ui.UIUtils
 
GETTING_RESULT_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
 
GETTING_RESULT_TIME() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
 
GETTING_RESULT_TIME() - Static method in class org.apache.spark.ui.ToolTips
 
gettingResult() - Method in class org.apache.spark.scheduler.TaskInfo
 
gettingResultTime() - Method in class org.apache.spark.scheduler.TaskInfo
The time when the task started remotely getting the result.
gettingResultTime() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
gettingResultTime(TaskData) - Static method in class org.apache.spark.status.AppStatusUtils
 
gettingResultTime(long, long, long) - Static method in class org.apache.spark.status.AppStatusUtils
 
getTol() - Method in interface org.apache.spark.ml.param.shared.HasTol
 
getToLowercase() - Method in class org.apache.spark.ml.feature.RegexTokenizer
 
getTopicConcentration() - Method in interface org.apache.spark.ml.clustering.LDAParams
 
getTopicConcentration() - Method in class org.apache.spark.mllib.clustering.LDA
Concentration parameter (commonly named "beta" or "eta") for the prior placed on topics' distributions over terms.
getTopicDistributionCol() - Method in interface org.apache.spark.ml.clustering.LDAParams
 
getTopologyForHost(String) - Method in class org.apache.spark.storage.DefaultTopologyMapper
 
getTopologyForHost(String) - Method in class org.apache.spark.storage.FileBasedTopologyMapper
 
getTopologyForHost(String) - Method in class org.apache.spark.storage.TopologyMapper
Gets the topology information given the host name
getTrainRatio() - Method in interface org.apache.spark.ml.tuning.TrainValidationSplitParams
 
getTreeStrategy() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
getTruncateQuery(String, Option<Object>) - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
The SQL query used to truncate a table.
getTruncateQuery(String) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
 
getTruncateQuery(String, Option<Object>) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
 
getTruncateQuery(String) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
 
getTruncateQuery(String, Option<Object>) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
 
getTruncateQuery(String) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
The SQL query that should be used to truncate a table.
getTruncateQuery(String, Option<Object>) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
The SQL query that should be used to truncate a table.
getTruncateQuery(String) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
 
getTruncateQuery(String, Option<Object>) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
 
getTruncateQuery(String) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
getTruncateQuery(String, Option<Object>) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
getTruncateQuery(String) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
 
getTruncateQuery(String, Option<Object>) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
 
getTruncateQuery(String, Option<Object>) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
The SQL query used to truncate a table.
getTruncateQuery(String, Option<Object>) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
The SQL query used to truncate a table.
getTruncateQuery(String, Option<Object>) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
The SQL query used to truncate a table.
getTruncateQuery$default$2() - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
 
getTruncateQuery$default$2() - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
 
getTruncateQuery$default$2() - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
 
getTruncateQuery$default$2() - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
getTruncateQuery$default$2() - Static method in class org.apache.spark.sql.jdbc.NoopDialect
 
getTruncateQuery$default$2() - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
getTruncateQuery$default$2() - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
 
getTruncateQuery$default$2() - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
getUDTFor(String) - Static method in class org.apache.spark.sql.types.UDTRegistration
Returns the Class of UserDefinedType for the name of a given user class.
getUidMap(Params) - Static method in class org.apache.spark.ml.util.MetaAlgorithmReadWrite
Examine the given estimator (which may be a compound estimator) and extract a mapping from UIDs to corresponding Params instances.
getUiRoot(ServletContext) - Static method in class org.apache.spark.status.api.v1.UIRootFromServletContext
 
getUpperBound(double, long, double) - Static method in class org.apache.spark.util.random.BinomialBounds
Returns a threshold p such that if we conduct n Bernoulli trials with success rate = p, it is very unlikely to have less than fraction * n successes.
getUpperBound(double) - Static method in class org.apache.spark.util.random.PoissonBounds
Returns a lambda such that Pr[X < s] is very small, where X ~ Pois(lambda).
getUpperBoundsOnCoefficients() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
 
getUpperBoundsOnIntercepts() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
 
getUsedTimeMs(long) - Static method in class org.apache.spark.util.Utils
Return the string to tell how long has passed in milliseconds.
getUseNodeIdCache() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
getUserCol() - Method in interface org.apache.spark.ml.recommendation.ALSModelParams
 
getUserJars(SparkConf) - Static method in class org.apache.spark.util.Utils
Return the jar files pointed by the "spark.jars" property.
getUTF8String(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
getUTF8String(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
getUTF8String(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
getUTF8String(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the string type value for rowId.
getValidationIndicatorCol() - Method in interface org.apache.spark.ml.param.shared.HasValidationIndicatorCol
 
getValidationTol() - Method in interface org.apache.spark.ml.tree.GBTParams
 
getValidationTol() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
getValue(int) - Method in class org.apache.spark.ml.attribute.NominalAttribute
Gets a value given its index.
getValuesMap(Seq<String>) - Method in interface org.apache.spark.sql.Row
Returns a Map consisting of names and values for the requested fieldNames For primitive types if value is null it returns 'zero value' specific for primitive ie.
getVarianceCol() - Method in interface org.apache.spark.ml.param.shared.HasVarianceCol
 
getVariancePower() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
 
getVectors() - Method in class org.apache.spark.ml.feature.Word2VecModel
Returns a dataframe with two fields, "word" and "vector", with "word" being a String and and the vector the DenseVector that it is mapped to.
getVectors() - Method in class org.apache.spark.mllib.feature.Word2VecModel
Returns a map of words to their vector representations.
getVectorSize() - Method in interface org.apache.spark.ml.feature.Word2VecBase
 
getVocabSize() - Method in interface org.apache.spark.ml.feature.CountVectorizerParams
 
getWeightCol() - Method in interface org.apache.spark.ml.param.shared.HasWeightCol
 
getWidth(Row) - Static method in class org.apache.spark.ml.image.ImageSchema
Gets the width of the image
getWindowSize() - Method in interface org.apache.spark.ml.feature.Word2VecBase
 
getWithMean() - Method in interface org.apache.spark.ml.feature.StandardScalerParams
 
getWithStd() - Method in interface org.apache.spark.ml.feature.StandardScalerParams
 
Gini - Class in org.apache.spark.mllib.tree.impurity
Class for calculating the Gini impurity (http://en.wikipedia.org/wiki/Decision_tree_learning#Gini_impurity) during multiclass classification.
Gini() - Constructor for class org.apache.spark.mllib.tree.impurity.Gini
 
GLMClassificationModel - Class in org.apache.spark.mllib.classification.impl
Helper class for import/export of GLM classification models.
GLMClassificationModel() - Constructor for class org.apache.spark.mllib.classification.impl.GLMClassificationModel
 
GLMClassificationModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.classification.impl
 
GLMClassificationModel.SaveLoadV1_0$.Data - Class in org.apache.spark.mllib.classification.impl
Model data for import/export
GLMClassificationModel.SaveLoadV1_0$.Data$ - Class in org.apache.spark.mllib.classification.impl
 
GLMRegressionModel - Class in org.apache.spark.mllib.regression.impl
Helper methods for import/export of GLM regression models.
GLMRegressionModel() - Constructor for class org.apache.spark.mllib.regression.impl.GLMRegressionModel
 
GLMRegressionModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.regression.impl
 
GLMRegressionModel.SaveLoadV1_0$.Data - Class in org.apache.spark.mllib.regression.impl
Model data for model import/export
GLMRegressionModel.SaveLoadV1_0$.Data$ - Class in org.apache.spark.mllib.regression.impl
 
glom() - Method in interface org.apache.spark.api.java.JavaRDDLike
Return an RDD created by coalescing all elements within each partition into an array.
glom() - Method in class org.apache.spark.rdd.RDD
Return an RDD created by coalescing all elements within each partition into an array.
glom() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD is generated by applying glom() to each RDD of this DStream.
glom() - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD is generated by applying glom() to each RDD of this DStream.
goButtonFormPath() - Method in interface org.apache.spark.ui.PagedTable
Returns the submission path for the "go to page #" form.
goodnessOfFit() - Method in class org.apache.spark.mllib.stat.test.ChiSqTest.NullHypothesis$
 
grad(DenseMatrix<Object>, DenseMatrix<Object>, DenseVector<Object>) - Method in interface org.apache.spark.ml.ann.LayerModel
Computes the gradient.
grad() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
 
gradient() - Method in interface org.apache.spark.ml.optim.aggregator.DifferentiableLossAggregator
The current weighted averaged gradient.
gradient() - Method in class org.apache.spark.ml.regression.AFTAggregator
 
Gradient - Class in org.apache.spark.mllib.optimization
:: DeveloperApi :: Class used to compute the gradient for a loss function, given a single data point.
Gradient() - Constructor for class org.apache.spark.mllib.optimization.Gradient
 
gradient(double, double) - Static method in class org.apache.spark.mllib.tree.loss.AbsoluteError
Method to calculate the gradients for the gradient boosting calculation for least absolute error calculation.
gradient(double, double) - Static method in class org.apache.spark.mllib.tree.loss.LogLoss
Method to calculate the loss gradients for the gradient boosting calculation for binary classification The gradient with respect to F(x) is: - 4 y / (1 + exp(2 y F(x)))
gradient(double, double) - Method in interface org.apache.spark.mllib.tree.loss.Loss
Method to calculate the gradients for the gradient boosting calculation.
gradient(double, double) - Static method in class org.apache.spark.mllib.tree.loss.SquaredError
Method to calculate the gradients for the gradient boosting calculation for least squares error calculation.
GradientBoostedTrees - Class in org.apache.spark.ml.tree.impl
 
GradientBoostedTrees() - Constructor for class org.apache.spark.ml.tree.impl.GradientBoostedTrees
 
GradientBoostedTrees - Class in org.apache.spark.mllib.tree
A class that implements Stochastic Gradient Boosting for regression and binary classification.
GradientBoostedTrees(BoostingStrategy) - Constructor for class org.apache.spark.mllib.tree.GradientBoostedTrees
 
GradientBoostedTreesModel - Class in org.apache.spark.mllib.tree.model
Represents a gradient boosted trees model.
GradientBoostedTreesModel(Enumeration.Value, DecisionTreeModel[], double[]) - Constructor for class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
 
GradientDescent - Class in org.apache.spark.mllib.optimization
Class used to solve an optimization problem using Gradient Descent.
gradientSumArray() - Method in interface org.apache.spark.ml.optim.aggregator.DifferentiableLossAggregator
Array of gradient values that are mutated when new instances are added to the aggregator.
Graph<VD,ED> - Class in org.apache.spark.graphx
The Graph abstractly represents a graph with arbitrary objects associated with vertices and edges.
GraphGenerators - Class in org.apache.spark.graphx.util
A collection of graph generating functions.
GraphGenerators() - Constructor for class org.apache.spark.graphx.util.GraphGenerators
 
GraphImpl<VD,ED> - Class in org.apache.spark.graphx.impl
An implementation of Graph to support computation on graphs.
GraphLoader - Class in org.apache.spark.graphx
Provides utilities for loading Graphs from files.
GraphLoader() - Constructor for class org.apache.spark.graphx.GraphLoader
 
GraphOps<VD,ED> - Class in org.apache.spark.graphx
Contains additional functionality for Graph.
GraphOps(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Constructor for class org.apache.spark.graphx.GraphOps
 
graphToGraphOps(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.Graph
Implicitly extracts the GraphOps member from a graph.
GraphXUtils - Class in org.apache.spark.graphx
 
GraphXUtils() - Constructor for class org.apache.spark.graphx.GraphXUtils
 
greater(Duration) - Method in class org.apache.spark.streaming.Duration
 
greater(Time) - Method in class org.apache.spark.streaming.Time
 
greaterEq(Duration) - Method in class org.apache.spark.streaming.Duration
 
greaterEq(Time) - Method in class org.apache.spark.streaming.Time
 
GreaterThan - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff the attribute evaluates to a value greater than value.
GreaterThan(String, Object) - Constructor for class org.apache.spark.sql.sources.GreaterThan
 
GreaterThanOrEqual - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff the attribute evaluates to a value greater than or equal to value.
GreaterThanOrEqual(String, Object) - Constructor for class org.apache.spark.sql.sources.GreaterThanOrEqual
 
greatest(Column...) - Static method in class org.apache.spark.sql.functions
Returns the greatest value of the list of values, skipping null values.
greatest(String, String...) - Static method in class org.apache.spark.sql.functions
Returns the greatest value of the list of column names, skipping null values.
greatest(Seq<Column>) - Static method in class org.apache.spark.sql.functions
Returns the greatest value of the list of values, skipping null values.
greatest(String, Seq<String>) - Static method in class org.apache.spark.sql.functions
Returns the greatest value of the list of column names, skipping null values.
gridGraph(SparkContext, int, int) - Static method in class org.apache.spark.graphx.util.GraphGenerators
Create rows by cols grid graph with each vertex connected to its row+1 and col+1 neighbors.
groupArr() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
 
groupBy(Function<T, U>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return an RDD of grouped elements.
groupBy(Function<T, U>, int) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return an RDD of grouped elements.
groupBy(Function1<T, K>, ClassTag<K>) - Method in class org.apache.spark.rdd.RDD
Return an RDD of grouped items.
groupBy(Function1<T, K>, int, ClassTag<K>) - Method in class org.apache.spark.rdd.RDD
Return an RDD of grouped elements.
groupBy(Function1<T, K>, Partitioner, ClassTag<K>, Ordering<K>) - Method in class org.apache.spark.rdd.RDD
Return an RDD of grouped items.
groupBy(Column...) - Method in class org.apache.spark.sql.Dataset
Groups the Dataset using the specified columns, so we can run aggregation on them.
groupBy(String, String...) - Method in class org.apache.spark.sql.Dataset
Groups the Dataset using the specified columns, so that we can run aggregation on them.
groupBy(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
Groups the Dataset using the specified columns, so we can run aggregation on them.
groupBy(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
Groups the Dataset using the specified columns, so that we can run aggregation on them.
groupByKey(Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
Group the values for each key in the RDD into a single sequence.
groupByKey(int) - Method in class org.apache.spark.api.java.JavaPairRDD
Group the values for each key in the RDD into a single sequence.
groupByKey() - Method in class org.apache.spark.api.java.JavaPairRDD
Group the values for each key in the RDD into a single sequence.
groupByKey(Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
Group the values for each key in the RDD into a single sequence.
groupByKey(int) - Method in class org.apache.spark.rdd.PairRDDFunctions
Group the values for each key in the RDD into a single sequence.
groupByKey() - Method in class org.apache.spark.rdd.PairRDDFunctions
Group the values for each key in the RDD into a single sequence.
groupByKey(Function1<T, K>, Encoder<K>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: (Scala-specific) Returns a KeyValueGroupedDataset where the data is grouped by the given key func.
groupByKey(MapFunction<T, K>, Encoder<K>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: (Java-specific) Returns a KeyValueGroupedDataset where the data is grouped by the given key func.
groupByKey() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying groupByKey to each RDD.
groupByKey(int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying groupByKey to each RDD.
groupByKey(Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying groupByKey on each RDD of this DStream.
groupByKey() - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying groupByKey to each RDD.
groupByKey(int) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying groupByKey to each RDD.
groupByKey(Partitioner) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying groupByKey on each RDD.
groupByKeyAndWindow(Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying groupByKey over a sliding window.
groupByKeyAndWindow(Duration, Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying groupByKey over a sliding window.
groupByKeyAndWindow(Duration, Duration, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying groupByKey over a sliding window on this DStream.
groupByKeyAndWindow(Duration, Duration, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying groupByKey over a sliding window on this DStream.
groupByKeyAndWindow(Duration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying groupByKey over a sliding window.
groupByKeyAndWindow(Duration, Duration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying groupByKey over a sliding window.
groupByKeyAndWindow(Duration, Duration, int) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying groupByKey over a sliding window on this DStream.
groupByKeyAndWindow(Duration, Duration, Partitioner) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Create a new DStream by applying groupByKey over a sliding window on this DStream.
GroupByType$() - Constructor for class org.apache.spark.sql.RelationalGroupedDataset.GroupByType$
 
groupEdges(Function2<ED, ED, ED>) - Method in class org.apache.spark.graphx.Graph
Merges multiple edges between two vertices into a single edge.
groupEdges(Function2<ED, ED, ED>) - Method in class org.apache.spark.graphx.impl.GraphImpl
 
groupHash() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
 
grouping(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: indicates whether a specified column in a GROUP BY list is aggregated or not, returns 1 for aggregated or 0 for not aggregated in the result set.
grouping(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: indicates whether a specified column in a GROUP BY list is aggregated or not, returns 1 for aggregated or 0 for not aggregated in the result set.
grouping_id(Seq<Column>) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the level of grouping, equals to
grouping_id(String, Seq<String>) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the level of grouping, equals to
GroupMappingServiceProvider - Interface in org.apache.spark.security
This Spark trait is used for mapping a given userName to a set of groups which it belongs to.
GroupState<S> - Interface in org.apache.spark.sql.streaming
:: Experimental ::
GroupStateTimeout - Class in org.apache.spark.sql.streaming
Represents the type of timeouts possible for the Dataset operations `mapGroupsWithState` and `flatMapGroupsWithState`.
GroupStateTimeout() - Constructor for class org.apache.spark.sql.streaming.GroupStateTimeout
 
groupWith(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
Alias for cogroup.
groupWith(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>) - Method in class org.apache.spark.api.java.JavaPairRDD
Alias for cogroup.
groupWith(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>, JavaPairRDD<K, W3>) - Method in class org.apache.spark.api.java.JavaPairRDD
Alias for cogroup.
groupWith(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Alias for cogroup.
groupWith(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Alias for cogroup.
groupWith(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>, RDD<Tuple2<K, W3>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Alias for cogroup.
gt(double) - Static method in class org.apache.spark.ml.param.ParamValidators
Check if value is greater than lowerBound
gt(Object) - Method in class org.apache.spark.sql.Column
Greater than.
gtEq(double) - Static method in class org.apache.spark.ml.param.ParamValidators
Check if value is greater than or equal to lowerBound
guard(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 

H

hadoopConfiguration() - Method in class org.apache.spark.api.java.JavaSparkContext
Returns the Hadoop configuration used for the Hadoop code (e.g.
hadoopConfiguration() - Method in class org.apache.spark.SparkContext
A default Hadoop Configuration for the Hadoop code (e.g.
hadoopDelegationCreds() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SparkAppConfig
 
hadoopFile(String, Class<F>, Class<K>, Class<V>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
Get an RDD for a Hadoop file with an arbitrary InputFormat.
hadoopFile(String, Class<F>, Class<K>, Class<V>) - Method in class org.apache.spark.api.java.JavaSparkContext
Get an RDD for a Hadoop file with an arbitrary InputFormat
hadoopFile(String, Class<? extends InputFormat<K, V>>, Class<K>, Class<V>, int) - Method in class org.apache.spark.SparkContext
Get an RDD for a Hadoop file with an arbitrary InputFormat
hadoopFile(String, int, ClassTag<K>, ClassTag<V>, ClassTag<F>) - Method in class org.apache.spark.SparkContext
Smarter version of hadoopFile() that uses class tags to figure out the classes of keys, values and the InputFormat so that users don't need to pass them directly.
hadoopFile(String, ClassTag<K>, ClassTag<V>, ClassTag<F>) - Method in class org.apache.spark.SparkContext
Smarter version of hadoopFile() that uses class tags to figure out the classes of keys, values and the InputFormat so that users don't need to pass them directly.
HadoopMapPartitionsWithSplitRDD$() - Constructor for class org.apache.spark.rdd.HadoopRDD.HadoopMapPartitionsWithSplitRDD$
 
HadoopMapRedCommitProtocol - Class in org.apache.spark.internal.io
An FileCommitProtocol implementation backed by an underlying Hadoop OutputCommitter (from the old mapred API).
HadoopMapRedCommitProtocol(String, String) - Constructor for class org.apache.spark.internal.io.HadoopMapRedCommitProtocol
 
HadoopMapReduceCommitProtocol - Class in org.apache.spark.internal.io
An FileCommitProtocol implementation backed by an underlying Hadoop OutputCommitter (from the newer mapreduce API, not the old mapred API).
HadoopMapReduceCommitProtocol(String, String, boolean) - Constructor for class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
 
hadoopRDD(JobConf, Class<F>, Class<K>, Class<V>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
Get an RDD for a Hadoop-readable dataset from a Hadoop JobConf giving its InputFormat and any other necessary info (e.g.
hadoopRDD(JobConf, Class<F>, Class<K>, Class<V>) - Method in class org.apache.spark.api.java.JavaSparkContext
Get an RDD for a Hadoop-readable dataset from a Hadoop JobConf giving its InputFormat and any other necessary info (e.g.
HadoopRDD<K,V> - Class in org.apache.spark.rdd
:: DeveloperApi :: An RDD that provides core functionality for reading data stored in Hadoop (e.g., files in HDFS, sources in HBase, or S3), using the older MapReduce API (org.apache.hadoop.mapred).
HadoopRDD(SparkContext, Broadcast<org.apache.spark.util.SerializableConfiguration>, Option<Function1<JobConf, BoxedUnit>>, Class<? extends InputFormat<K, V>>, Class<K>, Class<V>, int) - Constructor for class org.apache.spark.rdd.HadoopRDD
 
HadoopRDD(SparkContext, JobConf, Class<? extends InputFormat<K, V>>, Class<K>, Class<V>, int) - Constructor for class org.apache.spark.rdd.HadoopRDD
 
hadoopRDD(JobConf, Class<? extends InputFormat<K, V>>, Class<K>, Class<V>, int) - Method in class org.apache.spark.SparkContext
Get an RDD for a Hadoop-readable dataset from a Hadoop JobConf given its InputFormat and other necessary info (e.g.
HadoopRDD.HadoopMapPartitionsWithSplitRDD$ - Class in org.apache.spark.rdd
 
HadoopWriteConfigUtil<K,V> - Class in org.apache.spark.internal.io
Interface for create output format/committer/writer used during saving an RDD using a Hadoop OutputFormat (both from the old mapred API and the new mapreduce API)
HadoopWriteConfigUtil(ClassTag<V>) - Constructor for class org.apache.spark.internal.io.HadoopWriteConfigUtil
 
hammingLoss() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
Returns Hamming-loss
handleInvalid() - Method in class org.apache.spark.ml.feature.Bucketizer
Param for how to handle invalid entries.
handleInvalid() - Method in interface org.apache.spark.ml.feature.OneHotEncoderBase
Param for how to handle invalid data during transform().
handleInvalid() - Method in interface org.apache.spark.ml.feature.QuantileDiscretizerBase
Param for how to handle invalid entries.
handleInvalid() - Method in interface org.apache.spark.ml.feature.RFormulaBase
Param for how to handle invalid data (unseen or NULL values) in features and label column of string type.
handleInvalid() - Method in interface org.apache.spark.ml.feature.StringIndexerBase
Param for how to handle invalid data (unseen labels or NULL values).
handleInvalid() - Method in class org.apache.spark.ml.feature.VectorAssembler
Param for how to handle invalid data (NULL values).
handleInvalid() - Method in interface org.apache.spark.ml.feature.VectorIndexerParams
Param for how to handle invalid data (unseen labels or NULL values).
handleInvalid() - Method in class org.apache.spark.ml.feature.VectorSizeHint
Param for how to handle invalid entries.
handleInvalid() - Method in interface org.apache.spark.ml.param.shared.HasHandleInvalid
Param for how to handle invalid entries.
hasAccumulators(StageData) - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HasAggregationDepth - Interface in org.apache.spark.ml.param.shared
Trait for shared param aggregationDepth (default: 2).
hasAttr(String) - Method in class org.apache.spark.ml.attribute.AttributeGroup
Test whether this attribute group contains a specific attribute.
hasBytesSpilled(StageData) - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HasCachedBlocks(String) - Constructor for class org.apache.spark.storage.BlockManagerMessages.HasCachedBlocks
 
HasCachedBlocks$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.HasCachedBlocks$
 
hasCachedSerializedBroadcast() - Method in class org.apache.spark.ShuffleStatus
 
HasCheckpointInterval - Interface in org.apache.spark.ml.param.shared
Trait for shared param checkpointInterval.
HasCollectSubModels - Interface in org.apache.spark.ml.param.shared
Trait for shared param collectSubModels (default: false).
hasDefault(Param<T>) - Method in interface org.apache.spark.ml.param.Params
Tests whether the input param has a default value set.
HasDistanceMeasure - Interface in org.apache.spark.ml.param.shared
Trait for shared param distanceMeasure (default: org.apache.spark.mllib.clustering.DistanceMeasure.EUCLIDEAN).
HasElasticNetParam - Interface in org.apache.spark.ml.param.shared
Trait for shared param elasticNetParam.
HasFeaturesCol - Interface in org.apache.spark.ml.param.shared
Trait for shared param featuresCol (default: "features").
HasFitIntercept - Interface in org.apache.spark.ml.param.shared
Trait for shared param fitIntercept (default: true).
hash(Column...) - Static method in class org.apache.spark.sql.functions
Calculates the hash code of given columns, and returns the result as an int column.
hash(Seq<Column>) - Static method in class org.apache.spark.sql.functions
Calculates the hash code of given columns, and returns the result as an int column.
HasHandleInvalid - Interface in org.apache.spark.ml.param.shared
Trait for shared param handleInvalid.
hashCode() - Method in class org.apache.spark.api.java.Optional
 
hashCode() - Method in class org.apache.spark.graphx.EdgeDirection
 
hashCode() - Method in class org.apache.spark.HashPartitioner
 
hashCode() - Method in class org.apache.spark.ml.attribute.AttributeGroup
 
hashCode() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
 
hashCode() - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
hashCode() - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
hashCode() - Method in class org.apache.spark.ml.linalg.DenseMatrix
 
hashCode() - Method in class org.apache.spark.ml.linalg.DenseVector
 
hashCode() - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
hashCode() - Method in class org.apache.spark.ml.linalg.SparseVector
 
hashCode() - Method in interface org.apache.spark.ml.linalg.Vector
Returns a hash code value for the vector.
hashCode() - Method in class org.apache.spark.ml.param.Param
 
hashCode() - Method in class org.apache.spark.ml.tree.CategoricalSplit
 
hashCode() - Method in class org.apache.spark.ml.tree.ContinuousSplit
 
hashCode() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
 
hashCode() - Method in class org.apache.spark.mllib.linalg.DenseVector
 
hashCode() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
hashCode() - Method in class org.apache.spark.mllib.linalg.SparseVector
 
hashCode() - Method in interface org.apache.spark.mllib.linalg.Vector
Returns a hash code value for the vector.
hashCode() - Method in class org.apache.spark.mllib.linalg.VectorUDT
 
hashCode() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
 
hashCode() - Method in class org.apache.spark.mllib.tree.model.Predict
 
hashCode() - Method in class org.apache.spark.partial.BoundedDouble
 
hashCode() - Method in interface org.apache.spark.Partition
 
hashCode() - Method in class org.apache.spark.RangePartitioner
 
hashCode() - Method in class org.apache.spark.scheduler.cluster.ExecutorInfo
 
hashCode() - Method in class org.apache.spark.scheduler.InputFormatInfo
 
hashCode() - Method in class org.apache.spark.scheduler.SplitInfo
 
hashCode() - Method in class org.apache.spark.sql.Column
 
hashCode() - Method in interface org.apache.spark.sql.Row
 
hashCode() - Method in class org.apache.spark.sql.sources.In
 
hashCode() - Method in class org.apache.spark.sql.sources.v2.reader.streaming.Offset
 
hashCode() - Method in class org.apache.spark.sql.types.Decimal
 
hashCode() - Method in class org.apache.spark.sql.types.Metadata
 
hashCode() - Method in class org.apache.spark.sql.types.StructType
 
hashCode() - Method in class org.apache.spark.storage.BlockManagerId
 
hashCode() - Method in class org.apache.spark.storage.StorageLevel
 
HashingTF - Class in org.apache.spark.ml.feature
Maps a sequence of terms to their term frequencies using the hashing trick.
HashingTF(String) - Constructor for class org.apache.spark.ml.feature.HashingTF
 
HashingTF() - Constructor for class org.apache.spark.ml.feature.HashingTF
 
HashingTF - Class in org.apache.spark.mllib.feature
Maps a sequence of terms to their term frequencies using the hashing trick.
HashingTF(int) - Constructor for class org.apache.spark.mllib.feature.HashingTF
 
HashingTF() - Constructor for class org.apache.spark.mllib.feature.HashingTF
 
HashPartitioner - Class in org.apache.spark
A Partitioner that implements hash-based partitioning using Java's Object.hashCode.
HashPartitioner(int) - Constructor for class org.apache.spark.HashPartitioner
 
hasInput(StageData) - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HasInputCol - Interface in org.apache.spark.ml.param.shared
Trait for shared param inputCol.
HasInputCols - Interface in org.apache.spark.ml.param.shared
Trait for shared param inputCols.
hasInputOutputFormat() - Method in class org.apache.spark.sql.hive.execution.HiveOptions
 
hasLabelCol(StructType) - Method in interface org.apache.spark.ml.feature.RFormulaBase
 
HasLabelCol - Interface in org.apache.spark.ml.param.shared
Trait for shared param labelCol (default: "label").
hasLinkPredictionCol() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
Checks whether we should output link prediction.
HasLoss - Interface in org.apache.spark.ml.param.shared
Trait for shared param loss.
HasMaxIter - Interface in org.apache.spark.ml.param.shared
Trait for shared param maxIter.
hasMemoryInfo() - Method in class org.apache.spark.status.LiveExecutor
 
hasNext() - Method in class org.apache.spark.InterruptibleIterator
 
hasNull() - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
hasNull() - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns true if this column vector contains any null values.
hasOffsetCol() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
Checks whether offset column is set and nonempty.
hasOutput(StageData) - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HasOutputCol - Interface in org.apache.spark.ml.param.shared
Trait for shared param outputCol (default: uid + "__output").
HasOutputCols - Interface in org.apache.spark.ml.param.shared
Trait for shared param outputCols.
HasParallelism - Interface in org.apache.spark.ml.param.shared
Trait to define a level of parallelism for algorithms that are able to use multithreaded execution, and provide a thread-pool based execution context.
hasParam(String) - Method in interface org.apache.spark.ml.param.Params
Tests whether this instance contains a param with a given name.
hasParent() - Method in class org.apache.spark.ml.Model
Indicates whether this Model has a corresponding parent.
HasPredictionCol - Interface in org.apache.spark.ml.param.shared
Trait for shared param predictionCol (default: "prediction").
HasProbabilityCol - Interface in org.apache.spark.ml.param.shared
Trait for shared param probabilityCol (default: "probability").
hasQuantilesCol() - Method in interface org.apache.spark.ml.regression.AFTSurvivalRegressionParams
Checks whether the input has quantiles column name.
HasRawPredictionCol - Interface in org.apache.spark.ml.param.shared
Trait for shared param rawPredictionCol (default: "rawPrediction").
HasRegParam - Interface in org.apache.spark.ml.param.shared
Trait for shared param regParam.
hasRootAsShutdownDeleteDir(File) - Static method in class org.apache.spark.util.ShutdownHookManager
 
HasSeed - Interface in org.apache.spark.ml.param.shared
Trait for shared param seed (default: this.getClass.getName.hashCode.toLong).
hasShuffleRead(StageData) - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
hasShuffleWrite(StageData) - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
hasShutdownDeleteDir(File) - Static method in class org.apache.spark.util.ShutdownHookManager
 
HasSolver - Interface in org.apache.spark.ml.param.shared
Trait for shared param solver.
HasStandardization - Interface in org.apache.spark.ml.param.shared
Trait for shared param standardization (default: true).
HasStepSize - Interface in org.apache.spark.ml.param.shared
Trait for shared param stepSize.
hasSubModels() - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
 
hasSubModels() - Method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
 
hasSummary() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
Indicates whether a training summary exists for this model instance.
hasSummary() - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
Return true if there exists summary of model.
hasSummary() - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
Return true if there exists summary of model.
hasSummary() - Method in class org.apache.spark.ml.clustering.KMeansModel
Return true if there exists summary of model.
hasSummary() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
Indicates if summary is available.
hasSummary() - Method in class org.apache.spark.ml.regression.LinearRegressionModel
Indicates whether a training summary exists for this model instance.
HasThreshold - Interface in org.apache.spark.ml.param.shared
Trait for shared param threshold.
HasThresholds - Interface in org.apache.spark.ml.param.shared
Trait for shared param thresholds.
hasTimedOut() - Method in interface org.apache.spark.sql.streaming.GroupState
Whether the function has been called because the key has timed out.
HasTol - Interface in org.apache.spark.ml.param.shared
Trait for shared param tol.
HasValidationIndicatorCol - Interface in org.apache.spark.ml.param.shared
Trait for shared param validationIndicatorCol.
hasValue(String) - Method in class org.apache.spark.ml.attribute.NominalAttribute
Tests whether this attribute contains a specific value.
HasVarianceCol - Interface in org.apache.spark.ml.param.shared
Trait for shared param varianceCol.
HasWeightCol - Interface in org.apache.spark.ml.param.shared
Trait for shared param weightCol.
hasWeightCol() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
Checks whether weight column is set and nonempty.
hasWeightCol() - Method in interface org.apache.spark.ml.regression.IsotonicRegressionBase
Checks whether the input has weight column.
hasWriteObjectMethod() - Method in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
 
hasWriteReplaceMethod() - Method in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
 
HdfsUtils - Class in org.apache.spark.streaming.util
 
HdfsUtils() - Constructor for class org.apache.spark.streaming.util.HdfsUtils
 
head(int) - Method in class org.apache.spark.sql.Dataset
Returns the first n rows.
head() - Method in class org.apache.spark.sql.Dataset
Returns the first row.
HEADER_ACCUMULATORS() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_ATTEMPT() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_DESER_TIME() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_DISK_SPILL() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_DURATION() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_ERROR() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_EXECUTOR() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_GC_TIME() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_GETTING_RESULT_TIME() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_HOST() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_ID() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_INPUT_SIZE() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_LAUNCH_TIME() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_LOCALITY() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_MEM_SPILL() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_OUTPUT_SIZE() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_PEAK_MEM() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_SCHEDULER_DELAY() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_SER_TIME() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_SHUFFLE_READ_TIME() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_SHUFFLE_REMOTE_READS() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_SHUFFLE_TOTAL_READS() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_SHUFFLE_WRITE_SIZE() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_SHUFFLE_WRITE_TIME() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_STATUS() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
HEADER_TASK_INDEX() - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
headers() - Method in interface org.apache.spark.ui.PagedTable
 
headerSparkPage(HttpServletRequest, String, Function0<Seq<Node>>, SparkUITab, Option<Object>, Option<String>, boolean, boolean) - Static method in class org.apache.spark.ui.UIUtils
Returns a spark page with correctly formatted headers
hex(Column) - Static method in class org.apache.spark.sql.functions
Computes hex value of the given column.
high() - Method in class org.apache.spark.partial.BoundedDouble
 
HingeGradient - Class in org.apache.spark.mllib.optimization
:: DeveloperApi :: Compute gradient and loss for a Hinge loss function, as used in SVM binary classification.
HingeGradient() - Constructor for class org.apache.spark.mllib.optimization.HingeGradient
 
hint(String, Object...) - Method in class org.apache.spark.sql.Dataset
Specifies some hint on the current Dataset.
hint(String, Seq<Object>) - Method in class org.apache.spark.sql.Dataset
Specifies some hint on the current Dataset.
histogram(int) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Compute a histogram of the data using bucketCount number of buckets evenly spaced between the minimum and maximum of the RDD.
histogram(double[]) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Compute a histogram using the provided buckets.
histogram(Double[], boolean) - Method in class org.apache.spark.api.java.JavaDoubleRDD
 
histogram(int) - Method in class org.apache.spark.rdd.DoubleRDDFunctions
Compute a histogram of the data using bucketCount number of buckets evenly spaced between the minimum and maximum of the RDD.
histogram(double[], boolean) - Method in class org.apache.spark.rdd.DoubleRDDFunctions
Compute a histogram using the provided buckets.
HIVE_GENERIC_UDF_MACRO_CLS() - Static method in class org.apache.spark.sql.hive.HiveShim
 
HIVE_METASTORE_BARRIER_PREFIXES() - Static method in class org.apache.spark.sql.hive.HiveUtils
 
HIVE_METASTORE_JARS() - Static method in class org.apache.spark.sql.hive.HiveUtils
 
HIVE_METASTORE_SHARED_PREFIXES() - Static method in class org.apache.spark.sql.hive.HiveUtils
 
HIVE_METASTORE_VERSION() - Static method in class org.apache.spark.sql.hive.HiveUtils
 
HIVE_THRIFT_SERVER_ASYNC() - Static method in class org.apache.spark.sql.hive.HiveUtils
 
HiveAnalysis - Class in org.apache.spark.sql.hive
Replaces generic operations with specific variants that are designed to work with Hive.
HiveAnalysis() - Constructor for class org.apache.spark.sql.hive.HiveAnalysis
 
HiveCatalogMetrics - Class in org.apache.spark.metrics.source
:: Experimental :: Metrics for access to the hive external catalog.
HiveCatalogMetrics() - Constructor for class org.apache.spark.metrics.source.HiveCatalogMetrics
 
HiveClient - Interface in org.apache.spark.sql.hive.client
An externally visible interface to the Hive client.
HiveContext - Class in org.apache.spark.sql.hive
Deprecated.
Use SparkSession.builder.enableHiveSupport instead. Since 2.0.0.
HiveContext(SparkContext) - Constructor for class org.apache.spark.sql.hive.HiveContext
Deprecated.
 
HiveContext(JavaSparkContext) - Constructor for class org.apache.spark.sql.hive.HiveContext
Deprecated.
 
HiveFileFormat - Class in org.apache.spark.sql.hive.execution
FileFormat for writing Hive tables.
HiveFileFormat(org.apache.spark.sql.hive.HiveShim.ShimFileSinkDesc) - Constructor for class org.apache.spark.sql.hive.execution.HiveFileFormat
 
HiveFileFormat() - Constructor for class org.apache.spark.sql.hive.execution.HiveFileFormat
 
HiveFunctionWrapper$() - Constructor for class org.apache.spark.sql.hive.HiveShim.HiveFunctionWrapper$
 
HiveInspectors - Interface in org.apache.spark.sql.hive
1.
HiveInspectors.typeInfoConversions - Class in org.apache.spark.sql.hive
 
HiveOptions - Class in org.apache.spark.sql.hive.execution
Options for the Hive data source.
HiveOptions(CaseInsensitiveMap<String>) - Constructor for class org.apache.spark.sql.hive.execution.HiveOptions
 
HiveOptions(Map<String, String>) - Constructor for class org.apache.spark.sql.hive.execution.HiveOptions
 
HiveOutputWriter - Class in org.apache.spark.sql.hive.execution
 
HiveOutputWriter(String, org.apache.spark.sql.hive.HiveShim.ShimFileSinkDesc, JobConf, StructType) - Constructor for class org.apache.spark.sql.hive.execution.HiveOutputWriter
 
HiveScriptIOSchema - Class in org.apache.spark.sql.hive.execution
 
HiveScriptIOSchema(Seq<Tuple2<String, String>>, Seq<Tuple2<String, String>>, Option<String>, Option<String>, Seq<Tuple2<String, String>>, Seq<Tuple2<String, String>>, Option<String>, Option<String>, boolean) - Constructor for class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
HiveSessionResourceLoader - Class in org.apache.spark.sql.hive
 
HiveSessionResourceLoader(SparkSession, Function0<HiveClient>) - Constructor for class org.apache.spark.sql.hive.HiveSessionResourceLoader
 
HiveSessionStateBuilder - Class in org.apache.spark.sql.hive
Builder that produces a Hive-aware SessionState.
HiveSessionStateBuilder(SparkSession, Option<SessionState>) - Constructor for class org.apache.spark.sql.hive.HiveSessionStateBuilder
 
HiveShim - Class in org.apache.spark.sql.hive
 
HiveShim() - Constructor for class org.apache.spark.sql.hive.HiveShim
 
HiveShim.HiveFunctionWrapper$ - Class in org.apache.spark.sql.hive
 
HiveStrategies - Interface in org.apache.spark.sql.hive
 
HiveStrategies.HiveTableScans - Class in org.apache.spark.sql.hive
Retrieves data using a HiveTableScan.
HiveStrategies.HiveTableScans$ - Class in org.apache.spark.sql.hive
Retrieves data using a HiveTableScan.
HiveStrategies.Scripts - Class in org.apache.spark.sql.hive
 
HiveStrategies.Scripts$ - Class in org.apache.spark.sql.hive
 
HiveStringType - Class in org.apache.spark.sql.types
A hive string type for compatibility.
HiveStringType() - Constructor for class org.apache.spark.sql.types.HiveStringType
 
HiveTableScans() - Method in interface org.apache.spark.sql.hive.HiveStrategies
 
HiveTableScans() - Constructor for class org.apache.spark.sql.hive.HiveStrategies.HiveTableScans
 
HiveTableScans$() - Constructor for class org.apache.spark.sql.hive.HiveStrategies.HiveTableScans$
 
HiveTableUtil - Class in org.apache.spark.sql.hive
 
HiveTableUtil() - Constructor for class org.apache.spark.sql.hive.HiveTableUtil
 
HiveUDAFBuffer - Class in org.apache.spark.sql.hive
 
HiveUDAFBuffer(GenericUDAFEvaluator.AggregationBuffer, boolean) - Constructor for class org.apache.spark.sql.hive.HiveUDAFBuffer
 
HiveUtils - Class in org.apache.spark.sql.hive
 
HiveUtils() - Constructor for class org.apache.spark.sql.hive.HiveUtils
 
holdingLocks() - Method in class org.apache.spark.status.api.v1.ThreadStackTrace
 
horzcat(Matrix[]) - Static method in class org.apache.spark.ml.linalg.Matrices
Horizontally concatenate a sequence of matrices.
horzcat(Matrix[]) - Static method in class org.apache.spark.mllib.linalg.Matrices
Horizontally concatenate a sequence of matrices.
host() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillExecutorsOnHost
 
host() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveWorker
 
host() - Method in class org.apache.spark.scheduler.TaskInfo
 
host() - Method in interface org.apache.spark.scheduler.TaskLocation
 
host() - Method in interface org.apache.spark.SparkExecutorInfo
 
host() - Method in class org.apache.spark.SparkExecutorInfoImpl
 
host() - Method in class org.apache.spark.status.api.v1.TaskData
 
host() - Method in class org.apache.spark.status.LiveExecutor
 
HOST() - Static method in class org.apache.spark.status.TaskIndexNames
 
host() - Method in class org.apache.spark.storage.BlockManagerId
 
hostId() - Method in class org.apache.spark.scheduler.SparkListenerNodeBlacklisted
 
hostId() - Method in class org.apache.spark.scheduler.SparkListenerNodeBlacklistedForStage
 
hostId() - Method in class org.apache.spark.scheduler.SparkListenerNodeUnblacklisted
 
hostLocation() - Method in class org.apache.spark.scheduler.SplitInfo
 
hostname() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor
 
hostname() - Method in class org.apache.spark.status.LiveExecutor
 
hostPort() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
hostPort() - Method in class org.apache.spark.status.LiveExecutor
 
hostPort() - Method in class org.apache.spark.storage.BlockManagerId
 
hostToLocalTaskCount() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors
 
hour(Column) - Static method in class org.apache.spark.sql.functions
Extracts the hours as an integer from a given date/timestamp/string.
hours() - Static method in class org.apache.spark.scheduler.StatsReportListener
 
html() - Method in class org.apache.spark.status.api.v1.StackTrace
 
htmlResponderToServlet(Function1<HttpServletRequest, Seq<Node>>) - Static method in class org.apache.spark.ui.JettyUtils
 
httpRequest() - Method in interface org.apache.spark.status.api.v1.ApiRequestContext
 
httpResponseCode(URL, String, Seq<Tuple2<String, String>>) - Static method in class org.apache.spark.TestUtils
Returns the response code from an HTTP(S) URL.
hypot(Column, Column) - Static method in class org.apache.spark.sql.functions
Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
hypot(Column, String) - Static method in class org.apache.spark.sql.functions
Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
hypot(String, Column) - Static method in class org.apache.spark.sql.functions
Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
hypot(String, String) - Static method in class org.apache.spark.sql.functions
Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
hypot(Column, double) - Static method in class org.apache.spark.sql.functions
Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
hypot(String, double) - Static method in class org.apache.spark.sql.functions
Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
hypot(double, Column) - Static method in class org.apache.spark.sql.functions
Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
hypot(double, String) - Static method in class org.apache.spark.sql.functions
Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.

I

i() - Method in class org.apache.spark.mllib.linalg.distributed.MatrixEntry
 
id() - Method in class org.apache.spark.Accumulable
Deprecated.
 
id() - Method in interface org.apache.spark.api.java.JavaRDDLike
A unique ID for this RDD (within its SparkContext).
id() - Method in class org.apache.spark.broadcast.Broadcast
 
id() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
 
id() - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering.Assignment
 
id() - Method in class org.apache.spark.mllib.tree.model.Node
 
id() - Method in class org.apache.spark.rdd.RDD
A unique ID for this RDD (within its SparkContext).
id() - Method in class org.apache.spark.scheduler.AccumulableInfo
 
id() - Method in class org.apache.spark.scheduler.TaskInfo
 
id() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Returns the unique id of this query that persists across restarts from checkpoint data.
id() - Method in class org.apache.spark.sql.streaming.StreamingQueryListener.QueryStartedEvent
 
id() - Method in class org.apache.spark.sql.streaming.StreamingQueryListener.QueryTerminatedEvent
 
id() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
 
id() - Method in class org.apache.spark.status.api.v1.AccumulableInfo
 
id() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
 
id() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
id() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
 
id() - Method in class org.apache.spark.storage.RDDInfo
 
id() - Method in class org.apache.spark.streaming.dstream.InputDStream
This is a unique identifier for the input stream.
id() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
 
id() - Method in class org.apache.spark.util.AccumulatorV2
Returns the id of this accumulator, can only be called after registration.
Identifiable - Interface in org.apache.spark.ml.util
:: DeveloperApi ::
Identity$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Identity$
 
IDF - Class in org.apache.spark.ml.feature
Compute the Inverse Document Frequency (IDF) given a collection of documents.
IDF(String) - Constructor for class org.apache.spark.ml.feature.IDF
 
IDF() - Constructor for class org.apache.spark.ml.feature.IDF
 
idf() - Method in class org.apache.spark.ml.feature.IDFModel
Returns the IDF vector.
IDF - Class in org.apache.spark.mllib.feature
Inverse document frequency (IDF).
IDF(int) - Constructor for class org.apache.spark.mllib.feature.IDF
 
IDF() - Constructor for class org.apache.spark.mllib.feature.IDF
 
idf() - Method in class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
Returns the current IDF vector.
idf() - Method in class org.apache.spark.mllib.feature.IDFModel
 
IDF.DocumentFrequencyAggregator - Class in org.apache.spark.mllib.feature
Document frequency aggregator.
IDFBase - Interface in org.apache.spark.ml.feature
Params for IDF and IDFModel.
IDFModel - Class in org.apache.spark.ml.feature
Model fitted by IDF.
IDFModel - Class in org.apache.spark.mllib.feature
Represents an IDF model that can transform term frequency vectors.
ifPartitionNotExists() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
 
ImageDataSource - Class in org.apache.spark.ml.source.image
image package implements Spark SQL data source API for loading image data as DataFrame.
ImageDataSource() - Constructor for class org.apache.spark.ml.source.image.ImageDataSource
 
imageFields() - Static method in class org.apache.spark.ml.image.ImageSchema
 
ImageSchema - Class in org.apache.spark.ml.image
:: Experimental :: Defines the image schema and methods to read and manipulate images.
ImageSchema() - Constructor for class org.apache.spark.ml.image.ImageSchema
 
imageSchema() - Static method in class org.apache.spark.ml.image.ImageSchema
DataFrame with a single column of images named "image" (nullable)
implicitPrefs() - Method in interface org.apache.spark.ml.recommendation.ALSParams
Param to decide whether to use implicit preference.
implicits() - Method in class org.apache.spark.sql.SparkSession
Accessor for nested Scala object
implicits() - Method in class org.apache.spark.sql.SQLContext
Accessor for nested Scala object
implicits$() - Constructor for class org.apache.spark.sql.SparkSession.implicits$
 
implicits$() - Constructor for class org.apache.spark.sql.SQLContext.implicits$
 
improveException(Object, NotSerializableException) - Static method in class org.apache.spark.serializer.SerializationDebugger
Improve the given NotSerializableException with the serialization path leading from the given object to the problematic object.
Impurities - Class in org.apache.spark.mllib.tree.impurity
Factory for Impurity instances.
Impurities() - Constructor for class org.apache.spark.mllib.tree.impurity.Impurities
 
impurity() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
 
impurity() - Method in class org.apache.spark.ml.tree.InternalNode
 
impurity() - Method in class org.apache.spark.ml.tree.LeafNode
 
impurity() - Method in class org.apache.spark.ml.tree.Node
Impurity measure at this node (for training data)
impurity() - Method in interface org.apache.spark.ml.tree.TreeClassifierParams
Criterion used for information gain calculation (case-insensitive).
impurity() - Method in interface org.apache.spark.ml.tree.TreeRegressorParams
Criterion used for information gain calculation (case-insensitive).
impurity() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
Impurity - Interface in org.apache.spark.mllib.tree.impurity
Trait for calculating information gain.
impurity() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
 
impurity() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
 
impurity() - Method in class org.apache.spark.mllib.tree.model.Node
 
impurityStats() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
 
Imputer - Class in org.apache.spark.ml.feature
:: Experimental :: Imputation estimator for completing missing values, either using the mean or the median of the columns in which the missing values are located.
Imputer(String) - Constructor for class org.apache.spark.ml.feature.Imputer
 
Imputer() - Constructor for class org.apache.spark.ml.feature.Imputer
 
ImputerModel - Class in org.apache.spark.ml.feature
:: Experimental :: Model fitted by Imputer.
ImputerParams - Interface in org.apache.spark.ml.feature
Params for Imputer and ImputerModel.
In() - Static method in class org.apache.spark.graphx.EdgeDirection
Edges arriving at a vertex.
In - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff the attribute evaluates to one of the values in the array.
In(String, Object[]) - Constructor for class org.apache.spark.sql.sources.In
 
INACTIVE() - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
 
inArray(Object) - Static method in class org.apache.spark.ml.param.ParamValidators
Check for value in an allowed set of values.
inArray(List<T>) - Static method in class org.apache.spark.ml.param.ParamValidators
Check for value in an allowed set of values.
InBlock$() - Constructor for class org.apache.spark.ml.recommendation.ALS.InBlock$
 
InboxMessage - Interface in org.apache.spark.rpc.netty
 
IncompatibleMergeException - Exception in org.apache.spark.util.sketch
 
IncompatibleMergeException(String) - Constructor for exception org.apache.spark.util.sketch.IncompatibleMergeException
 
incrementFetchedPartitions(int) - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
 
incrementFileCacheHits(int) - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
 
incrementFilesDiscovered(int) - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
 
incrementHiveClientCalls(int) - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
 
incrementParallelListingJobCount(int) - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
 
inDegrees() - Method in class org.apache.spark.graphx.GraphOps
The in-degree of each vertex in the graph.
independence() - Method in class org.apache.spark.mllib.stat.test.ChiSqTest.NullHypothesis$
 
INDETERMINATE() - Static method in class org.apache.spark.rdd.DeterministicLevel
 
index() - Method in class org.apache.spark.ml.attribute.Attribute
Index of the attribute.
INDEX() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
 
index() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
 
index() - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
index() - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
index() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
index(int, int) - Method in interface org.apache.spark.ml.linalg.Matrix
Return the index for the (i, j)-th element in the backing array.
index() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRow
 
index(int, int) - Method in interface org.apache.spark.mllib.linalg.Matrix
Return the index for the (i, j)-th element in the backing array.
index() - Method in interface org.apache.spark.Partition
Get the partition's index within its parent RDD
index() - Method in class org.apache.spark.scheduler.TaskInfo
The index of this task within its task set.
index() - Method in class org.apache.spark.status.api.v1.TaskData
 
IndexedRow - Class in org.apache.spark.mllib.linalg.distributed
Represents a row of IndexedRowMatrix.
IndexedRow(long, Vector) - Constructor for class org.apache.spark.mllib.linalg.distributed.IndexedRow
 
IndexedRowMatrix - Class in org.apache.spark.mllib.linalg.distributed
Represents a row-oriented DistributedMatrix with indexed rows.
IndexedRowMatrix(RDD<IndexedRow>, long, int) - Constructor for class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
 
IndexedRowMatrix(RDD<IndexedRow>) - Constructor for class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
Alternative constructor leaving matrix dimensions to be determined automatically.
indexName(String) - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
indexOf(String) - Method in class org.apache.spark.ml.attribute.AttributeGroup
Index of an attribute specified by name.
indexOf(String) - Method in class org.apache.spark.ml.attribute.NominalAttribute
Index of a specific value.
indexOf(Object) - Method in class org.apache.spark.mllib.feature.HashingTF
Returns the index of the input term.
indexToLevel(int) - Static method in class org.apache.spark.mllib.tree.model.Node
Return the level of a tree which the given node is in.
IndexToString - Class in org.apache.spark.ml.feature
A Transformer that maps a column of indices back to a new column of corresponding string values.
IndexToString(String) - Constructor for class org.apache.spark.ml.feature.IndexToString
 
IndexToString() - Constructor for class org.apache.spark.ml.feature.IndexToString
 
indices() - Method in class org.apache.spark.ml.feature.VectorSlicer
An array of indices to select features from a vector column.
indices() - Method in class org.apache.spark.ml.linalg.SparseVector
 
indices() - Method in class org.apache.spark.mllib.linalg.SparseVector
 
inferSchema(SparkSession, Map<String, String>, Seq<FileStatus>) - Method in class org.apache.spark.sql.hive.execution.HiveFileFormat
 
inferSchema(CatalogTable) - Static method in class org.apache.spark.sql.hive.HiveUtils
Infers the schema for Hive serde tables and returns the CatalogTable with the inferred schema.
inferSchema(SparkSession, Map<String, String>, Seq<FileStatus>) - Method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
info() - Method in class org.apache.spark.status.LiveRDD
 
info() - Method in class org.apache.spark.status.LiveStage
 
info() - Method in class org.apache.spark.status.LiveTask
 
infoChanged(SparkAppHandle) - Method in interface org.apache.spark.launcher.SparkAppHandle.Listener
Callback for changes in any information that is not the handle's state.
infoGain() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
 
InformationGainStats - Class in org.apache.spark.mllib.tree.model
:: DeveloperApi :: Information gain statistics for each split param: gain information gain value param: impurity current node impurity param: leftImpurity left node impurity param: rightImpurity right node impurity param: leftPredict left node predict param: rightPredict right node predict
InformationGainStats(double, double, double, double, Predict, Predict) - Constructor for class org.apache.spark.mllib.tree.model.InformationGainStats
 
init() - Method in interface org.apache.spark.ExecutorPlugin
Initialize the executor plugin.
initcap(Column) - Static method in class org.apache.spark.sql.functions
Returns a new string column by converting the first letter of each word to uppercase.
initDaemon(Logger) - Static method in class org.apache.spark.util.Utils
Utility function that should be called early in main() for daemons to set up some common diagnostic state.
initHadoopOutputMetrics(TaskContext) - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
 
initialHash() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
 
initialize(boolean, SparkConf, org.apache.spark.SecurityManager) - Method in interface org.apache.spark.broadcast.BroadcastFactory
 
initialize(double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
 
initialize(double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
 
initialize(double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
 
initialize(double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
 
initialize(RDD<Tuple2<Object, Vector>>, LDA) - Method in interface org.apache.spark.mllib.clustering.LDAOptimizer
Initializer for the optimizer.
initialize() - Static method in class org.apache.spark.rdd.InputFileBlockHolder
Initializes thread local by explicitly getting the value.
initialize(TaskScheduler, SchedulerBackend) - Method in interface org.apache.spark.scheduler.ExternalClusterManager
Initialize task scheduler and backend scheduler.
initialize(MutableAggregationBuffer) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
Initializes the given aggregation buffer, i.e.
Initialized() - Static method in class org.apache.spark.rdd.CheckpointState
 
initializeLogging(boolean, boolean) - Method in interface org.apache.spark.internal.Logging
 
initializeLogIfNecessary(boolean) - Method in interface org.apache.spark.internal.Logging
 
initializeLogIfNecessary(boolean, boolean) - Method in interface org.apache.spark.internal.Logging
 
initialState(RDD<Tuple2<KeyType, StateType>>) - Method in class org.apache.spark.streaming.StateSpec
Set the RDD containing the initial states that will be used by mapWithState
initialState(JavaPairRDD<KeyType, StateType>) - Method in class org.apache.spark.streaming.StateSpec
Set the RDD containing the initial states that will be used by mapWithState
initialValue() - Method in class org.apache.spark.partial.PartialResult
 
initialWeights() - Method in interface org.apache.spark.ml.classification.MultilayerPerceptronParams
The initial weights of the model.
initInputSerDe(Seq<Expression>) - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
initMode() - Method in interface org.apache.spark.ml.clustering.KMeansParams
Param for the initialization algorithm.
initMode() - Method in interface org.apache.spark.ml.clustering.PowerIterationClusteringParams
Param for the initialization algorithm.
initModel(DenseVector<Object>, Random) - Method in interface org.apache.spark.ml.ann.Layer
Returns the instance of the layer with random generated weights.
initOutputFormat(JobContext) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
 
initOutputSerDe(Seq<Attribute>) - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
initSteps() - Method in interface org.apache.spark.ml.clustering.KMeansParams
Param for the number of steps for the k-means|| initialization mode.
initWriter(TaskAttemptContext, int) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
 
injectCheckRule(Function1<SparkSession, Function1<LogicalPlan, BoxedUnit>>) - Method in class org.apache.spark.sql.SparkSessionExtensions
Inject an check analysis Rule builder into the SparkSession.
injectOptimizerRule(Function1<SparkSession, Rule<LogicalPlan>>) - Method in class org.apache.spark.sql.SparkSessionExtensions
Inject an optimizer Rule builder into the SparkSession.
injectParser(Function2<SparkSession, ParserInterface, ParserInterface>) - Method in class org.apache.spark.sql.SparkSessionExtensions
Inject a custom parser into the SparkSession.
injectPlannerStrategy(Function1<SparkSession, SparkStrategy>) - Method in class org.apache.spark.sql.SparkSessionExtensions
Inject a planner Strategy builder into the SparkSession.
injectPostHocResolutionRule(Function1<SparkSession, Rule<LogicalPlan>>) - Method in class org.apache.spark.sql.SparkSessionExtensions
Inject an analyzer Rule builder into the SparkSession.
injectResolutionRule(Function1<SparkSession, Rule<LogicalPlan>>) - Method in class org.apache.spark.sql.SparkSessionExtensions
Inject an analyzer resolution Rule builder into the SparkSession.
InnerClosureFinder - Class in org.apache.spark.util
 
InnerClosureFinder(Set<Class<?>>) - Constructor for class org.apache.spark.util.InnerClosureFinder
 
innerJoin(EdgeRDD<ED2>, Function4<Object, Object, ED, ED2, ED3>, ClassTag<ED2>, ClassTag<ED3>) - Method in class org.apache.spark.graphx.EdgeRDD
Inner joins this EdgeRDD with another EdgeRDD, assuming both are partitioned using the same PartitionStrategy.
innerJoin(EdgeRDD<ED2>, Function4<Object, Object, ED, ED2, ED3>, ClassTag<ED2>, ClassTag<ED3>) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
innerJoin(RDD<Tuple2<Object, U>>, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
innerJoin(RDD<Tuple2<Object, U>>, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
Inner joins this VertexRDD with an RDD containing vertex attribute pairs.
innerZipJoin(VertexRDD<U>, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
innerZipJoin(VertexRDD<U>, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
Efficiently inner joins this VertexRDD with another VertexRDD sharing the same index.
inPlace() - Method in interface org.apache.spark.ml.ann.Layer
If true, the memory is not allocated for the output of this layer.
InProcessLauncher - Class in org.apache.spark.launcher
In-process launcher for Spark applications.
InProcessLauncher() - Constructor for class org.apache.spark.launcher.InProcessLauncher
 
input() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
 
INPUT() - Static method in class org.apache.spark.ui.ToolTips
 
input$() - Constructor for class org.apache.spark.InternalAccumulator.input$
 
input_file_name() - Static method in class org.apache.spark.sql.functions
Creates a string column for the file name of the current Spark task.
INPUT_FORMAT() - Static method in class org.apache.spark.sql.hive.execution.HiveOptions
 
INPUT_METRICS_PREFIX() - Static method in class org.apache.spark.InternalAccumulator
 
INPUT_RECORDS() - Static method in class org.apache.spark.status.TaskIndexNames
 
INPUT_SIZE() - Static method in class org.apache.spark.status.TaskIndexNames
 
inputBytes() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
inputBytes() - Method in class org.apache.spark.status.api.v1.StageData
 
inputCol() - Method in interface org.apache.spark.ml.param.shared.HasInputCol
Param for input column name.
inputCols() - Method in interface org.apache.spark.ml.param.shared.HasInputCols
Param for input column names.
inputDStream() - Method in class org.apache.spark.streaming.api.java.JavaInputDStream
 
inputDStream() - Method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
 
InputDStream<T> - Class in org.apache.spark.streaming.dstream
This is the abstract base class for all input streams.
InputDStream(StreamingContext, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.InputDStream
 
InputFileBlockHolder - Class in org.apache.spark.rdd
This holds file names of the current Spark task.
InputFileBlockHolder() - Constructor for class org.apache.spark.rdd.InputFileBlockHolder
 
inputFiles() - Method in class org.apache.spark.sql.Dataset
Returns a best-effort snapshot of the files that compose this Dataset.
inputFormat() - Method in class org.apache.spark.sql.hive.execution.HiveOptions
 
inputFormatClazz() - Method in class org.apache.spark.scheduler.InputFormatInfo
 
inputFormatClazz() - Method in class org.apache.spark.scheduler.SplitInfo
 
InputFormatInfo - Class in org.apache.spark.scheduler
:: DeveloperApi :: Parses and holds information about inputFormat (and files) specified as a parameter.
InputFormatInfo(Configuration, Class<?>, String) - Constructor for class org.apache.spark.scheduler.InputFormatInfo
 
InputMetricDistributions - Class in org.apache.spark.status.api.v1
 
InputMetrics - Class in org.apache.spark.status.api.v1
 
inputMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
inputMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 
InputPartition<T> - Interface in org.apache.spark.sql.sources.v2.reader
An input partition returned by DataSourceReader.planInputPartitions() and is responsible for creating the actual data reader of one RDD partition.
InputPartitionReader<T> - Interface in org.apache.spark.sql.sources.v2.reader
An input partition reader returned by InputPartition.createPartitionReader() and is responsible for outputting data for a RDD partition.
inputRecords() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
inputRecords() - Method in class org.apache.spark.status.api.v1.StageData
 
inputRowFormat() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
inputRowFormatMap() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
inputRowsPerSecond() - Method in class org.apache.spark.sql.streaming.SourceProgress
 
inputRowsPerSecond() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
The aggregate (across all sources) rate of data arriving.
inputSchema() - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
A StructType represents data types of input arguments of this aggregate function.
inputSerdeClass() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
inputSerdeProps() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
inputSize() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
 
inputStreamId() - Method in class org.apache.spark.streaming.scheduler.StreamInputInfo
 
inputTypes() - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
 
inRange(double, double, boolean, boolean) - Static method in class org.apache.spark.ml.param.ParamValidators
Check for value in range lowerBound to upperBound.
inRange(double, double) - Static method in class org.apache.spark.ml.param.ParamValidators
Version of `inRange()` which uses inclusive be default: [lowerBound, upperBound]
insert(Dataset<Row>, boolean) - Method in interface org.apache.spark.sql.sources.InsertableRelation
 
InsertableRelation - Interface in org.apache.spark.sql.sources
A BaseRelation that can be used to insert data into it through the insert method.
insertInto(String) - Method in class org.apache.spark.sql.DataFrameWriter
Inserts the content of the DataFrame to the specified table.
InsertIntoHiveDirCommand - Class in org.apache.spark.sql.hive.execution
Command for writing the results of query to file system.
InsertIntoHiveDirCommand(boolean, CatalogStorageFormat, LogicalPlan, boolean, Seq<String>) - Constructor for class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
 
InsertIntoHiveTable - Class in org.apache.spark.sql.hive.execution
Command for writing data out to a Hive table.
InsertIntoHiveTable(CatalogTable, Map<String, Option<String>>, LogicalPlan, boolean, boolean, Seq<String>) - Constructor for class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
 
inShutdown() - Static method in class org.apache.spark.util.ShutdownHookManager
Detect whether this thread might be executing a shutdown hook.
inspectorToDataType(ObjectInspector) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
inspectorToDataType(ObjectInspector) - Static method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
instance() - Static method in class org.apache.spark.mllib.tree.impurity.Entropy
Get this impurity instance.
instance() - Static method in class org.apache.spark.mllib.tree.impurity.Gini
Get this impurity instance.
instance() - Static method in class org.apache.spark.mllib.tree.impurity.Variance
Get this impurity instance.
INSTANCE - Static variable in class org.apache.spark.serializer.DummySerializerInstance
 
instantiate(String, String, String, boolean) - Static method in class org.apache.spark.internal.io.FileCommitProtocol
Instantiates a FileCommitProtocol using the given className.
instr(Column, String) - Static method in class org.apache.spark.sql.functions
Locate the position of the first occurrence of substr column in the given string.
INT() - Static method in class org.apache.spark.sql.Encoders
An encoder for nullable int type.
intAccumulator(int) - Method in class org.apache.spark.api.java.JavaSparkContext
Deprecated.
use sc().longAccumulator(). Since 2.0.0.
intAccumulator(int, String) - Method in class org.apache.spark.api.java.JavaSparkContext
Deprecated.
use sc().longAccumulator(String). Since 2.0.0.
IntAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.IntAccumulatorParam$
Deprecated.
 
IntArrayParam - Class in org.apache.spark.ml.param
:: DeveloperApi :: Specialized version of Param[Array[Int} for Java.
IntArrayParam(Params, String, String, Function1<int[], Object>) - Constructor for class org.apache.spark.ml.param.IntArrayParam
 
IntArrayParam(Params, String, String) - Constructor for class org.apache.spark.ml.param.IntArrayParam
 
IntegerType - Static variable in class org.apache.spark.sql.types.DataTypes
Gets the IntegerType object.
IntegerType - Class in org.apache.spark.sql.types
The data type representing Int values.
IntegerType() - Constructor for class org.apache.spark.sql.types.IntegerType
 
INTER_JOB_WAIT_MS() - Static method in class org.apache.spark.ui.UIWorkloadGenerator
 
InteractableTerm - Interface in org.apache.spark.ml.feature
A term that may be part of an interaction, e.g.
Interaction - Class in org.apache.spark.ml.feature
Implements the feature interaction transform.
Interaction(String) - Constructor for class org.apache.spark.ml.feature.Interaction
 
Interaction() - Constructor for class org.apache.spark.ml.feature.Interaction
 
intercept() - Method in class org.apache.spark.ml.classification.LinearSVCModel
 
intercept() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
The model intercept for "binomial" logistic regression.
intercept() - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
intercept() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
 
intercept() - Method in class org.apache.spark.ml.regression.LinearRegressionModel
 
intercept() - Method in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$.Data
 
intercept() - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
 
intercept() - Method in class org.apache.spark.mllib.classification.SVMModel
 
intercept() - Method in class org.apache.spark.mllib.regression.GeneralizedLinearModel
 
intercept() - Method in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$.Data
 
intercept() - Method in class org.apache.spark.mllib.regression.LassoModel
 
intercept() - Method in class org.apache.spark.mllib.regression.LinearRegressionModel
 
intercept() - Method in class org.apache.spark.mllib.regression.RidgeRegressionModel
 
interceptVector() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
 
intermediateStorageLevel() - Method in interface org.apache.spark.ml.recommendation.ALSParams
Param for StorageLevel for intermediate datasets.
InternalAccumulator - Class in org.apache.spark
A collection of fields and methods concerned with internal accumulators that represent task level metrics.
InternalAccumulator() - Constructor for class org.apache.spark.InternalAccumulator
 
InternalAccumulator.input$ - Class in org.apache.spark
 
InternalAccumulator.output$ - Class in org.apache.spark
 
InternalAccumulator.shuffleRead$ - Class in org.apache.spark
 
InternalAccumulator.shuffleWrite$ - Class in org.apache.spark
 
InternalKMeansModelWriter - Class in org.apache.spark.ml.clustering
A writer for KMeans that handles the "internal" (or default) format
InternalKMeansModelWriter() - Constructor for class org.apache.spark.ml.clustering.InternalKMeansModelWriter
 
InternalLinearRegressionModelWriter - Class in org.apache.spark.ml.regression
A writer for LinearRegression that handles the "internal" (or default) format
InternalLinearRegressionModelWriter() - Constructor for class org.apache.spark.ml.regression.InternalLinearRegressionModelWriter
 
InternalNode - Class in org.apache.spark.ml.tree
Internal Decision Tree node.
InterruptibleIterator<T> - Class in org.apache.spark
:: DeveloperApi :: An iterator that wraps around an existing iterator to provide task killing functionality.
InterruptibleIterator(TaskContext, Iterator<T>) - Constructor for class org.apache.spark.InterruptibleIterator
 
interruptThread() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask
 
interruptThread() - Method in class org.apache.spark.scheduler.local.KillTask
 
intersect(Dataset<T>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset containing rows only in both this Dataset and another Dataset.
intersectAll(Dataset<T>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset containing rows only in both this Dataset and another Dataset while preserving the duplicates.
intersection(JavaDoubleRDD) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return the intersection of this RDD and another one.
intersection(JavaPairRDD<K, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
Return the intersection of this RDD and another one.
intersection(JavaRDD<T>) - Method in class org.apache.spark.api.java.JavaRDD
Return the intersection of this RDD and another one.
intersection(RDD<T>) - Method in class org.apache.spark.rdd.RDD
Return the intersection of this RDD and another one.
intersection(RDD<T>, Partitioner, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
Return the intersection of this RDD and another one.
intersection(RDD<T>, int) - Method in class org.apache.spark.rdd.RDD
Return the intersection of this RDD and another one.
intervalMs() - Method in class org.apache.spark.sql.streaming.ProcessingTime
Deprecated.
 
IntParam - Class in org.apache.spark.ml.param
:: DeveloperApi :: Specialized version of Param[Int] for Java.
IntParam(String, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.IntParam
 
IntParam(String, String, String) - Constructor for class org.apache.spark.ml.param.IntParam
 
IntParam(Identifiable, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.IntParam
 
IntParam(Identifiable, String, String) - Constructor for class org.apache.spark.ml.param.IntParam
 
IntParam - Class in org.apache.spark.util
An extractor object for parsing strings into integers.
IntParam() - Constructor for class org.apache.spark.util.IntParam
 
invalidateSerializedMapOutputStatusCache() - Method in class org.apache.spark.ShuffleStatus
Clears the cached serialized map output statuses.
inverse() - Method in class org.apache.spark.ml.feature.DCT
Indicates whether to perform the inverse DCT (true) or forward DCT (false).
inverse(double[], int) - Static method in class org.apache.spark.mllib.linalg.CholeskyDecomposition
Computes the inverse of a real symmetric positive definite matrix A using the Cholesky factorization A = U**T*U.
Inverse$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Inverse$
 
invokedMethod(Object, Class<?>, String) - Static method in class org.apache.spark.graphx.util.BytecodeUtils
Test whether the given closure invokes the specified method in the specified class.
invokeWriteReplace(Object) - Method in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
 
ioEncryptionKey() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SparkAppConfig
 
ioschema() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
 
is32BitDecimalType(DataType) - Static method in class org.apache.spark.sql.types.DecimalType
Returns if dt is a DecimalType that fits inside an int
is64BitDecimalType(DataType) - Static method in class org.apache.spark.sql.types.DecimalType
Returns if dt is a DecimalType that fits inside a long
isActive() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Returns true if this query is actively running.
isActive() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
isActive() - Method in class org.apache.spark.status.api.v1.streaming.ReceiverInfo
 
isActive() - Method in class org.apache.spark.status.LiveExecutor
 
isAddIntercept() - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
Get if the algorithm uses addIntercept
isAllowed(Enumeration.Value, Enumeration.Value) - Static method in class org.apache.spark.scheduler.TaskLocality
 
isBatchingEnabled(SparkConf, boolean) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
isBindCollision(Throwable) - Static method in class org.apache.spark.util.Utils
Return whether the exception is caused by an address-port collision when binding.
isBlacklisted() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
isBlacklisted() - Method in class org.apache.spark.status.LiveExecutor
 
isBlacklisted() - Method in class org.apache.spark.status.LiveExecutorStageSummary
 
isBlacklistedForStage() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
isBroadcast() - Method in class org.apache.spark.storage.BlockId
 
isBucket() - Method in class org.apache.spark.sql.catalog.Column
 
isByteArrayDecimalType(DataType) - Static method in class org.apache.spark.sql.types.DecimalType
Returns if dt is a DecimalType that doesn't fit inside a long
isCached(String) - Method in class org.apache.spark.sql.catalog.Catalog
Returns true if the table is currently cached in-memory.
isCached(String) - Method in class org.apache.spark.sql.SQLContext
Returns true if the table is currently cached in-memory.
isCached() - Method in class org.apache.spark.storage.BlockStatus
 
isCached() - Method in class org.apache.spark.storage.RDDInfo
 
isCancelled() - Method in class org.apache.spark.ComplexFutureAction
 
isCancelled() - Method in interface org.apache.spark.FutureAction
Returns whether the action has been cancelled.
isCancelled() - Method in class org.apache.spark.SimpleFutureAction
 
isCascadingTruncateTable() - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
 
isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
 
isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
 
isCascadingTruncateTable() - Method in class org.apache.spark.sql.jdbc.JdbcDialect
Return Some[true] iff TRUNCATE TABLE causes cascading default.
isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
 
isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.NoopDialect
 
isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
 
isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
isCheckpointed() - Method in interface org.apache.spark.api.java.JavaRDDLike
Return whether this RDD has been checkpointed or not
isCheckpointed() - Method in class org.apache.spark.graphx.Graph
Return whether this Graph has been checkpointed or not.
isCheckpointed() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
isCheckpointed() - Method in class org.apache.spark.graphx.impl.GraphImpl
 
isCheckpointed() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
isCheckpointed() - Method in class org.apache.spark.rdd.RDD
Return whether this RDD is checkpointed and materialized, either reliably or locally.
isCliSessionState() - Static method in class org.apache.spark.sql.hive.HiveUtils
Check current Thread's SessionState type
isColMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
Indicates whether the values backing this matrix are arranged in column major order.
isCompatible(BloomFilter) - Method in class org.apache.spark.util.sketch.BloomFilter
Determines whether a given bloom filter is compatible with this bloom filter.
isCompleted() - Method in class org.apache.spark.BarrierTaskContext
 
isCompleted() - Method in class org.apache.spark.ComplexFutureAction
 
isCompleted() - Method in interface org.apache.spark.FutureAction
Returns whether the action has already been completed with a value or an exception.
isCompleted() - Method in class org.apache.spark.SimpleFutureAction
 
isCompleted() - Method in class org.apache.spark.TaskContext
Returns true if the task has completed.
isDataAvailable() - Method in class org.apache.spark.sql.streaming.StreamingQueryStatus
 
isDefined(Param<?>) - Method in interface org.apache.spark.ml.param.Params
Checks whether a param is explicitly set or has a default value.
isDistributed() - Method in class org.apache.spark.ml.clustering.DistributedLDAModel
 
isDistributed() - Method in class org.apache.spark.ml.clustering.LDAModel
Indicates whether this instance is of type DistributedLDAModel
isDistributed() - Method in class org.apache.spark.ml.clustering.LocalLDAModel
 
isDriver() - Method in class org.apache.spark.storage.BlockManagerId
 
isDynamicAllocationEnabled(SparkConf) - Static method in class org.apache.spark.util.Utils
Return whether dynamic allocation is enabled in the given conf.
isEmpty() - Method in interface org.apache.spark.api.java.JavaRDDLike
 
isEmpty() - Method in class org.apache.spark.rdd.RDD
 
isEmpty() - Method in class org.apache.spark.sql.Dataset
Returns true if the Dataset is empty.
isExecutorStartupConf(String) - Static method in class org.apache.spark.SparkConf
Return whether the given config should be passed to an executor on start-up.
isExperiment() - Method in class org.apache.spark.mllib.stat.test.BinarySample
 
isFailed(Enumeration.Value) - Static method in class org.apache.spark.TaskState
 
isFatalError(Throwable) - Static method in class org.apache.spark.util.Utils
Returns true if the given exception was fatal.
isFile(Path) - Static method in class org.apache.spark.ml.image.SamplePathFilter
 
isFinal() - Method in enum org.apache.spark.launcher.SparkAppHandle.State
Whether this state is a final state, meaning the application is not running anymore once it's reached.
isFinished(Enumeration.Value) - Static method in class org.apache.spark.TaskState
 
isIgnorableException(Throwable) - Method in interface org.apache.spark.util.ListenerBus
Allows bus implementations to prevent error logging for certain exceptions.
isin(Object...) - Method in class org.apache.spark.sql.Column
A boolean expression that is evaluated to true if the value of this expression is contained by the evaluated values of the arguments.
isin(Seq<Object>) - Method in class org.apache.spark.sql.Column
A boolean expression that is evaluated to true if the value of this expression is contained by the evaluated values of the arguments.
isInCollection(Iterable<?>) - Method in class org.apache.spark.sql.Column
A boolean expression that is evaluated to true if the value of this expression is contained by the provided collection.
isInCollection(Iterable<?>) - Method in class org.apache.spark.sql.Column
A boolean expression that is evaluated to true if the value of this expression is contained by the provided collection.
isInDirectory(File, File) - Static method in class org.apache.spark.util.Utils
Return whether the specified file is a parent directory of the child file.
isInitialValueFinal() - Method in class org.apache.spark.partial.PartialResult
 
isInterrupted() - Method in class org.apache.spark.BarrierTaskContext
 
isInterrupted() - Method in class org.apache.spark.TaskContext
Returns true if the task has been killed.
isLargerBetter() - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
 
isLargerBetter() - Method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
isLargerBetter() - Method in class org.apache.spark.ml.evaluation.Evaluator
Indicates whether the metric returned by evaluate should be maximized (true, default) or minimized (false).
isLargerBetter() - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
 
isLargerBetter() - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
 
isLeaf() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
 
isLeaf() - Method in class org.apache.spark.mllib.tree.model.Node
 
isLeftChild(int) - Static method in class org.apache.spark.mllib.tree.model.Node
Returns true if this is a left child.
isLocal() - Method in class org.apache.spark.api.java.JavaSparkContext
 
isLocal() - Method in class org.apache.spark.SparkContext
 
isLocal() - Method in class org.apache.spark.sql.Dataset
Returns true if the collect and take methods can be run locally (without any Spark executors).
isLocal() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
 
isLocalMaster(SparkConf) - Static method in class org.apache.spark.util.Utils
 
isMac() - Static method in class org.apache.spark.util.Utils
Whether the underlying operating system is Mac OS X.
isModifiable(String) - Method in class org.apache.spark.sql.RuntimeConfig
Indicates whether the configuration property with the given key is modifiable in the current session.
isMulticlassClassification() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
isMulticlassWithCategoricalFeatures() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
isMultipleOf(Duration) - Method in class org.apache.spark.streaming.Duration
 
isMultipleOf(Duration) - Method in class org.apache.spark.streaming.Time
 
isNaN() - Method in class org.apache.spark.sql.Column
True if the current expression is NaN.
isnan(Column) - Static method in class org.apache.spark.sql.functions
Return true iff the column is NaN.
isNominal() - Method in class org.apache.spark.ml.attribute.Attribute
Tests whether this attribute is nominal, true for NominalAttribute and BinaryAttribute.
isNominal() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
 
isNominal() - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
isNominal() - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
isNominal() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
isNotNull() - Method in class org.apache.spark.sql.Column
True if the current expression is NOT null.
IsNotNull - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff the attribute evaluates to a non-null value.
IsNotNull(String) - Constructor for class org.apache.spark.sql.sources.IsNotNull
 
isNull() - Method in class org.apache.spark.sql.Column
True if the current expression is null.
isnull(Column) - Static method in class org.apache.spark.sql.functions
Return true iff the column is null.
IsNull - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff the attribute evaluates to null.
IsNull(String) - Constructor for class org.apache.spark.sql.sources.IsNull
 
isNullAt(int) - Method in interface org.apache.spark.sql.Row
Checks whether the value at position i is null.
isNullAt(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
isNullAt(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
isNullAt(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
isNullAt(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns whether the value at rowId is NULL.
isNumeric() - Method in class org.apache.spark.ml.attribute.Attribute
Tests whether this attribute is numeric, true for NumericAttribute and BinaryAttribute.
isNumeric() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
 
isNumeric() - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
isNumeric() - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
isNumeric() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
isOpen() - Method in class org.apache.spark.security.CryptoStreamUtils.ErrorHandlingReadableChannel
 
isOpen() - Method in class org.apache.spark.storage.CountingWritableChannel
 
isOrdinal() - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
isotonic() - Method in interface org.apache.spark.ml.regression.IsotonicRegressionBase
Param for whether the output sequence should be isotonic/increasing (true) or antitonic/decreasing (false).
isotonic() - Method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
 
IsotonicRegression - Class in org.apache.spark.ml.regression
Isotonic regression.
IsotonicRegression(String) - Constructor for class org.apache.spark.ml.regression.IsotonicRegression
 
IsotonicRegression() - Constructor for class org.apache.spark.ml.regression.IsotonicRegression
 
IsotonicRegression - Class in org.apache.spark.mllib.regression
Isotonic regression.
IsotonicRegression() - Constructor for class org.apache.spark.mllib.regression.IsotonicRegression
Constructs IsotonicRegression instance with default parameter isotonic = true.
IsotonicRegressionBase - Interface in org.apache.spark.ml.regression
Params for isotonic regression.
IsotonicRegressionModel - Class in org.apache.spark.ml.regression
Model fitted by IsotonicRegression.
IsotonicRegressionModel - Class in org.apache.spark.mllib.regression
Regression model for isotonic regression.
IsotonicRegressionModel(double[], double[], boolean) - Constructor for class org.apache.spark.mllib.regression.IsotonicRegressionModel
 
IsotonicRegressionModel(Iterable<Object>, Iterable<Object>, Boolean) - Constructor for class org.apache.spark.mllib.regression.IsotonicRegressionModel
A Java-friendly constructor that takes two Iterable parameters and one Boolean parameter.
isOutputSpecValidationEnabled(SparkConf) - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
 
isPartition() - Method in class org.apache.spark.sql.catalog.Column
 
isPresent() - Method in class org.apache.spark.api.java.Optional
 
isRDD() - Method in class org.apache.spark.storage.BlockId
 
isReady() - Method in interface org.apache.spark.scheduler.SchedulerBackend
 
isRegistered() - Method in class org.apache.spark.util.AccumulatorV2
Returns true if this accumulator has been registered.
isRInstalled() - Static method in class org.apache.spark.api.r.RUtils
Check if R is installed before running tests that use R commands.
isRowMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
Indicates whether the values backing this matrix are arranged in row major order.
isRunningLocally() - Method in class org.apache.spark.BarrierTaskContext
 
isRunningLocally() - Method in class org.apache.spark.TaskContext
Deprecated.
Local execution was removed, so this always returns false. Since 2.0.0.
isSet(Param<?>) - Method in interface org.apache.spark.ml.param.Params
Checks whether a param is explicitly set.
isShuffle() - Method in class org.apache.spark.storage.BlockId
 
isSparkPortConf(String) - Static method in class org.apache.spark.SparkConf
Return true if the given config matches either spark.*.port or spark.port.*.
isSparkRInstalled() - Static method in class org.apache.spark.api.r.RUtils
Check if SparkR is installed before running tests that use SparkR.
isSplitable(SparkSession, Map<String, String>, Path) - Method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
isStarted() - Method in class org.apache.spark.streaming.receiver.Receiver
Check if the receiver has started or not.
isStopped() - Method in class org.apache.spark.SparkContext
 
isStopped() - Method in class org.apache.spark.streaming.receiver.Receiver
Check if receiver has been marked for stopping.
isStreaming() - Method in class org.apache.spark.sql.Dataset
Returns true if this Dataset contains one or more sources that continuously return data as it arrives.
isSubClassOf(Type, Class<?>) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
isTemporary() - Method in class org.apache.spark.sql.catalog.Function
 
isTemporary() - Method in class org.apache.spark.sql.catalog.Table
 
isTesting() - Static method in class org.apache.spark.util.Utils
Indicates whether Spark is currently running unit tests.
isTimingOut() - Method in class org.apache.spark.streaming.State
Whether the state is timing out and going to be removed by the system after the current batch.
isTraceEnabled() - Method in interface org.apache.spark.internal.Logging
 
isTransposed() - Method in class org.apache.spark.ml.linalg.DenseMatrix
 
isTransposed() - Method in interface org.apache.spark.ml.linalg.Matrix
Flag that keeps track whether the matrix is transposed or not.
isTransposed() - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
isTransposed() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
 
isTransposed() - Method in interface org.apache.spark.mllib.linalg.Matrix
Flag that keeps track whether the matrix is transposed or not.
isTransposed() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
isTriggerActive() - Method in class org.apache.spark.sql.streaming.StreamingQueryStatus
 
isValid() - Method in class org.apache.spark.ml.param.Param
 
isValid() - Method in class org.apache.spark.storage.StorageLevel
 
isWindows() - Static method in class org.apache.spark.util.Utils
Whether the underlying operating system is Windows.
isZero() - Method in class org.apache.spark.sql.types.Decimal
 
isZero() - Method in class org.apache.spark.streaming.Duration
 
isZero() - Method in class org.apache.spark.util.AccumulatorV2
Returns if this accumulator is zero value or not.
isZero() - Method in class org.apache.spark.util.CollectionAccumulator
Returns false if this accumulator instance has any values in it.
isZero() - Method in class org.apache.spark.util.DoubleAccumulator
Returns false if this accumulator has had any values added to it or the sum is non-zero.
isZero() - Method in class org.apache.spark.util.LegacyAccumulatorWrapper
 
isZero() - Method in class org.apache.spark.util.LongAccumulator
Returns false if this accumulator has had any values added to it or the sum is non-zero.
item() - Method in class org.apache.spark.ml.recommendation.ALS.Rating
 
itemCol() - Method in interface org.apache.spark.ml.recommendation.ALSModelParams
Param for the column name for item ids.
itemFactors() - Method in class org.apache.spark.ml.recommendation.ALSModel
 
items() - Method in class org.apache.spark.mllib.fpm.FPGrowth.FreqItemset
 
itemsCol() - Method in interface org.apache.spark.ml.fpm.FPGrowthParams
Items column name.
itemSupport() - Method in class org.apache.spark.mllib.fpm.FPGrowthModel
 
iterator(Partition, TaskContext) - Method in interface org.apache.spark.api.java.JavaRDDLike
Internal method to this RDD; will read from cache if applicable, or otherwise compute it.
iterator(Partition, TaskContext) - Method in class org.apache.spark.rdd.RDD
Internal method to this RDD; will read from cache if applicable, or otherwise compute it.
iterator() - Method in class org.apache.spark.sql.types.StructType
 
iterator() - Method in class org.apache.spark.status.RDDPartitionSeq
 
IV_LENGTH_IN_BYTES() - Static method in class org.apache.spark.security.CryptoStreamUtils
 

J

j() - Method in class org.apache.spark.mllib.linalg.distributed.MatrixEntry
 
jarOfClass(Class<?>) - Static method in class org.apache.spark.api.java.JavaSparkContext
Find the JAR from which a given class was loaded, to make it easy for users to pass their JARs to SparkContext.
jarOfClass(Class<?>) - Static method in class org.apache.spark.SparkContext
Find the JAR from which a given class was loaded, to make it easy for users to pass their JARs to SparkContext.
jarOfClass(Class<?>) - Static method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Find the JAR from which a given class was loaded, to make it easy for users to pass their JARs to StreamingContext.
jarOfClass(Class<?>) - Static method in class org.apache.spark.streaming.StreamingContext
Find the JAR from which a given class was loaded, to make it easy for users to pass their JARs to StreamingContext.
jarOfObject(Object) - Static method in class org.apache.spark.api.java.JavaSparkContext
Find the JAR that contains the class of a particular object, to make it easy for users to pass their JARs to SparkContext.
jarOfObject(Object) - Static method in class org.apache.spark.SparkContext
Find the JAR that contains the class of a particular object, to make it easy for users to pass their JARs to SparkContext.
jars() - Method in class org.apache.spark.api.java.JavaSparkContext
 
jars() - Method in class org.apache.spark.SparkContext
 
javaAntecedent() - Method in class org.apache.spark.mllib.fpm.AssociationRules.Rule
Returns antecedent in a Java List.
javaCategoryMaps() - Method in class org.apache.spark.ml.feature.VectorIndexerModel
Java-friendly version of categoryMaps
javaConsequent() - Method in class org.apache.spark.mllib.fpm.AssociationRules.Rule
Returns consequent in a Java List.
JavaDoubleRDD - Class in org.apache.spark.api.java
 
JavaDoubleRDD(RDD<Object>) - Constructor for class org.apache.spark.api.java.JavaDoubleRDD
 
JavaDStream<T> - Class in org.apache.spark.streaming.api.java
A Java-friendly interface to DStream, the basic abstraction in Spark Streaming that represents a continuous stream of data.
JavaDStream(DStream<T>, ClassTag<T>) - Constructor for class org.apache.spark.streaming.api.java.JavaDStream
 
JavaDStreamLike<T,This extends JavaDStreamLike<T,This,R>,R extends JavaRDDLike<T,R>> - Interface in org.apache.spark.streaming.api.java
 
JavaFutureAction<T> - Interface in org.apache.spark.api.java
 
JavaHadoopRDD<K,V> - Class in org.apache.spark.api.java
 
JavaHadoopRDD(HadoopRDD<K, V>, ClassTag<K>, ClassTag<V>) - Constructor for class org.apache.spark.api.java.JavaHadoopRDD
 
javaHome() - Method in class org.apache.spark.status.api.v1.RuntimeInfo
 
JavaInputDStream<T> - Class in org.apache.spark.streaming.api.java
A Java-friendly interface to InputDStream.
JavaInputDStream(InputDStream<T>, ClassTag<T>) - Constructor for class org.apache.spark.streaming.api.java.JavaInputDStream
 
javaItems() - Method in class org.apache.spark.mllib.fpm.FPGrowth.FreqItemset
Returns items in a Java List.
JavaIterableWrapperSerializer - Class in org.apache.spark.serializer
A Kryo serializer for serializing results returned by asJavaIterable.
JavaIterableWrapperSerializer() - Constructor for class org.apache.spark.serializer.JavaIterableWrapperSerializer
 
JavaMapWithStateDStream<KeyType,ValueType,StateType,MappedType> - Class in org.apache.spark.streaming.api.java
:: Experimental :: DStream representing the stream of data generated by mapWithState operation on a JavaPairDStream.
JavaNewHadoopRDD<K,V> - Class in org.apache.spark.api.java
 
JavaNewHadoopRDD(NewHadoopRDD<K, V>, ClassTag<K>, ClassTag<V>) - Constructor for class org.apache.spark.api.java.JavaNewHadoopRDD
 
javaOcvTypes() - Static method in class org.apache.spark.ml.image.ImageSchema
(Java-specific) OpenCV type mapping supported
JavaPackage - Class in org.apache.spark.mllib
A dummy class as a workaround to show the package doc of spark.mllib in generated Java API docs.
JavaPairDStream<K,V> - Class in org.apache.spark.streaming.api.java
A Java-friendly interface to a DStream of key-value pairs, which provides extra methods like reduceByKey and join.
JavaPairDStream(DStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Constructor for class org.apache.spark.streaming.api.java.JavaPairDStream
 
JavaPairInputDStream<K,V> - Class in org.apache.spark.streaming.api.java
A Java-friendly interface to InputDStream of key-value pairs.
JavaPairInputDStream(InputDStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Constructor for class org.apache.spark.streaming.api.java.JavaPairInputDStream
 
JavaPairRDD<K,V> - Class in org.apache.spark.api.java
 
JavaPairRDD(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Constructor for class org.apache.spark.api.java.JavaPairRDD
 
JavaPairReceiverInputDStream<K,V> - Class in org.apache.spark.streaming.api.java
A Java-friendly interface to ReceiverInputDStream, the abstract class for defining any input stream that receives data over the network.
JavaPairReceiverInputDStream(ReceiverInputDStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Constructor for class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
 
JavaParams - Class in org.apache.spark.ml.param
:: DeveloperApi :: Java-friendly wrapper for Params.
JavaParams() - Constructor for class org.apache.spark.ml.param.JavaParams
 
JavaRDD<T> - Class in org.apache.spark.api.java
 
JavaRDD(RDD<T>, ClassTag<T>) - Constructor for class org.apache.spark.api.java.JavaRDD
 
javaRDD() - Method in class org.apache.spark.sql.Dataset
Returns the content of the Dataset as a JavaRDD of Ts.
JavaRDDLike<T,This extends JavaRDDLike<T,This>> - Interface in org.apache.spark.api.java
Defines operations common to several Java RDD implementations.
JavaReceiverInputDStream<T> - Class in org.apache.spark.streaming.api.java
A Java-friendly interface to ReceiverInputDStream, the abstract class for defining any input stream that receives data over the network.
JavaReceiverInputDStream(ReceiverInputDStream<T>, ClassTag<T>) - Constructor for class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
 
javaSequence() - Method in class org.apache.spark.mllib.fpm.PrefixSpan.FreqSequence
Returns sequence as a Java List of lists for Java users.
javaSerialization(ClassTag<T>) - Static method in class org.apache.spark.sql.Encoders
(Scala-specific) Creates an encoder that serializes objects of type T using generic Java serialization.
javaSerialization(Class<T>) - Static method in class org.apache.spark.sql.Encoders
Creates an encoder that serializes objects of type T using generic Java serialization.
JavaSerializer - Class in org.apache.spark.serializer
:: DeveloperApi :: A Spark serializer that uses Java's built-in serialization.
JavaSerializer(SparkConf) - Constructor for class org.apache.spark.serializer.JavaSerializer
 
JavaSparkContext - Class in org.apache.spark.api.java
A Java-friendly version of SparkContext that returns JavaRDDs and works with Java collections instead of Scala ones.
JavaSparkContext(SparkContext) - Constructor for class org.apache.spark.api.java.JavaSparkContext
 
JavaSparkContext() - Constructor for class org.apache.spark.api.java.JavaSparkContext
Create a JavaSparkContext that loads settings from system properties (for instance, when launching with ./bin/spark-submit).
JavaSparkContext(SparkConf) - Constructor for class org.apache.spark.api.java.JavaSparkContext
 
JavaSparkContext(String, String) - Constructor for class org.apache.spark.api.java.JavaSparkContext
 
JavaSparkContext(String, String, SparkConf) - Constructor for class org.apache.spark.api.java.JavaSparkContext
 
JavaSparkContext(String, String, String, String) - Constructor for class org.apache.spark.api.java.JavaSparkContext
 
JavaSparkContext(String, String, String, String[]) - Constructor for class org.apache.spark.api.java.JavaSparkContext
 
JavaSparkContext(String, String, String, String[], Map<String, String>) - Constructor for class org.apache.spark.api.java.JavaSparkContext
 
JavaSparkStatusTracker - Class in org.apache.spark.api.java
Low-level status reporting APIs for monitoring job and stage progress.
JavaStreamingContext - Class in org.apache.spark.streaming.api.java
A Java-friendly version of StreamingContext which is the main entry point for Spark Streaming functionality.
JavaStreamingContext(StreamingContext) - Constructor for class org.apache.spark.streaming.api.java.JavaStreamingContext
 
JavaStreamingContext(String, String, Duration) - Constructor for class org.apache.spark.streaming.api.java.JavaStreamingContext
Create a StreamingContext.
JavaStreamingContext(String, String, Duration, String, String) - Constructor for class org.apache.spark.streaming.api.java.JavaStreamingContext
Create a StreamingContext.
JavaStreamingContext(String, String, Duration, String, String[]) - Constructor for class org.apache.spark.streaming.api.java.JavaStreamingContext
Create a StreamingContext.
JavaStreamingContext(String, String, Duration, String, String[], Map<String, String>) - Constructor for class org.apache.spark.streaming.api.java.JavaStreamingContext
Create a StreamingContext.
JavaStreamingContext(JavaSparkContext, Duration) - Constructor for class org.apache.spark.streaming.api.java.JavaStreamingContext
Create a JavaStreamingContext using an existing JavaSparkContext.
JavaStreamingContext(SparkConf, Duration) - Constructor for class org.apache.spark.streaming.api.java.JavaStreamingContext
Create a JavaStreamingContext using a SparkConf configuration.
JavaStreamingContext(String) - Constructor for class org.apache.spark.streaming.api.java.JavaStreamingContext
Recreate a JavaStreamingContext from a checkpoint file.
JavaStreamingContext(String, Configuration) - Constructor for class org.apache.spark.streaming.api.java.JavaStreamingContext
Re-creates a JavaStreamingContext from a checkpoint file.
JavaStreamingListenerEvent - Interface in org.apache.spark.streaming.api.java
Base trait for events related to JavaStreamingListener
javaTopicAssignments() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
Java-friendly version of topicAssignments
javaTopicDistributions() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
Java-friendly version of topicDistributions
javaTopTopicsPerDocument(int) - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
Java-friendly version of topTopicsPerDocument
javaTreeWeights() - Method in interface org.apache.spark.ml.tree.TreeEnsembleModel
Weights used by the python wrappers.
javaTypeToDataType(Type) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
javaTypeToDataType(Type) - Static method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
JavaUtils - Class in org.apache.spark.api.java
 
JavaUtils() - Constructor for class org.apache.spark.api.java.JavaUtils
 
JavaUtils.SerializableMapWrapper<A,B> - Class in org.apache.spark.api.java
 
javaVersion() - Method in class org.apache.spark.status.api.v1.RuntimeInfo
 
jdbc(String, String, Properties) - Method in class org.apache.spark.sql.DataFrameReader
Construct a DataFrame representing the database table accessible via JDBC URL url named table and connection properties.
jdbc(String, String, String, long, long, int, Properties) - Method in class org.apache.spark.sql.DataFrameReader
Construct a DataFrame representing the database table accessible via JDBC URL url named table.
jdbc(String, String, String[], Properties) - Method in class org.apache.spark.sql.DataFrameReader
Construct a DataFrame representing the database table accessible via JDBC URL url named table using connection properties.
jdbc(String, String, Properties) - Method in class org.apache.spark.sql.DataFrameWriter
Saves the content of the DataFrame to an external database table via JDBC.
jdbc(String, String) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().jdbc().
jdbc(String, String, String, long, long, int) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().jdbc().
jdbc(String, String, String[]) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().jdbc().
JdbcDialect - Class in org.apache.spark.sql.jdbc
:: DeveloperApi :: Encapsulates everything (extensions, workarounds, quirks) to handle the SQL dialect of a certain database or jdbc driver.
JdbcDialect() - Constructor for class org.apache.spark.sql.jdbc.JdbcDialect
 
JdbcDialects - Class in org.apache.spark.sql.jdbc
:: DeveloperApi :: Registry of dialects that apply to every new jdbc org.apache.spark.sql.DataFrame.
JdbcDialects() - Constructor for class org.apache.spark.sql.jdbc.JdbcDialects
 
jdbcNullType() - Method in class org.apache.spark.sql.jdbc.JdbcType
 
JdbcRDD<T> - Class in org.apache.spark.rdd
An RDD that executes a SQL query on a JDBC connection and reads results.
JdbcRDD(SparkContext, Function0<Connection>, String, long, long, int, Function1<ResultSet, T>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.JdbcRDD
 
JdbcRDD.ConnectionFactory - Interface in org.apache.spark.rdd
 
JdbcType - Class in org.apache.spark.sql.jdbc
:: DeveloperApi :: A database type definition coupled with the jdbc type needed to send null values to the database.
JdbcType(String, int) - Constructor for class org.apache.spark.sql.jdbc.JdbcType
 
JettyUtils - Class in org.apache.spark.ui
Utilities for launching a web server using Jetty's HTTP Server class
JettyUtils() - Constructor for class org.apache.spark.ui.JettyUtils
 
JettyUtils.ServletParams<T> - Class in org.apache.spark.ui
 
JettyUtils.ServletParams$ - Class in org.apache.spark.ui
 
JOB_DAG() - Static method in class org.apache.spark.ui.ToolTips
 
JOB_TIMELINE() - Static method in class org.apache.spark.ui.ToolTips
 
JobData - Class in org.apache.spark.status.api.v1
 
jobEndFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
jobEndToJson(SparkListenerJobEnd) - Static method in class org.apache.spark.util.JsonProtocol
 
JobExecutionStatus - Enum in org.apache.spark
 
jobFailed(Exception) - Method in interface org.apache.spark.scheduler.JobListener
 
JobGeneratorEvent - Interface in org.apache.spark.streaming.scheduler
Event classes for JobGenerator
jobGroup() - Method in class org.apache.spark.status.api.v1.JobData
 
jobId() - Method in class org.apache.spark.scheduler.SparkListenerJobEnd
 
jobId() - Method in class org.apache.spark.scheduler.SparkListenerJobStart
 
jobId() - Method in interface org.apache.spark.SparkJobInfo
 
jobId() - Method in class org.apache.spark.SparkJobInfoImpl
 
jobId() - Method in class org.apache.spark.status.api.v1.JobData
 
jobId() - Method in class org.apache.spark.status.LiveJob
 
jobID() - Method in class org.apache.spark.TaskCommitDenied
 
jobIds() - Method in interface org.apache.spark.api.java.JavaFutureAction
Returns the job IDs run by the underlying async operation.
jobIds() - Method in class org.apache.spark.ComplexFutureAction
 
jobIds() - Method in interface org.apache.spark.FutureAction
Returns the job IDs run by the underlying async operation.
jobIds() - Method in class org.apache.spark.SimpleFutureAction
 
jobIds() - Method in class org.apache.spark.status.api.v1.streaming.OutputOperationInfo
 
jobIds() - Method in class org.apache.spark.status.LiveStage
 
JobListener - Interface in org.apache.spark.scheduler
Interface used to listen for job completion or failure events after submitting a job to the DAGScheduler.
JobResult - Interface in org.apache.spark.scheduler
:: DeveloperApi :: A result of a job in the DAGScheduler.
jobResult() - Method in class org.apache.spark.scheduler.SparkListenerJobEnd
 
jobResultFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
jobResultToJson(JobResult) - Static method in class org.apache.spark.util.JsonProtocol
 
jobs() - Method in class org.apache.spark.status.LiveStage
 
JobSchedulerEvent - Interface in org.apache.spark.streaming.scheduler
 
jobStartFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
jobStartToJson(SparkListenerJobStart) - Static method in class org.apache.spark.util.JsonProtocol
 
JobSubmitter - Interface in org.apache.spark
Handle via which a "run" function passed to a ComplexFutureAction can submit jobs for execution.
JobSucceeded - Class in org.apache.spark.scheduler
 
JobSucceeded() - Constructor for class org.apache.spark.scheduler.JobSucceeded
 
join(JavaPairRDD<K, W>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
Return an RDD containing all pairs of elements with matching keys in this and other.
join(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
Return an RDD containing all pairs of elements with matching keys in this and other.
join(JavaPairRDD<K, W>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
Return an RDD containing all pairs of elements with matching keys in this and other.
join(RDD<Tuple2<K, W>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return an RDD containing all pairs of elements with matching keys in this and other.
join(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return an RDD containing all pairs of elements with matching keys in this and other.
join(RDD<Tuple2<K, W>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return an RDD containing all pairs of elements with matching keys in this and other.
join(Dataset<?>) - Method in class org.apache.spark.sql.Dataset
Join with another DataFrame.
join(Dataset<?>, String) - Method in class org.apache.spark.sql.Dataset
Inner equi-join with another DataFrame using the given column.
join(Dataset<?>, Seq<String>) - Method in class org.apache.spark.sql.Dataset
Inner equi-join with another DataFrame using the given columns.
join(Dataset<?>, Seq<String>, String) - Method in class org.apache.spark.sql.Dataset
Equi-join with another DataFrame using the given columns.
join(Dataset<?>, Column) - Method in class org.apache.spark.sql.Dataset
Inner join with another DataFrame, using the given join expression.
join(Dataset<?>, Column, String) - Method in class org.apache.spark.sql.Dataset
Join with another DataFrame, using the given join expression.
join(JavaPairDStream<K, W>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'join' between RDDs of this DStream and other DStream.
join(JavaPairDStream<K, W>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'join' between RDDs of this DStream and other DStream.
join(JavaPairDStream<K, W>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'join' between RDDs of this DStream and other DStream.
join(DStream<Tuple2<K, W>>, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'join' between RDDs of this DStream and other DStream.
join(DStream<Tuple2<K, W>>, int, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'join' between RDDs of this DStream and other DStream.
join(DStream<Tuple2<K, W>>, Partitioner, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'join' between RDDs of this DStream and other DStream.
joinVertices(RDD<Tuple2<Object, U>>, Function3<Object, VD, U, VD>, ClassTag<U>) - Method in class org.apache.spark.graphx.GraphOps
Join the vertices with an RDD and then apply a function from the vertex and RDD entry to a new vertex value.
joinWith(Dataset<U>, Column, String) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: Joins this Dataset returning a Tuple2 for each pair where condition evaluates to true.
joinWith(Dataset<U>, Column) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: Using inner equi-join to join this Dataset returning a Tuple2 for each pair where condition evaluates to true.
json(String...) - Method in class org.apache.spark.sql.DataFrameReader
Loads JSON files and returns the results as a DataFrame.
json(String) - Method in class org.apache.spark.sql.DataFrameReader
Loads a JSON file and returns the results as a DataFrame.
json(Seq<String>) - Method in class org.apache.spark.sql.DataFrameReader
Loads JSON files and returns the results as a DataFrame.
json(JavaRDD<String>) - Method in class org.apache.spark.sql.DataFrameReader
Deprecated.
Use json(Dataset[String]) instead. Since 2.2.0.
json(RDD<String>) - Method in class org.apache.spark.sql.DataFrameReader
Deprecated.
Use json(Dataset[String]) instead. Since 2.2.0.
json(Dataset<String>) - Method in class org.apache.spark.sql.DataFrameReader
Loads a Dataset[String] storing JSON objects (JSON Lines text format or newline-delimited JSON) and returns the result as a DataFrame.
json(String) - Method in class org.apache.spark.sql.DataFrameWriter
Saves the content of the DataFrame in JSON format ( JSON Lines text format or newline-delimited JSON) at the specified path.
json() - Method in class org.apache.spark.sql.sources.v2.reader.streaming.Offset
A JSON-serialized representation of an Offset that is used for saving offsets to the offset log.
json(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Loads a JSON file stream and returns the results as a DataFrame.
json() - Method in class org.apache.spark.sql.streaming.SinkProgress
The compact JSON representation of this progress.
json() - Method in class org.apache.spark.sql.streaming.SourceProgress
The compact JSON representation of this progress.
json() - Method in class org.apache.spark.sql.streaming.StateOperatorProgress
The compact JSON representation of this progress.
json() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
The compact JSON representation of this progress.
json() - Method in class org.apache.spark.sql.streaming.StreamingQueryStatus
The compact JSON representation of this status.
json() - Static method in class org.apache.spark.sql.types.BinaryType
 
json() - Static method in class org.apache.spark.sql.types.BooleanType
 
json() - Static method in class org.apache.spark.sql.types.ByteType
 
json() - Static method in class org.apache.spark.sql.types.CalendarIntervalType
 
json() - Method in class org.apache.spark.sql.types.DataType
The compact JSON representation of this data type.
json() - Static method in class org.apache.spark.sql.types.DateType
 
json() - Static method in class org.apache.spark.sql.types.DoubleType
 
json() - Static method in class org.apache.spark.sql.types.FloatType
 
json() - Static method in class org.apache.spark.sql.types.IntegerType
 
json() - Static method in class org.apache.spark.sql.types.LongType
 
json() - Method in class org.apache.spark.sql.types.Metadata
Converts to its JSON representation.
json() - Static method in class org.apache.spark.sql.types.NullType
 
json() - Static method in class org.apache.spark.sql.types.ShortType
 
json() - Static method in class org.apache.spark.sql.types.StringType
 
json() - Static method in class org.apache.spark.sql.types.TimestampType
 
json_tuple(Column, String...) - Static method in class org.apache.spark.sql.functions
Creates a new row for a json column according to the given field names.
json_tuple(Column, Seq<String>) - Static method in class org.apache.spark.sql.functions
Creates a new row for a json column according to the given field names.
jsonDecode(String) - Method in class org.apache.spark.ml.param.BooleanParam
 
jsonDecode(String) - Method in class org.apache.spark.ml.param.DoubleArrayArrayParam
 
jsonDecode(String) - Method in class org.apache.spark.ml.param.DoubleArrayParam
 
jsonDecode(String) - Method in class org.apache.spark.ml.param.DoubleParam
 
jsonDecode(String) - Method in class org.apache.spark.ml.param.FloatParam
 
jsonDecode(String) - Method in class org.apache.spark.ml.param.IntArrayParam
 
jsonDecode(String) - Method in class org.apache.spark.ml.param.IntParam
 
jsonDecode(String) - Method in class org.apache.spark.ml.param.LongParam
 
jsonDecode(String) - Method in class org.apache.spark.ml.param.Param
Decodes a param value from JSON.
jsonDecode(String) - Method in class org.apache.spark.ml.param.StringArrayParam
 
jsonEncode(boolean) - Method in class org.apache.spark.ml.param.BooleanParam
 
jsonEncode(double[][]) - Method in class org.apache.spark.ml.param.DoubleArrayArrayParam
 
jsonEncode(double[]) - Method in class org.apache.spark.ml.param.DoubleArrayParam
 
jsonEncode(double) - Method in class org.apache.spark.ml.param.DoubleParam
 
jsonEncode(float) - Method in class org.apache.spark.ml.param.FloatParam
 
jsonEncode(int[]) - Method in class org.apache.spark.ml.param.IntArrayParam
 
jsonEncode(int) - Method in class org.apache.spark.ml.param.IntParam
 
jsonEncode(long) - Method in class org.apache.spark.ml.param.LongParam
 
jsonEncode(T) - Method in class org.apache.spark.ml.param.Param
Encodes a param value into JSON, which can be decoded by `jsonDecode()`.
jsonEncode(String[]) - Method in class org.apache.spark.ml.param.StringArrayParam
 
jsonFile(String) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().json().
jsonFile(String, StructType) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().json().
jsonFile(String, double) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().json().
JsonMatrixConverter - Class in org.apache.spark.ml.linalg
 
JsonMatrixConverter() - Constructor for class org.apache.spark.ml.linalg.JsonMatrixConverter
 
JsonProtocol - Class in org.apache.spark.util
Serializes SparkListener events to/from JSON.
JsonProtocol() - Constructor for class org.apache.spark.util.JsonProtocol
 
jsonRDD(RDD<String>) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().json().
jsonRDD(JavaRDD<String>) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().json().
jsonRDD(RDD<String>, StructType) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().json().
jsonRDD(JavaRDD<String>, StructType) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().json().
jsonRDD(RDD<String>, double) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().json().
jsonRDD(JavaRDD<String>, double) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().json().
jsonResponderToServlet(Function1<HttpServletRequest, JsonAST.JValue>) - Static method in class org.apache.spark.ui.JettyUtils
 
JsonVectorConverter - Class in org.apache.spark.ml.linalg
 
JsonVectorConverter() - Constructor for class org.apache.spark.ml.linalg.JsonVectorConverter
 
jValueDecode(JsonAST.JValue) - Static method in class org.apache.spark.ml.param.DoubleParam
Decodes a param value from JValue.
jValueDecode(JsonAST.JValue) - Static method in class org.apache.spark.ml.param.FloatParam
Decodes a param value from JValue.
jValueEncode(double) - Static method in class org.apache.spark.ml.param.DoubleParam
Encodes a param value into JValue.
jValueEncode(float) - Static method in class org.apache.spark.ml.param.FloatParam
Encodes a param value into JValue.
JVM_GC_TIME() - Static method in class org.apache.spark.InternalAccumulator
 
jvmGcTime() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
jvmGcTime() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 

K

k() - Method in interface org.apache.spark.ml.clustering.BisectingKMeansParams
The desired number of leaf clusters.
k() - Method in class org.apache.spark.ml.clustering.ClusteringSummary
 
k() - Method in interface org.apache.spark.ml.clustering.GaussianMixtureParams
Number of independent Gaussians in the mixture model.
k() - Method in interface org.apache.spark.ml.clustering.KMeansParams
The number of clusters to create (k).
k() - Method in interface org.apache.spark.ml.clustering.LDAParams
Param for the number of topics (clusters) to infer.
k() - Method in interface org.apache.spark.ml.clustering.PowerIterationClusteringParams
The number of clusters to create (k).
k() - Method in interface org.apache.spark.ml.feature.PCAParams
The number of principal components.
k() - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
Number of leaf clusters.
k() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
 
k() - Method in class org.apache.spark.mllib.clustering.ExpectationSum
 
k() - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
Number of gaussians in mixture
k() - Method in class org.apache.spark.mllib.clustering.KMeansModel
Total number of clusters.
k() - Method in class org.apache.spark.mllib.clustering.LDAModel
Number of topics
k() - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
 
k() - Method in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel
 
k() - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
 
k() - Method in class org.apache.spark.mllib.feature.PCA
 
k() - Method in class org.apache.spark.mllib.feature.PCAModel
 
K_MEANS_PARALLEL() - Static method in class org.apache.spark.mllib.clustering.KMeans
 
kClassTag() - Method in class org.apache.spark.api.java.JavaHadoopRDD
 
kClassTag() - Method in class org.apache.spark.api.java.JavaNewHadoopRDD
 
kClassTag() - Method in class org.apache.spark.api.java.JavaPairRDD
 
kClassTag() - Method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
 
kClassTag() - Method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
 
keepLastCheckpoint() - Method in interface org.apache.spark.ml.clustering.LDAParams
For EM optimizer only: optimizer = "em".
KernelDensity - Class in org.apache.spark.mllib.stat
Kernel density estimation.
KernelDensity() - Constructor for class org.apache.spark.mllib.stat.KernelDensity
 
keyArray() - Method in class org.apache.spark.sql.vectorized.ColumnarMap
 
keyAs(Encoder<L>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
Returns a new KeyValueGroupedDataset where the type of the key has been mapped to the specified type.
keyBy(Function<T, U>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Creates tuples of the elements in this RDD by applying f.
keyBy(Function1<T, K>) - Method in class org.apache.spark.rdd.RDD
Creates tuples of the elements in this RDD by applying f.
keyOrdering() - Method in class org.apache.spark.ShuffleDependency
 
keyPrefix() - Method in interface org.apache.spark.sql.sources.v2.SessionConfigSupport
Key prefix of the session configs to propagate.
keys() - Method in class org.apache.spark.api.java.JavaPairRDD
Return an RDD with the keys of each tuple.
keys() - Method in class org.apache.spark.rdd.PairRDDFunctions
Return an RDD with the keys of each tuple.
keys() - Method in class org.apache.spark.sql.KeyValueGroupedDataset
Returns a Dataset that contains each unique key.
keyType() - Method in class org.apache.spark.sql.types.MapType
 
KeyValueGroupedDataset<K,V> - Class in org.apache.spark.sql
:: Experimental :: A Dataset has been logically grouped by a user specified grouping key.
kFold(RDD<T>, int, int, ClassTag<T>) - Static method in class org.apache.spark.mllib.util.MLUtils
Return a k element array of pairs of RDDs with the first element of each pair containing the training data, a complement of the validation data and the second element, the validation data, containing a unique 1/kth of the data.
kFold(RDD<T>, int, long, ClassTag<T>) - Static method in class org.apache.spark.mllib.util.MLUtils
Version of kFold() taking a Long seed.
kill() - Method in interface org.apache.spark.launcher.SparkAppHandle
Tries to kill the underlying application.
killAllTaskAttempts(int, boolean, String) - Method in interface org.apache.spark.scheduler.TaskScheduler
 
killed() - Method in class org.apache.spark.scheduler.TaskInfo
 
KILLED() - Static method in class org.apache.spark.TaskState
 
killedSummary() - Method in class org.apache.spark.status.LiveJob
 
killedSummary() - Method in class org.apache.spark.status.LiveStage
 
killedTasks() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
killedTasks() - Method in class org.apache.spark.status.LiveExecutorStageSummary
 
killedTasks() - Method in class org.apache.spark.status.LiveJob
 
killedTasks() - Method in class org.apache.spark.status.LiveStage
 
killedTasksSummary() - Method in class org.apache.spark.status.api.v1.JobData
 
killedTasksSummary() - Method in class org.apache.spark.status.api.v1.StageData
 
killExecutor(String) - Method in interface org.apache.spark.ExecutorAllocationClient
Request that the cluster manager kill the specified executor.
killExecutor(String) - Method in class org.apache.spark.SparkContext
:: DeveloperApi :: Request that the cluster manager kill the specified executor.
killExecutors(Seq<String>, boolean, boolean, boolean) - Method in interface org.apache.spark.ExecutorAllocationClient
Request that the cluster manager kill the specified executors.
KillExecutors(Seq<String>) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillExecutors
 
killExecutors(Seq<String>) - Method in class org.apache.spark.SparkContext
:: DeveloperApi :: Request that the cluster manager kill the specified executors.
KillExecutors$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillExecutors$
 
killExecutorsOnHost(String) - Method in interface org.apache.spark.ExecutorAllocationClient
Request that the cluster manager kill every executor on the specified host.
KillExecutorsOnHost(String) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillExecutorsOnHost
 
KillExecutorsOnHost$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillExecutorsOnHost$
 
KillTask(long, String, boolean, String) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask
 
KillTask - Class in org.apache.spark.scheduler.local
 
KillTask(long, boolean, String) - Constructor for class org.apache.spark.scheduler.local.KillTask
 
killTask(long, String, boolean, String) - Method in interface org.apache.spark.scheduler.SchedulerBackend
Requests that an executor kills a running task.
KillTask$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask$
 
killTaskAttempt(long, boolean, String) - Method in interface org.apache.spark.scheduler.TaskScheduler
Kills a task attempt.
killTaskAttempt(long, boolean, String) - Method in class org.apache.spark.SparkContext
Kill and reschedule the given task attempt.
KinesisDataGenerator - Interface in org.apache.spark.streaming.kinesis
A wrapper interface that will allow us to consolidate the code for synthetic data generation.
KinesisInitialPositions - Class in org.apache.spark.streaming.kinesis
 
KinesisInitialPositions() - Constructor for class org.apache.spark.streaming.kinesis.KinesisInitialPositions
 
KinesisInitialPositions.AtTimestamp - Class in org.apache.spark.streaming.kinesis
 
KinesisInitialPositions.Latest - Class in org.apache.spark.streaming.kinesis
 
KinesisInitialPositions.TrimHorizon - Class in org.apache.spark.streaming.kinesis
 
KinesisUtils - Class in org.apache.spark.streaming.kinesis
 
KinesisUtils() - Constructor for class org.apache.spark.streaming.kinesis.KinesisUtils
 
KinesisUtilsPythonHelper - Class in org.apache.spark.streaming.kinesis
This is a helper class that wraps the methods in KinesisUtils into more Python-friendly class and function so that it can be easily instantiated and called from Python's KinesisUtils.
KinesisUtilsPythonHelper() - Constructor for class org.apache.spark.streaming.kinesis.KinesisUtilsPythonHelper
 
kManifest() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
 
KMeans - Class in org.apache.spark.ml.clustering
K-means clustering with support for k-means|| initialization proposed by Bahmani et al.
KMeans(String) - Constructor for class org.apache.spark.ml.clustering.KMeans
 
KMeans() - Constructor for class org.apache.spark.ml.clustering.KMeans
 
KMeans - Class in org.apache.spark.mllib.clustering
K-means clustering with a k-means++ like initialization mode (the k-means|| algorithm by Bahmani et al).
KMeans() - Constructor for class org.apache.spark.mllib.clustering.KMeans
Constructs a KMeans instance with default parameters: {k: 2, maxIterations: 20, initializationMode: "k-means||", initializationSteps: 2, epsilon: 1e-4, seed: random, distanceMeasure: "euclidean"}.
KMeansDataGenerator - Class in org.apache.spark.mllib.util
:: DeveloperApi :: Generate test data for KMeans.
KMeansDataGenerator() - Constructor for class org.apache.spark.mllib.util.KMeansDataGenerator
 
KMeansModel - Class in org.apache.spark.ml.clustering
Model fitted by KMeans.
KMeansModel - Class in org.apache.spark.mllib.clustering
A clustering model for K-means.
KMeansModel(Vector[], String, double, int) - Constructor for class org.apache.spark.mllib.clustering.KMeansModel
 
KMeansModel(Vector[]) - Constructor for class org.apache.spark.mllib.clustering.KMeansModel
 
KMeansModel(Iterable<Vector>) - Constructor for class org.apache.spark.mllib.clustering.KMeansModel
A Java-friendly constructor that takes an Iterable of Vectors.
KMeansModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.clustering
 
KMeansModel.SaveLoadV2_0$ - Class in org.apache.spark.mllib.clustering
 
KMeansParams - Interface in org.apache.spark.ml.clustering
Common params for KMeans and KMeansModel
kMeansPlusPlus(int, VectorWithNorm[], double[], int, int) - Static method in class org.apache.spark.mllib.clustering.LocalKMeans
Run K-means++ on the weighted point set points.
KMeansSummary - Class in org.apache.spark.ml.clustering
:: Experimental :: Summary of KMeans.
KnownSizeEstimation - Interface in org.apache.spark.util
A trait that allows a class to give SizeEstimator more accurate size estimation.
KolmogorovSmirnovTest - Class in org.apache.spark.ml.stat
:: Experimental ::
KolmogorovSmirnovTest() - Constructor for class org.apache.spark.ml.stat.KolmogorovSmirnovTest
 
kolmogorovSmirnovTest(RDD<Object>, String, double...) - Static method in class org.apache.spark.mllib.stat.Statistics
Convenience function to conduct a one-sample, two-sided Kolmogorov-Smirnov test for probability distribution equality.
kolmogorovSmirnovTest(JavaDoubleRDD, String, double...) - Static method in class org.apache.spark.mllib.stat.Statistics
Java-friendly version of kolmogorovSmirnovTest()
kolmogorovSmirnovTest(RDD<Object>, Function1<Object, Object>) - Static method in class org.apache.spark.mllib.stat.Statistics
Conduct the two-sided Kolmogorov-Smirnov (KS) test for data sampled from a continuous distribution.
kolmogorovSmirnovTest(RDD<Object>, String, Seq<Object>) - Static method in class org.apache.spark.mllib.stat.Statistics
Convenience function to conduct a one-sample, two-sided Kolmogorov-Smirnov test for probability distribution equality.
kolmogorovSmirnovTest(JavaDoubleRDD, String, Seq<Object>) - Static method in class org.apache.spark.mllib.stat.Statistics
Java-friendly version of kolmogorovSmirnovTest()
KolmogorovSmirnovTest - Class in org.apache.spark.mllib.stat.test
Conduct the two-sided Kolmogorov Smirnov (KS) test for data sampled from a continuous distribution.
KolmogorovSmirnovTest() - Constructor for class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTest
 
KolmogorovSmirnovTest.NullHypothesis$ - Class in org.apache.spark.mllib.stat.test
 
KolmogorovSmirnovTestResult - Class in org.apache.spark.mllib.stat.test
Object containing the test results for the Kolmogorov-Smirnov test.
kryo(ClassTag<T>) - Static method in class org.apache.spark.sql.Encoders
(Scala-specific) Creates an encoder that serializes objects of type T using Kryo.
kryo(Class<T>) - Static method in class org.apache.spark.sql.Encoders
Creates an encoder that serializes objects of type T using Kryo.
KryoRegistrator - Interface in org.apache.spark.serializer
Interface implemented by clients to register their classes with Kryo when using Kryo serialization.
KryoSerializer - Class in org.apache.spark.serializer
A Spark serializer that uses the Kryo serialization library.
KryoSerializer(SparkConf) - Constructor for class org.apache.spark.serializer.KryoSerializer
 
kurtosis(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the kurtosis of the values in a group.
kurtosis(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the kurtosis of the values in a group.
KVUtils - Class in org.apache.spark.status
 
KVUtils() - Constructor for class org.apache.spark.status.KVUtils
 

L

L1Updater - Class in org.apache.spark.mllib.optimization
:: DeveloperApi :: Updater for L1 regularized problems.
L1Updater() - Constructor for class org.apache.spark.mllib.optimization.L1Updater
 
label() - Method in class org.apache.spark.ml.feature.LabeledPoint
 
label() - Method in class org.apache.spark.mllib.regression.LabeledPoint
 
labelCol() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Field in "predictions" which gives the true label of each instance (if available).
labelCol() - Method in class org.apache.spark.ml.classification.LogisticRegressionSummaryImpl
 
labelCol() - Method in interface org.apache.spark.ml.param.shared.HasLabelCol
Param for label column name.
labelCol() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
 
LabeledPoint - Class in org.apache.spark.ml.feature
Class that represents the features and label of a data point.
LabeledPoint(double, Vector) - Constructor for class org.apache.spark.ml.feature.LabeledPoint
 
LabeledPoint - Class in org.apache.spark.mllib.regression
Class that represents the features and labels of a data point.
LabeledPoint(double, Vector) - Constructor for class org.apache.spark.mllib.regression.LabeledPoint
 
LabelPropagation - Class in org.apache.spark.graphx.lib
Label Propagation algorithm.
LabelPropagation() - Constructor for class org.apache.spark.graphx.lib.LabelPropagation
 
labels() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns the sequence of labels in ascending order.
labels() - Method in class org.apache.spark.ml.feature.IndexToString
Optional param for array of labels specifying index-string mapping.
labels() - Method in class org.apache.spark.ml.feature.StringIndexerModel
 
labels() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
 
labels() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$.Data
 
labels() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data
 
labels() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns the sequence of labels in ascending order
labels() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
Returns the sequence of labels in ascending order
lag(Column, int) - Static method in class org.apache.spark.sql.functions
Window function: returns the value that is offset rows before the current row, and null if there is less than offset rows before the current row.
lag(String, int) - Static method in class org.apache.spark.sql.functions
Window function: returns the value that is offset rows before the current row, and null if there is less than offset rows before the current row.
lag(String, int, Object) - Static method in class org.apache.spark.sql.functions
Window function: returns the value that is offset rows before the current row, and defaultValue if there is less than offset rows before the current row.
lag(Column, int, Object) - Static method in class org.apache.spark.sql.functions
Window function: returns the value that is offset rows before the current row, and defaultValue if there is less than offset rows before the current row.
LassoModel - Class in org.apache.spark.mllib.regression
Regression model trained using Lasso.
LassoModel(Vector, double) - Constructor for class org.apache.spark.mllib.regression.LassoModel
 
LassoWithSGD - Class in org.apache.spark.mllib.regression
Train a regression model with L1-regularization using Stochastic Gradient Descent.
LassoWithSGD() - Constructor for class org.apache.spark.mllib.regression.LassoWithSGD
Deprecated.
Use ml.regression.LinearRegression with elasticNetParam = 1.0. Note the default regParam is 0.01 for LassoWithSGD, but is 0.0 for LinearRegression. Since 2.0.0.
last(Column, boolean) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the last value in a group.
last(String, boolean) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the last value of the column in a group.
last(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the last value in a group.
last(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the last value of the column in a group.
last_day(Column) - Static method in class org.apache.spark.sql.functions
Returns the last day of the month which the given date belongs to.
lastDir() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
 
lastError() - Method in class org.apache.spark.status.api.v1.streaming.ReceiverInfo
 
lastError() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
 
lastErrorMessage() - Method in class org.apache.spark.status.api.v1.streaming.ReceiverInfo
 
lastErrorMessage() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
 
lastErrorTime() - Method in class org.apache.spark.status.api.v1.streaming.ReceiverInfo
 
lastErrorTime() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
 
lastProgress() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Returns the most recent StreamingQueryProgress update of this streaming query.
lastStageNameAndDescription(org.apache.spark.status.AppStatusStore, JobData) - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
lastUpdate() - Method in class org.apache.spark.status.LiveRDDDistribution
 
lastUpdated() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
 
Latest() - Constructor for class org.apache.spark.streaming.kinesis.KinesisInitialPositions.Latest
 
latestModel() - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
Return the latest model.
latestModel() - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
Return the latest model.
launch() - Method in class org.apache.spark.launcher.SparkLauncher
Launches a sub-process that will start the configured Spark application.
LAUNCH_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
 
LAUNCHING() - Static method in class org.apache.spark.TaskState
 
LaunchTask(org.apache.spark.util.SerializableBuffer) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.LaunchTask
 
LaunchTask$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.LaunchTask$
 
launchTime() - Method in class org.apache.spark.scheduler.TaskInfo
 
launchTime() - Method in class org.apache.spark.status.api.v1.TaskData
 
Layer - Interface in org.apache.spark.ml.ann
Trait that holds Layer properties, that are needed to instantiate it.
LayerModel - Interface in org.apache.spark.ml.ann
Trait that holds Layer weights (or parameters).
layerModels() - Method in interface org.apache.spark.ml.ann.TopologyModel
Array of layer models
layers() - Method in interface org.apache.spark.ml.ann.TopologyModel
Array of layers
layers() - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
 
layers() - Method in interface org.apache.spark.ml.classification.MultilayerPerceptronParams
Layer sizes including input size and output size.
LBFGS - Class in org.apache.spark.mllib.optimization
:: DeveloperApi :: Class used to solve an optimization problem using Limited-memory BFGS.
LBFGS(Gradient, Updater) - Constructor for class org.apache.spark.mllib.optimization.LBFGS
 
LDA - Class in org.apache.spark.ml.clustering
Latent Dirichlet Allocation (LDA), a topic model designed for text documents.
LDA(String) - Constructor for class org.apache.spark.ml.clustering.LDA
 
LDA() - Constructor for class org.apache.spark.ml.clustering.LDA
 
LDA - Class in org.apache.spark.mllib.clustering
Latent Dirichlet Allocation (LDA), a topic model designed for text documents.
LDA() - Constructor for class org.apache.spark.mllib.clustering.LDA
Constructs a LDA instance with default parameters.
LDAModel - Class in org.apache.spark.ml.clustering
Model fitted by LDA.
LDAModel - Class in org.apache.spark.mllib.clustering
Latent Dirichlet Allocation (LDA) model.
LDAOptimizer - Interface in org.apache.spark.mllib.clustering
:: DeveloperApi ::
LDAParams - Interface in org.apache.spark.ml.clustering
 
LDAUtils - Class in org.apache.spark.mllib.clustering
Utility methods for LDA.
LDAUtils() - Constructor for class org.apache.spark.mllib.clustering.LDAUtils
 
lead(String, int) - Static method in class org.apache.spark.sql.functions
Window function: returns the value that is offset rows after the current row, and null if there is less than offset rows after the current row.
lead(Column, int) - Static method in class org.apache.spark.sql.functions
Window function: returns the value that is offset rows after the current row, and null if there is less than offset rows after the current row.
lead(String, int, Object) - Static method in class org.apache.spark.sql.functions
Window function: returns the value that is offset rows after the current row, and defaultValue if there is less than offset rows after the current row.
lead(Column, int, Object) - Static method in class org.apache.spark.sql.functions
Window function: returns the value that is offset rows after the current row, and defaultValue if there is less than offset rows after the current row.
LeafNode - Class in org.apache.spark.ml.tree
Decision tree leaf node.
learningDecay() - Method in interface org.apache.spark.ml.clustering.LDAParams
For Online optimizer only: optimizer = "online".
learningOffset() - Method in interface org.apache.spark.ml.clustering.LDAParams
For Online optimizer only: optimizer = "online".
learningRate() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
least(Column...) - Static method in class org.apache.spark.sql.functions
Returns the least value of the list of values, skipping null values.
least(String, String...) - Static method in class org.apache.spark.sql.functions
Returns the least value of the list of column names, skipping null values.
least(Seq<Column>) - Static method in class org.apache.spark.sql.functions
Returns the least value of the list of values, skipping null values.
least(String, Seq<String>) - Static method in class org.apache.spark.sql.functions
Returns the least value of the list of column names, skipping null values.
LeastSquaresGradient - Class in org.apache.spark.mllib.optimization
:: DeveloperApi :: Compute gradient and loss for a Least-squared loss function, as used in linear regression.
LeastSquaresGradient() - Constructor for class org.apache.spark.mllib.optimization.LeastSquaresGradient
 
left() - Method in class org.apache.spark.sql.sources.And
 
left() - Method in class org.apache.spark.sql.sources.Or
 
leftCategories() - Method in class org.apache.spark.ml.tree.CategoricalSplit
Get sorted categories which split to the left
leftCategoriesOrThreshold() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData
 
leftChild() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
 
leftChild() - Method in class org.apache.spark.ml.tree.InternalNode
 
leftChildIndex(int) - Static method in class org.apache.spark.mllib.tree.model.Node
Return the index of the left child of this node.
leftImpurity() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
 
leftJoin(RDD<Tuple2<Object, VD2>>, Function3<Object, VD, Option<VD2>, VD3>, ClassTag<VD2>, ClassTag<VD3>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
leftJoin(RDD<Tuple2<Object, VD2>>, Function3<Object, VD, Option<VD2>, VD3>, ClassTag<VD2>, ClassTag<VD3>) - Method in class org.apache.spark.graphx.VertexRDD
Left joins this VertexRDD with an RDD containing vertex attribute pairs.
leftNode() - Method in class org.apache.spark.mllib.tree.model.Node
 
leftNodeId() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
 
leftOuterJoin(JavaPairRDD<K, W>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
Perform a left outer join of this and other.
leftOuterJoin(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
Perform a left outer join of this and other.
leftOuterJoin(JavaPairRDD<K, W>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
Perform a left outer join of this and other.
leftOuterJoin(RDD<Tuple2<K, W>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
Perform a left outer join of this and other.
leftOuterJoin(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Perform a left outer join of this and other.
leftOuterJoin(RDD<Tuple2<K, W>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
Perform a left outer join of this and other.
leftOuterJoin(JavaPairDStream<K, W>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'left outer join' between RDDs of this DStream and other DStream.
leftOuterJoin(JavaPairDStream<K, W>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'left outer join' between RDDs of this DStream and other DStream.
leftOuterJoin(JavaPairDStream<K, W>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'left outer join' between RDDs of this DStream and other DStream.
leftOuterJoin(DStream<Tuple2<K, W>>, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'left outer join' between RDDs of this DStream and other DStream.
leftOuterJoin(DStream<Tuple2<K, W>>, int, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'left outer join' between RDDs of this DStream and other DStream.
leftOuterJoin(DStream<Tuple2<K, W>>, Partitioner, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'left outer join' between RDDs of this DStream and other DStream.
leftPredict() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
 
leftZipJoin(VertexRDD<VD2>, Function3<Object, VD, Option<VD2>, VD3>, ClassTag<VD2>, ClassTag<VD3>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
leftZipJoin(VertexRDD<VD2>, Function3<Object, VD, Option<VD2>, VD3>, ClassTag<VD2>, ClassTag<VD3>) - Method in class org.apache.spark.graphx.VertexRDD
Left joins this RDD with another VertexRDD with the same index.
LegacyAccumulatorWrapper<R,T> - Class in org.apache.spark.util
 
LegacyAccumulatorWrapper(R, AccumulableParam<R, T>) - Constructor for class org.apache.spark.util.LegacyAccumulatorWrapper
 
length() - Method in class org.apache.spark.scheduler.SplitInfo
 
length(Column) - Static method in class org.apache.spark.sql.functions
Computes the character length of a given string or number of bytes of a binary string.
length() - Method in interface org.apache.spark.sql.Row
Number of elements in the Row.
length() - Method in class org.apache.spark.sql.types.CharType
 
length() - Method in class org.apache.spark.sql.types.HiveStringType
 
length() - Method in class org.apache.spark.sql.types.StructType
 
length() - Method in class org.apache.spark.sql.types.VarcharType
 
length() - Method in class org.apache.spark.status.RDDPartitionSeq
 
leq(Object) - Method in class org.apache.spark.sql.Column
Less than or equal to.
less(Duration) - Method in class org.apache.spark.streaming.Duration
 
less(Time) - Method in class org.apache.spark.streaming.Time
 
lessEq(Duration) - Method in class org.apache.spark.streaming.Duration
 
lessEq(Time) - Method in class org.apache.spark.streaming.Time
 
LessThan - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff the attribute evaluates to a value less than value.
LessThan(String, Object) - Constructor for class org.apache.spark.sql.sources.LessThan
 
LessThanOrEqual - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff the attribute evaluates to a value less than or equal to value.
LessThanOrEqual(String, Object) - Constructor for class org.apache.spark.sql.sources.LessThanOrEqual
 
levenshtein(Column, Column) - Static method in class org.apache.spark.sql.functions
Computes the Levenshtein distance of the two given string columns.
libraryPathEnvName() - Static method in class org.apache.spark.util.Utils
Return the current system LD_LIBRARY_PATH name
libraryPathEnvPrefix(Seq<String>) - Static method in class org.apache.spark.util.Utils
Return the prefix of a command that appends the given library paths to the system-specific library path environment variable.
LibSVMDataSource - Class in org.apache.spark.ml.source.libsvm
libsvm package implements Spark SQL data source API for loading LIBSVM data as DataFrame.
LibSVMDataSource() - Constructor for class org.apache.spark.ml.source.libsvm.LibSVMDataSource
 
lift() - Method in class org.apache.spark.mllib.fpm.AssociationRules.Rule
Returns the lift of the rule.
like(String) - Method in class org.apache.spark.sql.Column
SQL like expression.
limit(int) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset by taking the first n rows.
line() - Method in exception org.apache.spark.sql.AnalysisException
 
LinearDataGenerator - Class in org.apache.spark.mllib.util
:: DeveloperApi :: Generate sample data used for Linear Data.
LinearDataGenerator() - Constructor for class org.apache.spark.mllib.util.LinearDataGenerator
 
LinearRegression - Class in org.apache.spark.ml.regression
Linear regression.
LinearRegression(String) - Constructor for class org.apache.spark.ml.regression.LinearRegression
 
LinearRegression() - Constructor for class org.apache.spark.ml.regression.LinearRegression
 
LinearRegressionModel - Class in org.apache.spark.ml.regression
Model produced by LinearRegression.
LinearRegressionModel - Class in org.apache.spark.mllib.regression
Regression model trained using LinearRegression.
LinearRegressionModel(Vector, double) - Constructor for class org.apache.spark.mllib.regression.LinearRegressionModel
 
LinearRegressionParams - Interface in org.apache.spark.ml.regression
Params for linear regression.
LinearRegressionSummary - Class in org.apache.spark.ml.regression
:: Experimental :: Linear regression results evaluated on a dataset.
LinearRegressionTrainingSummary - Class in org.apache.spark.ml.regression
:: Experimental :: Linear regression training results.
LinearRegressionWithSGD - Class in org.apache.spark.mllib.regression
Train a linear regression model with no regularization using Stochastic Gradient Descent.
LinearRegressionWithSGD() - Constructor for class org.apache.spark.mllib.regression.LinearRegressionWithSGD
Deprecated.
Use ml.regression.LinearRegression or LBFGS. Since 2.0.0.
LinearSVC - Class in org.apache.spark.ml.classification
:: Experimental ::
LinearSVC(String) - Constructor for class org.apache.spark.ml.classification.LinearSVC
 
LinearSVC() - Constructor for class org.apache.spark.ml.classification.LinearSVC
 
LinearSVCModel - Class in org.apache.spark.ml.classification
:: Experimental :: Linear SVM Model trained by LinearSVC
LinearSVCParams - Interface in org.apache.spark.ml.classification
Params for linear SVM Classifier.
link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.CLogLog$
 
link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Identity$
 
link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Inverse$
 
link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Log$
 
link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Logit$
 
link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Probit$
 
link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Sqrt$
 
link() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
Param for the name of link function which provides the relationship between the linear predictor and the mean of the distribution function.
Link$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Link$
 
linkPower() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
Param for the index in the power link function.
linkPredictionCol() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
Param for link prediction (linear predictor) column name.
listColumns(String) - Method in class org.apache.spark.sql.catalog.Catalog
Returns a list of columns for the given table/view or temporary view.
listColumns(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
Returns a list of columns for the given table/view in the specified database.
listDatabases() - Method in class org.apache.spark.sql.catalog.Catalog
Returns a list of databases available across all sessions.
listDatabases(String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
List the names of all the databases that match the specified pattern.
ListenerBus<L,E> - Interface in org.apache.spark.util
An event bus which posts events to its listeners.
listenerManager() - Method in class org.apache.spark.sql.SparkSession
:: Experimental :: An interface to register custom QueryExecutionListeners that listen for execution metrics.
listenerManager() - Method in class org.apache.spark.sql.SQLContext
An interface to register custom QueryExecutionListeners that listen for execution metrics.
listeners() - Method in interface org.apache.spark.util.ListenerBus
 
listFiles() - Method in class org.apache.spark.SparkContext
Returns a list of file paths that are added to resources.
listFunctions() - Method in class org.apache.spark.sql.catalog.Catalog
Returns a list of functions registered in the current database.
listFunctions(String) - Method in class org.apache.spark.sql.catalog.Catalog
Returns a list of functions registered in the specified database.
listFunctions(String, String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Return the names of all functions that match the given pattern in the database.
listingTable(Seq<String>, Function1<T, Seq<Node>>, Iterable<T>, boolean, Option<String>, Seq<String>, boolean, boolean) - Static method in class org.apache.spark.ui.UIUtils
Returns an HTML table constructed by generating a row for each object in a sequence.
listJars() - Method in class org.apache.spark.SparkContext
Returns a list of jar files that are added to resources.
listOrcFiles(String, Configuration) - Static method in class org.apache.spark.sql.hive.orc.OrcFileOperator
 
listTables() - Method in class org.apache.spark.sql.catalog.Catalog
Returns a list of tables/views in the current database.
listTables(String) - Method in class org.apache.spark.sql.catalog.Catalog
Returns a list of tables/views in the specified database.
listTables(String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns the names of all tables in the given database.
listTables(String, String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns the names of tables in the given database that matches the given pattern.
lit(Object) - Static method in class org.apache.spark.sql.functions
Creates a Column of literal value.
literal(String) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
LIVE_ENTITY_UPDATE_MIN_FLUSH_PERIOD() - Static method in class org.apache.spark.status.config
 
LIVE_ENTITY_UPDATE_PERIOD() - Static method in class org.apache.spark.status.config
 
LiveEntityHelpers - Class in org.apache.spark.status
 
LiveEntityHelpers() - Constructor for class org.apache.spark.status.LiveEntityHelpers
 
LiveExecutor - Class in org.apache.spark.status
 
LiveExecutor(String, long) - Constructor for class org.apache.spark.status.LiveExecutor
 
LiveExecutorStageSummary - Class in org.apache.spark.status
 
LiveExecutorStageSummary(int, int, String) - Constructor for class org.apache.spark.status.LiveExecutorStageSummary
 
LiveJob - Class in org.apache.spark.status
 
LiveJob(int, String, Option<String>, Option<Date>, Seq<Object>, Option<String>, int) - Constructor for class org.apache.spark.status.LiveJob
 
LiveRDD - Class in org.apache.spark.status
 
LiveRDD(RDDInfo) - Constructor for class org.apache.spark.status.LiveRDD
 
LiveRDDDistribution - Class in org.apache.spark.status
 
LiveRDDDistribution(LiveExecutor) - Constructor for class org.apache.spark.status.LiveRDDDistribution
 
LiveRDDPartition - Class in org.apache.spark.status
 
LiveRDDPartition(String) - Constructor for class org.apache.spark.status.LiveRDDPartition
 
LiveStage - Class in org.apache.spark.status
 
LiveStage() - Constructor for class org.apache.spark.status.LiveStage
 
LiveTask - Class in org.apache.spark.status
 
LiveTask(TaskInfo, int, int, Option<Object>) - Constructor for class org.apache.spark.status.LiveTask
 
load(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
 
load(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
 
load(String) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
 
load(String) - Static method in class org.apache.spark.ml.classification.GBTClassifier
 
load(String) - Static method in class org.apache.spark.ml.classification.LinearSVC
 
load(String) - Static method in class org.apache.spark.ml.classification.LinearSVCModel
 
load(String) - Static method in class org.apache.spark.ml.classification.LogisticRegression
 
load(String) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
 
load(String) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
 
load(String) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
 
load(String) - Static method in class org.apache.spark.ml.classification.NaiveBayes
 
load(String) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
 
load(String) - Static method in class org.apache.spark.ml.classification.OneVsRest
 
load(String) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
 
load(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
 
load(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
 
load(String) - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
 
load(String) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
 
load(String) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
 
load(String) - Static method in class org.apache.spark.ml.clustering.GaussianMixture
 
load(String) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
 
load(String) - Static method in class org.apache.spark.ml.clustering.KMeans
 
load(String) - Static method in class org.apache.spark.ml.clustering.KMeansModel
 
load(String) - Static method in class org.apache.spark.ml.clustering.LDA
 
load(String) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
 
load(String) - Static method in class org.apache.spark.ml.clustering.PowerIterationClustering
 
load(String) - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
 
load(String) - Static method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
load(String) - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
 
load(String) - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
 
load(String) - Static method in class org.apache.spark.ml.feature.Binarizer
 
load(String) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
 
load(String) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
 
load(String) - Static method in class org.apache.spark.ml.feature.Bucketizer
 
load(String) - Static method in class org.apache.spark.ml.feature.ChiSqSelector
 
load(String) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
 
load(String) - Static method in class org.apache.spark.ml.feature.ColumnPruner
 
load(String) - Static method in class org.apache.spark.ml.feature.CountVectorizer
 
load(String) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
 
load(String) - Static method in class org.apache.spark.ml.feature.DCT
 
load(String) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
 
load(String) - Static method in class org.apache.spark.ml.feature.FeatureHasher
 
load(String) - Static method in class org.apache.spark.ml.feature.HashingTF
 
load(String) - Static method in class org.apache.spark.ml.feature.IDF
 
load(String) - Static method in class org.apache.spark.ml.feature.IDFModel
 
load(String) - Static method in class org.apache.spark.ml.feature.Imputer
 
load(String) - Static method in class org.apache.spark.ml.feature.ImputerModel
 
load(String) - Static method in class org.apache.spark.ml.feature.IndexToString
 
load(String) - Static method in class org.apache.spark.ml.feature.Interaction
 
load(String) - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
 
load(String) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
 
load(String) - Static method in class org.apache.spark.ml.feature.MinHashLSH
 
load(String) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
 
load(String) - Static method in class org.apache.spark.ml.feature.MinMaxScaler
 
load(String) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
 
load(String) - Static method in class org.apache.spark.ml.feature.NGram
 
load(String) - Static method in class org.apache.spark.ml.feature.Normalizer
 
load(String) - Static method in class org.apache.spark.ml.feature.OneHotEncoder
Deprecated.
 
load(String) - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
 
load(String) - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
 
load(String) - Static method in class org.apache.spark.ml.feature.PCA
 
load(String) - Static method in class org.apache.spark.ml.feature.PCAModel
 
load(String) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
 
load(String) - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
load(String) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
 
load(String) - Static method in class org.apache.spark.ml.feature.RFormula
 
load(String) - Static method in class org.apache.spark.ml.feature.RFormulaModel
 
load(String) - Static method in class org.apache.spark.ml.feature.SQLTransformer
 
load(String) - Static method in class org.apache.spark.ml.feature.StandardScaler
 
load(String) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
 
load(String) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
 
load(String) - Static method in class org.apache.spark.ml.feature.StringIndexer
 
load(String) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
 
load(String) - Static method in class org.apache.spark.ml.feature.Tokenizer
 
load(String) - Static method in class org.apache.spark.ml.feature.VectorAssembler
 
load(String) - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
 
load(String) - Static method in class org.apache.spark.ml.feature.VectorIndexer
 
load(String) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
 
load(String) - Static method in class org.apache.spark.ml.feature.VectorSizeHint
 
load(String) - Static method in class org.apache.spark.ml.feature.VectorSlicer
 
load(String) - Static method in class org.apache.spark.ml.feature.Word2Vec
 
load(String) - Static method in class org.apache.spark.ml.feature.Word2VecModel
 
load(String) - Static method in class org.apache.spark.ml.fpm.FPGrowth
 
load(String) - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
 
load(String) - Static method in class org.apache.spark.ml.Pipeline
 
load(String, SparkContext, String) - Method in class org.apache.spark.ml.Pipeline.SharedReadWrite$
Load metadata and stages for a Pipeline or PipelineModel
load(String) - Static method in class org.apache.spark.ml.PipelineModel
 
load(String) - Static method in class org.apache.spark.ml.r.RWrappers
 
load(String) - Static method in class org.apache.spark.ml.recommendation.ALS
 
load(String) - Static method in class org.apache.spark.ml.recommendation.ALSModel
 
load(String) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
 
load(String) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
load(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
 
load(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
 
load(String) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
 
load(String) - Static method in class org.apache.spark.ml.regression.GBTRegressor
 
load(String) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
 
load(String) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
 
load(String) - Static method in class org.apache.spark.ml.regression.IsotonicRegression
 
load(String) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
 
load(String) - Static method in class org.apache.spark.ml.regression.LinearRegression
 
load(String) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
 
load(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
 
load(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
 
load(String) - Static method in class org.apache.spark.ml.tuning.CrossValidator
 
load(String) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
 
load(String) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
 
load(String) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
 
load(String) - Method in interface org.apache.spark.ml.util.MLReadable
Reads an ML instance from the input path, a shortcut of read.load(path).
load(String) - Method in class org.apache.spark.ml.util.MLReader
Loads the ML component from the input path.
load(SparkContext, String) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionModel
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.classification.NaiveBayesModel
 
load(SparkContext, String) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$
 
load(SparkContext, String) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.classification.SVMModel
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
 
load(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel.SaveLoadV1_0$
 
load(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel.SaveLoadV2_0$
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.clustering.DistributedLDAModel
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.clustering.KMeansModel
 
load(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.KMeansModel.SaveLoadV1_0$
 
load(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.KMeansModel.SaveLoadV2_0$
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.clustering.LocalLDAModel
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel
 
load(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel.SaveLoadV1_0$
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.feature.ChiSqSelectorModel
 
load(SparkContext, String) - Method in class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.feature.Word2VecModel
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.fpm.FPGrowthModel
 
load(SparkContext, String) - Method in class org.apache.spark.mllib.fpm.FPGrowthModel.SaveLoadV1_0$
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.fpm.PrefixSpanModel
 
load(SparkContext, String) - Method in class org.apache.spark.mllib.fpm.PrefixSpanModel.SaveLoadV1_0$
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
Load a model from the given path.
load(SparkContext, String) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel.SaveLoadV1_0$
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.regression.LassoModel
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.regression.LinearRegressionModel
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionModel
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
 
load(SparkContext, String, String, int) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
 
load(SparkContext, String) - Static method in class org.apache.spark.mllib.tree.model.RandomForestModel
 
load(SparkContext, String) - Method in interface org.apache.spark.mllib.util.Loader
Load a model from the given path.
load(String...) - Method in class org.apache.spark.sql.DataFrameReader
Loads input in as a DataFrame, for data sources that support multiple paths.
load() - Method in class org.apache.spark.sql.DataFrameReader
Loads input in as a DataFrame, for data sources that don't require a path (e.g.
load(String) - Method in class org.apache.spark.sql.DataFrameReader
Loads input in as a DataFrame, for data sources that require a path (e.g.
load(Seq<String>) - Method in class org.apache.spark.sql.DataFrameReader
Loads input in as a DataFrame, for data sources that support multiple paths.
load(String) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().load(path).
load(String, String) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().format(source).load(path).
load(String, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().format(source).options(options).load().
load(String, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().format(source).options(options).load().
load(String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().format(source).schema(schema).options(options).load().
load(String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().format(source).schema(schema).options(options).load().
load() - Method in class org.apache.spark.sql.streaming.DataStreamReader
Loads input data stream in as a DataFrame, for data streams that don't require a path (e.g.
load(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Loads input in as a DataFrame, for data streams that read from some path.
loadClass(String, boolean) - Method in class org.apache.spark.util.ChildFirstURLClassLoader
 
loadClass(String, boolean) - Method in class org.apache.spark.util.ParentClassLoader
 
loadData(SparkContext, String, String) - Method in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$
Helper method for loading GLM classification model data.
loadData(SparkContext, String, String, int) - Method in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$
Helper method for loading GLM regression model data.
loadDefaultSparkProperties(SparkConf, String) - Static method in class org.apache.spark.util.Utils
Load default Spark properties from the given file.
loadDefaultStopWords(String) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
Loads the default stop words for the given language.
loadDynamicPartitions(String, String, String, LinkedHashMap<String, String>, boolean, int) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Loads new dynamic partitions into an existing table.
Loader<M extends Saveable> - Interface in org.apache.spark.mllib.util
:: DeveloperApi ::
loadExtensions(Class<T>, Seq<String>, SparkConf) - Static method in class org.apache.spark.util.Utils
Create instances of extension classes.
loadImpl(String, SparkSession, String, String) - Static method in class org.apache.spark.ml.tree.EnsembleModelReadWrite
Helper method for loading a tree ensemble from disk.
loadImpl(Dataset<Row>, Item, ClassTag<Item>) - Method in class org.apache.spark.mllib.fpm.FPGrowthModel.SaveLoadV1_0$
 
loadImpl(Dataset<Row>, Item, ClassTag<Item>) - Method in class org.apache.spark.mllib.fpm.PrefixSpanModel.SaveLoadV1_0$
 
loadLabeledPoints(SparkContext, String, int) - Static method in class org.apache.spark.mllib.util.MLUtils
Loads labeled points saved using RDD[LabeledPoint].saveAsTextFile.
loadLabeledPoints(SparkContext, String) - Static method in class org.apache.spark.mllib.util.MLUtils
Loads labeled points saved using RDD[LabeledPoint].saveAsTextFile with the default number of partitions.
loadLibSVMFile(SparkContext, String, int, int) - Static method in class org.apache.spark.mllib.util.MLUtils
Loads labeled data in the LIBSVM format into an RDD[LabeledPoint].
loadLibSVMFile(SparkContext, String, int) - Static method in class org.apache.spark.mllib.util.MLUtils
Loads labeled data in the LIBSVM format into an RDD[LabeledPoint], with the default number of partitions.
loadLibSVMFile(SparkContext, String) - Static method in class org.apache.spark.mllib.util.MLUtils
Loads binary labeled data in the LIBSVM format into an RDD[LabeledPoint], with number of features determined automatically and the default number of partitions.
loadPartition(String, String, String, LinkedHashMap<String, String>, boolean, boolean, boolean) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Loads a static partition into an existing table.
loadTable(String, String, boolean, boolean) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Loads data into an existing table.
loadTreeNodes(String, org.apache.spark.ml.util.DefaultParamsReader.Metadata, SparkSession) - Static method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite
Load a decision tree from a file.
loadVectors(SparkContext, String, int) - Static method in class org.apache.spark.mllib.util.MLUtils
Loads vectors saved using RDD[Vector].saveAsTextFile.
loadVectors(SparkContext, String) - Static method in class org.apache.spark.mllib.util.MLUtils
Loads vectors saved using RDD[Vector].saveAsTextFile with the default number of partitions.
LOCAL_BLOCKS_FETCHED() - Method in class org.apache.spark.InternalAccumulator.shuffleRead$
 
LOCAL_BYTES_READ() - Method in class org.apache.spark.InternalAccumulator.shuffleRead$
 
LOCAL_CLUSTER_REGEX() - Static method in class org.apache.spark.SparkMasterRegex
 
LOCAL_N_FAILURES_REGEX() - Static method in class org.apache.spark.SparkMasterRegex
 
LOCAL_N_REGEX() - Static method in class org.apache.spark.SparkMasterRegex
 
localBlocksFetched() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
 
localBlocksFetched() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
 
localBytesRead() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
 
localCanonicalHostName() - Static method in class org.apache.spark.util.Utils
Get the local machine's FQDN.
localCheckpoint() - Method in class org.apache.spark.rdd.RDD
Mark this RDD for local checkpointing using Spark's existing caching layer.
localCheckpoint() - Method in class org.apache.spark.sql.Dataset
Eagerly locally checkpoints a Dataset and return the new Dataset.
localCheckpoint(boolean) - Method in class org.apache.spark.sql.Dataset
Locally checkpoints a Dataset and return the new Dataset.
locale() - Method in class org.apache.spark.ml.feature.StopWordsRemover
Locale of the input for case insensitive matching.
localHostName() - Static method in class org.apache.spark.util.Utils
Get the local machine's hostname.
localHostNameForURI() - Static method in class org.apache.spark.util.Utils
Get the local machine's URI.
LOCALITY() - Static method in class org.apache.spark.status.TaskIndexNames
 
localityAwareTasks() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors
 
localitySummary() - Method in class org.apache.spark.status.LiveStage
 
LocalKMeans - Class in org.apache.spark.mllib.clustering
An utility object to run K-means locally.
LocalKMeans() - Constructor for class org.apache.spark.mllib.clustering.LocalKMeans
 
LocalLDAModel - Class in org.apache.spark.ml.clustering
Local (non-distributed) model fitted by LDA.
LocalLDAModel - Class in org.apache.spark.mllib.clustering
Local LDA model.
localSeqToDatasetHolder(Seq<T>, Encoder<T>) - Method in class org.apache.spark.sql.SQLImplicits
Creates a Dataset from a local Seq.
localSparkRPackagePath() - Static method in class org.apache.spark.api.r.RUtils
Get the SparkR package path in the local spark distribution.
localValue() - Method in class org.apache.spark.Accumulable
Deprecated.
Get the current value of this accumulator from within a task.
locate(String, Column) - Static method in class org.apache.spark.sql.functions
Locate the position of the first occurrence of substr.
locate(String, Column, int) - Static method in class org.apache.spark.sql.functions
Locate the position of the first occurrence of substr in a string column, after position pos.
location() - Method in interface org.apache.spark.scheduler.MapStatus
Location where this task was run.
location() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
 
location() - Method in class org.apache.spark.ui.storage.ExecutorStreamSummary
 
locations() - Method in class org.apache.spark.storage.BlockManagerMessages.BlockLocationsAndStatus
 
locationUri() - Method in class org.apache.spark.sql.catalog.Database
 
log() - Method in interface org.apache.spark.internal.Logging
 
log(Function0<Parsers.Parser<T>>, String) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
log(Column) - Static method in class org.apache.spark.sql.functions
Computes the natural logarithm of the given value.
log(String) - Static method in class org.apache.spark.sql.functions
Computes the natural logarithm of the given column.
log(double, Column) - Static method in class org.apache.spark.sql.functions
Returns the first argument-base logarithm of the second argument.
log(double, String) - Static method in class org.apache.spark.sql.functions
Returns the first argument-base logarithm of the second argument.
Log$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Log$
 
log10(Column) - Static method in class org.apache.spark.sql.functions
Computes the logarithm of the given value in base 10.
log10(String) - Static method in class org.apache.spark.sql.functions
Computes the logarithm of the given value in base 10.
log1p(Column) - Static method in class org.apache.spark.sql.functions
Computes the natural logarithm of the given value plus one.
log1p(String) - Static method in class org.apache.spark.sql.functions
Computes the natural logarithm of the given column plus one.
log2(Column) - Static method in class org.apache.spark.sql.functions
Computes the logarithm of the given column in base 2.
log2(String) - Static method in class org.apache.spark.sql.functions
Computes the logarithm of the given value in base 2.
log_() - Method in interface org.apache.spark.internal.Logging
 
logDebug(Function0<String>) - Method in interface org.apache.spark.internal.Logging
 
logDebug(Function0<String>, Throwable) - Method in interface org.apache.spark.internal.Logging
 
logDeprecationWarning(String) - Static method in class org.apache.spark.SparkConf
Logs a warning message if the given config key is deprecated.
logError(Function0<String>) - Method in interface org.apache.spark.internal.Logging
 
logError(Function0<String>, Throwable) - Method in interface org.apache.spark.internal.Logging
 
logEvent() - Method in interface org.apache.spark.scheduler.SparkListenerEvent
 
Logging - Interface in org.apache.spark.internal
Utility trait for classes that want to log data.
logInfo(Function0<String>) - Method in interface org.apache.spark.internal.Logging
 
logInfo(Function0<String>, Throwable) - Method in interface org.apache.spark.internal.Logging
 
LogisticGradient - Class in org.apache.spark.mllib.optimization
:: DeveloperApi :: Compute gradient and loss for a multinomial logistic loss function, as used in multi-class classification (it is also used in binary logistic regression).
LogisticGradient(int) - Constructor for class org.apache.spark.mllib.optimization.LogisticGradient
 
LogisticGradient() - Constructor for class org.apache.spark.mllib.optimization.LogisticGradient
 
LogisticRegression - Class in org.apache.spark.ml.classification
Logistic regression.
LogisticRegression(String) - Constructor for class org.apache.spark.ml.classification.LogisticRegression
 
LogisticRegression() - Constructor for class org.apache.spark.ml.classification.LogisticRegression
 
LogisticRegressionDataGenerator - Class in org.apache.spark.mllib.util
:: DeveloperApi :: Generate test data for LogisticRegression.
LogisticRegressionDataGenerator() - Constructor for class org.apache.spark.mllib.util.LogisticRegressionDataGenerator
 
LogisticRegressionModel - Class in org.apache.spark.ml.classification
Model produced by LogisticRegression.
LogisticRegressionModel - Class in org.apache.spark.mllib.classification
Classification model trained using Multinomial/Binary Logistic Regression.
LogisticRegressionModel(Vector, double, int, int) - Constructor for class org.apache.spark.mllib.classification.LogisticRegressionModel
 
LogisticRegressionModel(Vector, double) - Constructor for class org.apache.spark.mllib.classification.LogisticRegressionModel
Constructs a LogisticRegressionModel with weights and intercept for binary classification.
LogisticRegressionParams - Interface in org.apache.spark.ml.classification
Params for logistic regression.
LogisticRegressionSummary - Interface in org.apache.spark.ml.classification
:: Experimental :: Abstraction for logistic regression results for a given model.
LogisticRegressionSummaryImpl - Class in org.apache.spark.ml.classification
Multiclass logistic regression results for a given model.
LogisticRegressionSummaryImpl(Dataset<Row>, String, String, String, String) - Constructor for class org.apache.spark.ml.classification.LogisticRegressionSummaryImpl
 
LogisticRegressionTrainingSummary - Interface in org.apache.spark.ml.classification
:: Experimental :: Abstraction for multiclass logistic regression training results.
LogisticRegressionTrainingSummaryImpl - Class in org.apache.spark.ml.classification
Multiclass logistic regression training results.
LogisticRegressionTrainingSummaryImpl(Dataset<Row>, String, String, String, String, double[]) - Constructor for class org.apache.spark.ml.classification.LogisticRegressionTrainingSummaryImpl
 
LogisticRegressionWithLBFGS - Class in org.apache.spark.mllib.classification
Train a classification model for Multinomial/Binary Logistic Regression using Limited-memory BFGS.
LogisticRegressionWithLBFGS() - Constructor for class org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
 
LogisticRegressionWithSGD - Class in org.apache.spark.mllib.classification
Train a classification model for Binary Logistic Regression using Stochastic Gradient Descent.
LogisticRegressionWithSGD() - Constructor for class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
Deprecated.
Use ml.classification.LogisticRegression or LogisticRegressionWithLBFGS. Since 2.0.0.
Logit$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Logit$
 
logLikelihood() - Method in class org.apache.spark.ml.clustering.ExpectationAggregator
 
logLikelihood() - Method in class org.apache.spark.ml.clustering.GaussianMixtureSummary
 
logLikelihood(Dataset<?>) - Method in class org.apache.spark.ml.clustering.LDAModel
Calculates a lower bound on the log likelihood of the entire corpus.
logLikelihood() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
Log likelihood of the observed tokens in the training set, given the current parameter estimates: log P(docs | topics, topic distributions for docs, alpha, eta)
logLikelihood() - Method in class org.apache.spark.mllib.clustering.ExpectationSum
 
logLikelihood(RDD<Tuple2<Object, Vector>>) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
Calculates a lower bound on the log likelihood of the entire corpus.
logLikelihood(JavaPairRDD<Long, Vector>) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
Java-friendly version of logLikelihood
LogLoss - Class in org.apache.spark.mllib.tree.loss
:: DeveloperApi :: Class for log loss calculation (for classification).
LogLoss() - Constructor for class org.apache.spark.mllib.tree.loss.LogLoss
 
logName() - Method in interface org.apache.spark.internal.Logging
 
LogNormalGenerator - Class in org.apache.spark.mllib.random
:: DeveloperApi :: Generates i.i.d.
LogNormalGenerator(double, double) - Constructor for class org.apache.spark.mllib.random.LogNormalGenerator
 
logNormalGraph(SparkContext, int, int, double, double, long) - Static method in class org.apache.spark.graphx.util.GraphGenerators
Generate a graph whose vertex out degree distribution is log normal.
logNormalJavaRDD(JavaSparkContext, double, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Java-friendly version of RandomRDDs.logNormalRDD.
logNormalJavaRDD(JavaSparkContext, double, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.logNormalJavaRDD with the default seed.
logNormalJavaRDD(JavaSparkContext, double, double, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.logNormalJavaRDD with the default number of partitions and the default seed.
logNormalJavaVectorRDD(JavaSparkContext, double, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Java-friendly version of RandomRDDs.logNormalVectorRDD.
logNormalJavaVectorRDD(JavaSparkContext, double, double, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.logNormalJavaVectorRDD with the default seed.
logNormalJavaVectorRDD(JavaSparkContext, double, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.logNormalJavaVectorRDD with the default number of partitions and the default seed.
logNormalRDD(SparkContext, double, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Generates an RDD comprised of i.i.d. samples from the log normal distribution with the input mean and standard deviation
logNormalVectorRDD(SparkContext, double, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from a log normal distribution.
logpdf(Vector) - Method in class org.apache.spark.ml.stat.distribution.MultivariateGaussian
Returns the log-density of this multivariate Gaussian at given point, x
logpdf(Vector) - Method in class org.apache.spark.mllib.stat.distribution.MultivariateGaussian
Returns the log-density of this multivariate Gaussian at given point, x
logPerplexity(Dataset<?>) - Method in class org.apache.spark.ml.clustering.LDAModel
Calculate an upper bound on perplexity.
logPerplexity(RDD<Tuple2<Object, Vector>>) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
Calculate an upper bound on perplexity.
logPerplexity(JavaPairRDD<Long, Vector>) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
Java-friendly version of logPerplexity
logPrior() - Method in class org.apache.spark.ml.clustering.DistributedLDAModel
Log probability of the current parameter estimate: log P(topics, topic distributions for docs | Dirichlet hyperparameters)
logPrior() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
Log probability of the current parameter estimate: log P(topics, topic distributions for docs | alpha, eta)
logStartFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
logStartToJson(SparkListenerLogStart) - Static method in class org.apache.spark.util.JsonProtocol
 
logTrace(Function0<String>) - Method in interface org.apache.spark.internal.Logging
 
logTrace(Function0<String>, Throwable) - Method in interface org.apache.spark.internal.Logging
 
logTuningParams(org.apache.spark.ml.util.Instrumentation) - Method in interface org.apache.spark.ml.tuning.ValidatorParams
Instrumentation logging for tuning params including the inner estimator and evaluator info.
logUncaughtExceptions(Function0<T>) - Static method in class org.apache.spark.util.Utils
Execute the given block, logging and re-throwing any uncaught exception.
logUrlMap() - Method in class org.apache.spark.scheduler.cluster.ExecutorInfo
 
logUrls() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor
 
logWarning(Function0<String>) - Method in interface org.apache.spark.internal.Logging
 
logWarning(Function0<String>, Throwable) - Method in interface org.apache.spark.internal.Logging
 
LONG() - Static method in class org.apache.spark.sql.Encoders
An encoder for nullable long type.
longAccumulator() - Method in class org.apache.spark.SparkContext
Create and register a long accumulator, which starts with 0 and accumulates inputs by add.
longAccumulator(String) - Method in class org.apache.spark.SparkContext
Create and register a long accumulator, which starts with 0 and accumulates inputs by add.
LongAccumulator - Class in org.apache.spark.util
An accumulator for computing sum, count, and average of 64-bit integers.
LongAccumulator() - Constructor for class org.apache.spark.util.LongAccumulator
 
LongAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.LongAccumulatorParam$
Deprecated.
 
LongParam - Class in org.apache.spark.ml.param
:: DeveloperApi :: Specialized version of Param[Long] for Java.
LongParam(String, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.LongParam
 
LongParam(String, String, String) - Constructor for class org.apache.spark.ml.param.LongParam
 
LongParam(Identifiable, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.LongParam
 
LongParam(Identifiable, String, String) - Constructor for class org.apache.spark.ml.param.LongParam
 
LongType - Static variable in class org.apache.spark.sql.types.DataTypes
Gets the LongType object.
LongType - Class in org.apache.spark.sql.types
The data type representing Long values.
LongType() - Constructor for class org.apache.spark.sql.types.LongType
 
lookup(K) - Method in class org.apache.spark.api.java.JavaPairRDD
Return the list of values in the RDD for key key.
lookup(K) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return the list of values in the RDD for key key.
lookupRpcTimeout(SparkConf) - Static method in class org.apache.spark.util.RpcUtils
Returns the default Spark timeout to use for RPC remote endpoint lookup.
loss(DenseMatrix<Object>, DenseMatrix<Object>, DenseMatrix<Object>) - Method in interface org.apache.spark.ml.ann.LossFunction
Returns the value of loss function.
loss() - Method in interface org.apache.spark.ml.optim.aggregator.DifferentiableLossAggregator
The current loss value of this aggregator.
loss() - Method in interface org.apache.spark.ml.param.shared.HasLoss
Param for the loss function to be optimized.
loss() - Method in class org.apache.spark.ml.regression.AFTAggregator
 
loss() - Method in interface org.apache.spark.ml.regression.LinearRegressionParams
The loss function to be optimized.
loss() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
Loss - Interface in org.apache.spark.mllib.tree.loss
:: DeveloperApi :: Trait for adding "pluggable" loss functions for the gradient boosting algorithm.
Losses - Class in org.apache.spark.mllib.tree.loss
 
Losses() - Constructor for class org.apache.spark.mllib.tree.loss.Losses
 
LossFunction - Interface in org.apache.spark.ml.ann
Trait for loss function
LossReasonPending - Class in org.apache.spark.scheduler
A loss reason that means we don't yet know why the executor exited.
LossReasonPending() - Constructor for class org.apache.spark.scheduler.LossReasonPending
 
lossSum() - Method in interface org.apache.spark.ml.optim.aggregator.DifferentiableLossAggregator
 
lossType() - Method in interface org.apache.spark.ml.tree.GBTClassifierParams
Loss function which GBT tries to minimize.
lossType() - Method in interface org.apache.spark.ml.tree.GBTRegressorParams
Loss function which GBT tries to minimize.
LOST() - Static method in class org.apache.spark.TaskState
 
low() - Method in class org.apache.spark.partial.BoundedDouble
 
lower(Column) - Static method in class org.apache.spark.sql.functions
Converts a string column to lower case.
lowerBoundsOnCoefficients() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
The lower bounds on coefficients if fitting under bound constrained optimization.
lowerBoundsOnIntercepts() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
The lower bounds on intercepts if fitting under bound constrained optimization.
LowPrioritySQLImplicits - Interface in org.apache.spark.sql
Lower priority implicit methods for converting Scala objects into Datasets.
lpad(Column, int, String) - Static method in class org.apache.spark.sql.functions
Left-pad the string column with pad to a length of len.
LSHParams - Interface in org.apache.spark.ml.feature
Params for LSH.
lt(double) - Static method in class org.apache.spark.ml.param.ParamValidators
Check if value is less than upperBound
lt(Object) - Method in class org.apache.spark.sql.Column
Less than.
ltEq(double) - Static method in class org.apache.spark.ml.param.ParamValidators
Check if value is less than or equal to upperBound
ltrim(Column) - Static method in class org.apache.spark.sql.functions
Trim the spaces from left end for the specified string value.
ltrim(Column, String) - Static method in class org.apache.spark.sql.functions
Trim the specified character string from left end for the specified string column.
LZ4CompressionCodec - Class in org.apache.spark.io
:: DeveloperApi :: LZ4 implementation of CompressionCodec.
LZ4CompressionCodec(SparkConf) - Constructor for class org.apache.spark.io.LZ4CompressionCodec
 
LZFCompressionCodec - Class in org.apache.spark.io
:: DeveloperApi :: LZF implementation of CompressionCodec.
LZFCompressionCodec(SparkConf) - Constructor for class org.apache.spark.io.LZFCompressionCodec
 

M

main(String[]) - Static method in class org.apache.spark.ml.param.shared.SharedParamsCodeGen
 
main(String[]) - Static method in class org.apache.spark.mllib.util.KMeansDataGenerator
 
main(String[]) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
 
main(String[]) - Static method in class org.apache.spark.mllib.util.LogisticRegressionDataGenerator
 
main(String[]) - Static method in class org.apache.spark.mllib.util.MFDataGenerator
 
main(String[]) - Static method in class org.apache.spark.mllib.util.SVMDataGenerator
 
main(String[]) - Static method in class org.apache.spark.streaming.util.RawTextSender
 
main(String[]) - Static method in class org.apache.spark.ui.UIWorkloadGenerator
 
main(String[]) - Method in interface org.apache.spark.util.CommandLineUtils
 
majorMinorVersion(String) - Static method in class org.apache.spark.util.VersionUtils
Given a Spark version string, return the (major version number, minor version number).
majorVersion(String) - Static method in class org.apache.spark.util.VersionUtils
Given a Spark version string, return the major version number.
makeBinarySearch(Ordering<K>, ClassTag<K>) - Static method in class org.apache.spark.util.CollectionsUtils
 
makeDescription(String, String, boolean) - Static method in class org.apache.spark.ui.UIUtils
Returns HTML rendering of a job or stage description.
makeDriverRef(String, SparkConf, org.apache.spark.rpc.RpcEnv) - Static method in class org.apache.spark.util.RpcUtils
Retrieve a RpcEndpointRef which is located in the driver via its name.
makeHref(boolean, String, String) - Static method in class org.apache.spark.ui.UIUtils
Return the correct Href after checking if master is running in the reverse proxy mode or not.
makeProgressBar(int, int, int, int, Map<String, Object>, int) - Static method in class org.apache.spark.ui.UIUtils
 
makeRDD(Seq<T>, int, ClassTag<T>) - Method in class org.apache.spark.SparkContext
Distribute a local Scala collection to form an RDD.
makeRDD(Seq<Tuple2<T, Seq<String>>>, ClassTag<T>) - Method in class org.apache.spark.SparkContext
Distribute a local Scala collection to form an RDD, with one or more location preferences (hostnames of Spark nodes) for each object.
makeRDDForPartitionedTable(Seq<Partition>) - Method in interface org.apache.spark.sql.hive.TableReader
 
makeRDDForTable(Table) - Method in interface org.apache.spark.sql.hive.TableReader
 
map(Function<T, R>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return a new RDD by applying a function to all elements of this RDD.
map(Function1<Object, Object>) - Method in interface org.apache.spark.ml.linalg.Matrix
Map the values of this matrix using a function.
map(Function1<Object, Object>) - Method in interface org.apache.spark.mllib.linalg.Matrix
Map the values of this matrix using a function.
map(Function1<R, T>) - Method in class org.apache.spark.partial.PartialResult
Transform this PartialResult into a PartialResult of type T.
map(Function1<T, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
Return a new RDD by applying a function to all elements of this RDD.
map(DataType, DataType) - Method in class org.apache.spark.sql.ColumnName
Creates a new StructField of type map.
map(MapType) - Method in class org.apache.spark.sql.ColumnName
 
map(Function1<T, U>, Encoder<U>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: (Scala-specific) Returns a new Dataset that contains the result of applying func to each element.
map(MapFunction<T, U>, Encoder<U>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: (Java-specific) Returns a new Dataset that contains the result of applying func to each element.
map(Column...) - Static method in class org.apache.spark.sql.functions
Creates a new map column.
map(Seq<Column>) - Static method in class org.apache.spark.sql.functions
Creates a new map column.
map(Function<T, U>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream by applying a function to all elements of this DStream.
map(Function1<T, U>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream by applying a function to all elements of this DStream.
map_concat(Column...) - Static method in class org.apache.spark.sql.functions
Returns the union of all the given maps.
map_concat(Seq<Column>) - Static method in class org.apache.spark.sql.functions
Returns the union of all the given maps.
map_from_arrays(Column, Column) - Static method in class org.apache.spark.sql.functions
Creates a new map column.
map_from_entries(Column) - Static method in class org.apache.spark.sql.functions
Returns a map created from the given array of entries.
map_keys(Column) - Static method in class org.apache.spark.sql.functions
Returns an unordered array containing the keys of the map.
map_values(Column) - Static method in class org.apache.spark.sql.functions
Returns an unordered array containing the values of the map.
mapAsSerializableJavaMap(Map<A, B>) - Static method in class org.apache.spark.api.java.JavaUtils
 
mapEdgePartitions(Function2<Object, EdgePartition<ED, VD>, EdgePartition<ED2, VD2>>, ClassTag<ED2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
mapEdges(Function1<Edge<ED>, ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
Transforms each edge attribute in the graph using the map function.
mapEdges(Function2<Object, Iterator<Edge<ED>>, Iterator<ED2>>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
Transforms each edge attribute using the map function, passing it a whole partition at a time.
mapEdges(Function2<Object, Iterator<Edge<ED>>, Iterator<ED2>>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
 
mapFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-------------------------------- * Util JSON deserialization methods |
MapFunction<T,U> - Interface in org.apache.spark.api.java.function
Base interface for a map function used in Dataset's map function.
mapGroups(Function2<K, Iterator<V>, U>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
(Scala-specific) Applies the given function to each group of data.
mapGroups(MapGroupsFunction<K, V, U>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
(Java-specific) Applies the given function to each group of data.
MapGroupsFunction<K,V,R> - Interface in org.apache.spark.api.java.function
Base interface for a map function used in GroupedDataset's mapGroup function.
mapGroupsWithState(Function3<K, Iterator<V>, GroupState<S>, U>, Encoder<S>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
::Experimental:: (Scala-specific) Applies the given function to each group of data, while maintaining a user-defined per-group state.
mapGroupsWithState(GroupStateTimeout, Function3<K, Iterator<V>, GroupState<S>, U>, Encoder<S>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
::Experimental:: (Scala-specific) Applies the given function to each group of data, while maintaining a user-defined per-group state.
mapGroupsWithState(MapGroupsWithStateFunction<K, V, S, U>, Encoder<S>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
::Experimental:: (Java-specific) Applies the given function to each group of data, while maintaining a user-defined per-group state.
mapGroupsWithState(MapGroupsWithStateFunction<K, V, S, U>, Encoder<S>, Encoder<U>, GroupStateTimeout) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
::Experimental:: (Java-specific) Applies the given function to each group of data, while maintaining a user-defined per-group state.
MapGroupsWithStateFunction<K,V,S,R> - Interface in org.apache.spark.api.java.function
mapId() - Method in class org.apache.spark.FetchFailed
 
mapId() - Method in class org.apache.spark.storage.ShuffleBlockId
 
mapId() - Method in class org.apache.spark.storage.ShuffleDataBlockId
 
mapId() - Method in class org.apache.spark.storage.ShuffleIndexBlockId
 
mapOutputTracker() - Method in class org.apache.spark.SparkEnv
 
MapOutputTrackerMessage - Interface in org.apache.spark
 
mapPartitions(FlatMapFunction<Iterator<T>, U>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return a new RDD by applying a function to each partition of this RDD.
mapPartitions(FlatMapFunction<Iterator<T>, U>, boolean) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return a new RDD by applying a function to each partition of this RDD.
mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
Return a new RDD by applying a function to each partition of this RDD.
mapPartitions(Function1<Iterator<T>, Iterator<S>>, boolean, ClassTag<S>) - Method in class org.apache.spark.rdd.RDDBarrier
:: Experimental :: Returns a new RDD by applying a function to each partition of the wrapped RDD, where tasks are launched together in a barrier stage.
mapPartitions(Function1<Iterator<T>, Iterator<U>>, Encoder<U>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: (Scala-specific) Returns a new Dataset that contains the result of applying func to each partition.
mapPartitions(MapPartitionsFunction<T, U>, Encoder<U>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: (Java-specific) Returns a new Dataset that contains the result of applying f to each partition.
mapPartitions(FlatMapFunction<Iterator<T>, U>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD is generated by applying mapPartitions() to each RDDs of this DStream.
mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD is generated by applying mapPartitions() to each RDDs of this DStream.
MapPartitionsFunction<T,U> - Interface in org.apache.spark.api.java.function
Base interface for function used in Dataset's mapPartitions.
mapPartitionsToDouble(DoubleFlatMapFunction<Iterator<T>>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return a new RDD by applying a function to each partition of this RDD.
mapPartitionsToDouble(DoubleFlatMapFunction<Iterator<T>>, boolean) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return a new RDD by applying a function to each partition of this RDD.
mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return a new RDD by applying a function to each partition of this RDD.
mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>, boolean) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return a new RDD by applying a function to each partition of this RDD.
mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD is generated by applying mapPartitions() to each RDDs of this DStream.
mapPartitionsWithIndex(Function2<Integer, Iterator<T>, Iterator<R>>, boolean) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return a new RDD by applying a function to each partition of this RDD, while tracking the index of the original partition.
mapPartitionsWithIndex(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
Return a new RDD by applying a function to each partition of this RDD, while tracking the index of the original partition.
mapPartitionsWithInputSplit(Function2<InputSplit, Iterator<Tuple2<K, V>>, Iterator<R>>, boolean) - Method in class org.apache.spark.api.java.JavaHadoopRDD
Maps over a partition, providing the InputSplit that was used as the base of the partition.
mapPartitionsWithInputSplit(Function2<InputSplit, Iterator<Tuple2<K, V>>, Iterator<R>>, boolean) - Method in class org.apache.spark.api.java.JavaNewHadoopRDD
Maps over a partition, providing the InputSplit that was used as the base of the partition.
mapPartitionsWithInputSplit(Function2<InputSplit, Iterator<Tuple2<K, V>>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.HadoopRDD
Maps over a partition, providing the InputSplit that was used as the base of the partition.
mapPartitionsWithInputSplit(Function2<InputSplit, Iterator<Tuple2<K, V>>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.NewHadoopRDD
Maps over a partition, providing the InputSplit that was used as the base of the partition.
mapredInputFormat() - Method in class org.apache.spark.scheduler.InputFormatInfo
 
mapreduceInputFormat() - Method in class org.apache.spark.scheduler.InputFormatInfo
 
mapSideCombine() - Method in class org.apache.spark.ShuffleDependency
 
MapStatus - Interface in org.apache.spark.scheduler
Result returned by a ShuffleMapTask to a scheduler.
mapStatuses() - Method in class org.apache.spark.ShuffleStatus
MapStatus for each partition.
mapToDouble(DoubleFunction<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return a new RDD by applying a function to all elements of this RDD.
mapToJson(Map<String, String>) - Static method in class org.apache.spark.util.JsonProtocol
------------------------------ * Util JSON serialization methods |
mapToPair(PairFunction<T, K2, V2>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return a new RDD by applying a function to all elements of this RDD.
mapToPair(PairFunction<T, K2, V2>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream by applying a function to all elements of this DStream.
mapTriplets(Function1<EdgeTriplet<VD, ED>, ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
Transforms each edge attribute using the map function, passing it the adjacent vertex attributes as well.
mapTriplets(Function1<EdgeTriplet<VD, ED>, ED2>, TripletFields, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
Transforms each edge attribute using the map function, passing it the adjacent vertex attributes as well.
mapTriplets(Function2<Object, Iterator<EdgeTriplet<VD, ED>>, Iterator<ED2>>, TripletFields, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
Transforms each edge attribute a partition at a time using the map function, passing it the adjacent vertex attributes as well.
mapTriplets(Function2<Object, Iterator<EdgeTriplet<VD, ED>>, Iterator<ED2>>, TripletFields, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
 
MapType - Class in org.apache.spark.sql.types
The data type for Maps.
MapType(DataType, DataType, boolean) - Constructor for class org.apache.spark.sql.types.MapType
 
MapType() - Constructor for class org.apache.spark.sql.types.MapType
No-arg constructor for kryo.
mapValues(Function<V, U>) - Method in class org.apache.spark.api.java.JavaPairRDD
Pass each value in the key-value pair RDD through a map function without changing the keys; this also retains the original RDD's partitioning.
mapValues(Function1<Edge<ED>, ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.EdgeRDD
Map the values in an edge partitioning preserving the structure but changing the values.
mapValues(Function1<Edge<ED>, ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
mapValues(Function1<VD, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
mapValues(Function2<Object, VD, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
mapValues(Function1<VD, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
Maps each vertex attribute, preserving the index.
mapValues(Function2<Object, VD, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
Maps each vertex attribute, additionally supplying the vertex ID.
mapValues(Function1<V, U>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Pass each value in the key-value pair RDD through a map function without changing the keys; this also retains the original RDD's partitioning.
mapValues(Function1<V, W>, Encoder<W>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
Returns a new KeyValueGroupedDataset where the given function func has been applied to the data.
mapValues(MapFunction<V, W>, Encoder<W>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
Returns a new KeyValueGroupedDataset where the given function func has been applied to the data.
mapValues(Function<V, U>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying a map function to the value of each key-value pairs in 'this' DStream without changing the key.
mapValues(Function1<V, U>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying a map function to the value of each key-value pairs in 'this' DStream without changing the key.
mapVertices(Function2<Object, VD, VD2>, ClassTag<VD2>, Predef.$eq$colon$eq<VD, VD2>) - Method in class org.apache.spark.graphx.Graph
Transforms each vertex attribute in the graph using the map function.
mapVertices(Function2<Object, VD, VD2>, ClassTag<VD2>, Predef.$eq$colon$eq<VD, VD2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
 
mapWithState(StateSpec<K, V, StateType, MappedType>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
:: Experimental :: Return a JavaMapWithStateDStream by applying a function to every key-value element of this stream, while maintaining some state data for each unique key.
mapWithState(StateSpec<K, V, StateType, MappedType>, ClassTag<StateType>, ClassTag<MappedType>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
:: Experimental :: Return a MapWithStateDStream by applying a function to every key-value element of this stream, while maintaining some state data for each unique key.
MapWithStateDStream<KeyType,ValueType,StateType,MappedType> - Class in org.apache.spark.streaming.dstream
:: Experimental :: DStream representing the stream of data generated by mapWithState operation on a pair DStream.
MapWithStateDStream(StreamingContext, ClassTag<MappedType>) - Constructor for class org.apache.spark.streaming.dstream.MapWithStateDStream
 
mark(int) - Method in class org.apache.spark.storage.BufferReleasingInputStream
 
markSupported() - Method in class org.apache.spark.storage.BufferReleasingInputStream
 
mask(Graph<VD2, ED2>, ClassTag<VD2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
Restricts the graph to only the vertices and edges that are also in other, but keeps the attributes from this graph.
mask(Graph<VD2, ED2>, ClassTag<VD2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
 
master() - Method in class org.apache.spark.api.java.JavaSparkContext
 
master() - Method in class org.apache.spark.SparkContext
 
master(String) - Method in class org.apache.spark.sql.SparkSession.Builder
Sets the Spark master URL to connect to, such as "local" to run locally, "local[4]" to run locally with 4 cores, or "spark://master:7077" to run on a Spark standalone cluster.
Matrices - Class in org.apache.spark.ml.linalg
Factory methods for Matrix.
Matrices() - Constructor for class org.apache.spark.ml.linalg.Matrices
 
Matrices - Class in org.apache.spark.mllib.linalg
Factory methods for Matrix.
Matrices() - Constructor for class org.apache.spark.mllib.linalg.Matrices
 
Matrix - Interface in org.apache.spark.ml.linalg
Trait for a local matrix.
Matrix - Interface in org.apache.spark.mllib.linalg
Trait for a local matrix.
MatrixEntry - Class in org.apache.spark.mllib.linalg.distributed
Represents an entry in a distributed matrix.
MatrixEntry(long, long, double) - Constructor for class org.apache.spark.mllib.linalg.distributed.MatrixEntry
 
MatrixFactorizationModel - Class in org.apache.spark.mllib.recommendation
Model representing the result of matrix factorization.
MatrixFactorizationModel(int, RDD<Tuple2<Object, double[]>>, RDD<Tuple2<Object, double[]>>) - Constructor for class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
 
MatrixFactorizationModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.recommendation
 
MatrixImplicits - Class in org.apache.spark.mllib.linalg
Implicit methods available in Scala for converting Matrix to Matrix and vice versa.
MatrixImplicits() - Constructor for class org.apache.spark.mllib.linalg.MatrixImplicits
 
MatrixType() - Static method in class org.apache.spark.ml.linalg.SQLDataTypes
Data type for Matrix.
max() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Returns the maximum element from this RDD as defined by the default comparator natural order.
max(Comparator<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Returns the maximum element from this RDD as defined by the specified Comparator[T].
MAX() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
 
max() - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
max() - Method in interface org.apache.spark.ml.feature.MinMaxScalerParams
upper bound after transformation, shared by all features Default: 1.0
max(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
max(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
max() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
Maximum value of each dimension.
max() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
Maximum value of each column.
max(Ordering<T>) - Method in class org.apache.spark.rdd.RDD
Returns the max of this RDD as defined by the implicit Ordering[T].
max(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the maximum value of the expression in a group.
max(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the maximum value of the column in a group.
max(String...) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Compute the max value for each numeric columns for each group.
max(Seq<String>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Compute the max value for each numeric columns for each group.
max(Duration) - Method in class org.apache.spark.streaming.Duration
 
max(Time) - Method in class org.apache.spark.streaming.Time
 
max(long, long) - Static method in class org.apache.spark.streaming.util.RawTextHelper
 
max() - Method in class org.apache.spark.util.StatCounter
 
MAX_FEATURES_FOR_NORMAL_SOLVER() - Static method in class org.apache.spark.ml.regression.LinearRegression
When using LinearRegression.solver == "normal", the solver must limit the number of features to at most this number.
MAX_INT_DIGITS() - Static method in class org.apache.spark.sql.types.Decimal
Maximum number of decimal digits an Int can represent
MAX_LONG_DIGITS() - Static method in class org.apache.spark.sql.types.Decimal
Maximum number of decimal digits a Long can represent
MAX_PRECISION() - Static method in class org.apache.spark.sql.types.DecimalType
 
MAX_RETAINED_DEAD_EXECUTORS() - Static method in class org.apache.spark.status.config
 
MAX_RETAINED_JOBS() - Static method in class org.apache.spark.status.config
 
MAX_RETAINED_ROOT_NODES() - Static method in class org.apache.spark.status.config
 
MAX_RETAINED_STAGES() - Static method in class org.apache.spark.status.config
 
MAX_RETAINED_TASKS_PER_STAGE() - Static method in class org.apache.spark.status.config
 
MAX_SCALE() - Static method in class org.apache.spark.sql.types.DecimalType
 
maxAbs() - Method in class org.apache.spark.ml.feature.MaxAbsScalerModel
 
MaxAbsScaler - Class in org.apache.spark.ml.feature
Rescale each feature individually to range [-1, 1] by dividing through the largest maximum absolute value in each feature.
MaxAbsScaler(String) - Constructor for class org.apache.spark.ml.feature.MaxAbsScaler
 
MaxAbsScaler() - Constructor for class org.apache.spark.ml.feature.MaxAbsScaler
 
MaxAbsScalerModel - Class in org.apache.spark.ml.feature
Model fitted by MaxAbsScaler.
MaxAbsScalerParams - Interface in org.apache.spark.ml.feature
maxBins() - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
Maximum number of bins used for discretizing continuous features and for choosing how to split on features at each node.
maxBins() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
maxBufferSizeMb() - Method in class org.apache.spark.serializer.KryoSerializer
 
maxCategories() - Method in interface org.apache.spark.ml.feature.VectorIndexerParams
Threshold for the number of values a categorical feature can take.
maxCores() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
 
maxDepth() - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
Maximum depth of the tree (nonnegative).
maxDepth() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
maxDF() - Method in interface org.apache.spark.ml.feature.CountVectorizerParams
Specifies the maximum number of different documents a term could appear in to be included in the vocabulary.
maxId() - Static method in class org.apache.spark.mllib.tree.configuration.Algo
 
maxId() - Static method in class org.apache.spark.mllib.tree.configuration.EnsembleCombiningStrategy
 
maxId() - Static method in class org.apache.spark.mllib.tree.configuration.FeatureType
 
maxId() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
 
maxId() - Static method in class org.apache.spark.rdd.CheckpointState
 
maxId() - Static method in class org.apache.spark.rdd.DeterministicLevel
 
maxId() - Static method in class org.apache.spark.scheduler.SchedulingMode
 
maxId() - Static method in class org.apache.spark.scheduler.TaskLocality
 
maxId() - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
 
maxId() - Static method in class org.apache.spark.TaskState
 
maxIter() - Method in interface org.apache.spark.ml.param.shared.HasMaxIter
Param for maximum number of iterations (&gt;= 0).
maxIters() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
 
maxLocalProjDBSize() - Method in class org.apache.spark.ml.fpm.PrefixSpan
Param for the maximum number of items (including delimiters used in the internal storage format) allowed in a projected database before local processing (default: 32000000).
maxMem() - Method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
 
maxMemory() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
maxMemory() - Method in class org.apache.spark.status.LiveExecutor
 
maxMemoryInMB() - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
Maximum memory in MB allocated to histogram aggregation.
maxMemoryInMB() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
maxMessageSizeBytes(SparkConf) - Static method in class org.apache.spark.util.RpcUtils
Returns the configured max message size for messages in bytes.
maxNodesInLevel(int) - Static method in class org.apache.spark.mllib.tree.model.Node
Return the maximum number of nodes which can be in the given level of the tree.
maxNumConcurrentTasks() - Method in interface org.apache.spark.scheduler.SchedulerBackend
Get the max number of tasks that can be concurrent launched currently.
maxOffHeapMem() - Method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
 
maxOffHeapMemSize() - Method in class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager
 
maxOnHeapMem() - Method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
 
maxOnHeapMemSize() - Method in class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager
 
maxPatternLength() - Method in class org.apache.spark.ml.fpm.PrefixSpan
Param for the maximal pattern length (default: 10).
maxPrecisionForBytes(int) - Static method in class org.apache.spark.sql.types.Decimal
 
maxReplicas() - Method in class org.apache.spark.storage.BlockManagerMessages.ReplicateBlock
 
maxSentenceLength() - Method in interface org.apache.spark.ml.feature.Word2VecBase
Sets the maximum length (in words) of each sentence in the input data.
maxSplitFeatureIndex() - Method in interface org.apache.spark.ml.tree.DecisionTreeModel
Trace down the tree, and return the largest feature index used in any split.
maxTasks() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
maxTasks() - Method in class org.apache.spark.status.LiveExecutor
 
maxVal() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
 
maybeUpdateOutputMetrics(OutputMetrics, Function0<Object>, long) - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
 
md5(Column) - Static method in class org.apache.spark.sql.functions
Calculates the MD5 digest of a binary column and returns the value as a 32 character hex string.
mean() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Compute the mean of this RDD's elements.
mean() - Method in class org.apache.spark.ml.feature.StandardScalerModel
 
mean() - Method in class org.apache.spark.ml.stat.distribution.MultivariateGaussian
 
mean(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
mean(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
mean() - Method in class org.apache.spark.mllib.feature.StandardScalerModel
 
mean() - Method in class org.apache.spark.mllib.random.ExponentialGenerator
 
mean() - Method in class org.apache.spark.mllib.random.LogNormalGenerator
 
mean() - Method in class org.apache.spark.mllib.random.PoissonGenerator
 
mean() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
Sample mean of each dimension.
mean() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
Sample mean vector.
mean() - Method in class org.apache.spark.partial.BoundedDouble
 
mean() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
Compute the mean of this RDD's elements.
mean(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the average of the values in a group.
mean(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the average of the values in a group.
mean(String...) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Compute the average value for each numeric columns for each group.
mean(Seq<String>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Compute the average value for each numeric columns for each group.
mean() - Method in class org.apache.spark.util.StatCounter
 
meanAbsoluteError() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
Returns the mean absolute error, which is a risk function corresponding to the expected value of the absolute error loss or l1-norm loss.
meanAbsoluteError() - Method in class org.apache.spark.mllib.evaluation.RegressionMetrics
Returns the mean absolute error, which is a risk function corresponding to the expected value of the absolute error loss or l1-norm loss.
meanApprox(long, Double) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return the approximate mean of the elements in this RDD.
meanApprox(long) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Approximate operation to return the mean within a timeout.
meanApprox(long, double) - Method in class org.apache.spark.rdd.DoubleRDDFunctions
Approximate operation to return the mean within a timeout.
meanAveragePrecision() - Method in class org.apache.spark.mllib.evaluation.RankingMetrics
Returns the mean average precision (MAP) of all the queries.
means() - Method in class org.apache.spark.ml.clustering.ExpectationAggregator
 
means() - Method in class org.apache.spark.mllib.clustering.ExpectationSum
 
meanSquaredError() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
Returns the mean squared error, which is a risk function corresponding to the expected value of the squared error loss or quadratic loss.
meanSquaredError() - Method in class org.apache.spark.mllib.evaluation.RegressionMetrics
Returns the mean squared error, which is a risk function corresponding to the expected value of the squared error loss or quadratic loss.
megabytesToString(long) - Static method in class org.apache.spark.util.Utils
Convert a quantity in megabytes to a human-readable string such as "4.0 MB".
MEM_SPILL() - Static method in class org.apache.spark.status.TaskIndexNames
 
MEMORY_AND_DISK - Static variable in class org.apache.spark.api.java.StorageLevels
 
MEMORY_AND_DISK() - Static method in class org.apache.spark.storage.StorageLevel
 
MEMORY_AND_DISK_2 - Static variable in class org.apache.spark.api.java.StorageLevels
 
MEMORY_AND_DISK_2() - Static method in class org.apache.spark.storage.StorageLevel
 
MEMORY_AND_DISK_SER - Static variable in class org.apache.spark.api.java.StorageLevels
 
MEMORY_AND_DISK_SER() - Static method in class org.apache.spark.storage.StorageLevel
 
MEMORY_AND_DISK_SER_2 - Static variable in class org.apache.spark.api.java.StorageLevels
 
MEMORY_AND_DISK_SER_2() - Static method in class org.apache.spark.storage.StorageLevel
 
MEMORY_BYTES_SPILLED() - Static method in class org.apache.spark.InternalAccumulator
 
MEMORY_ONLY - Static variable in class org.apache.spark.api.java.StorageLevels
 
MEMORY_ONLY() - Static method in class org.apache.spark.storage.StorageLevel
 
MEMORY_ONLY_2 - Static variable in class org.apache.spark.api.java.StorageLevels
 
MEMORY_ONLY_2() - Static method in class org.apache.spark.storage.StorageLevel
 
MEMORY_ONLY_SER - Static variable in class org.apache.spark.api.java.StorageLevels
 
MEMORY_ONLY_SER() - Static method in class org.apache.spark.storage.StorageLevel
 
MEMORY_ONLY_SER_2 - Static variable in class org.apache.spark.api.java.StorageLevels
 
MEMORY_ONLY_SER_2() - Static method in class org.apache.spark.storage.StorageLevel
 
memoryBytesSpilled() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
memoryBytesSpilled() - Method in class org.apache.spark.status.api.v1.StageData
 
memoryBytesSpilled() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
memoryBytesSpilled() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 
memoryCost(int, int) - Static method in class org.apache.spark.mllib.feature.PCAUtil
 
MemoryEntry<T> - Interface in org.apache.spark.storage.memory
 
MemoryEntryBuilder<T> - Interface in org.apache.spark.storage.memory
 
memoryManager() - Method in class org.apache.spark.SparkEnv
 
memoryMetrics() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
MemoryMetrics - Class in org.apache.spark.status.api.v1
 
memoryMode() - Method in class org.apache.spark.storage.memory.DeserializedMemoryEntry
 
memoryMode() - Method in interface org.apache.spark.storage.memory.MemoryEntry
 
memoryMode() - Method in class org.apache.spark.storage.memory.SerializedMemoryEntry
 
MemoryParam - Class in org.apache.spark.util
An extractor object for parsing JVM memory strings, such as "10g", into an Int representing the number of megabytes.
MemoryParam() - Constructor for class org.apache.spark.util.MemoryParam
 
memoryPerExecutorMB() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
 
memoryRemaining() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
 
memoryStringToMb(String) - Static method in class org.apache.spark.util.Utils
Convert a Java memory parameter passed to -Xmx (such as 300m or 1g) to a number of mebibytes.
memoryUsed() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
memoryUsed() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
 
memoryUsed() - Method in class org.apache.spark.status.api.v1.RDDPartitionInfo
 
memoryUsed() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
 
memoryUsed() - Method in class org.apache.spark.status.LiveExecutor
 
memoryUsed() - Method in class org.apache.spark.status.LiveRDD
 
memoryUsed() - Method in class org.apache.spark.status.LiveRDDDistribution
 
memoryUsed() - Method in class org.apache.spark.status.LiveRDDPartition
 
memoryUsedBytes() - Method in class org.apache.spark.sql.streaming.StateOperatorProgress
 
memSize() - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
 
memSize() - Method in class org.apache.spark.storage.BlockStatus
 
memSize() - Method in class org.apache.spark.storage.BlockUpdatedInfo
 
memSize() - Method in class org.apache.spark.storage.RDDInfo
 
merge(R) - Method in class org.apache.spark.Accumulable
Deprecated.
Merge two accumulable objects together
merge(ExpectationAggregator) - Method in class org.apache.spark.ml.clustering.ExpectationAggregator
Merge another ExpectationAggregator, update the weights, means and covariances for each distributions, and update the log likelihood.
merge(Agg) - Method in interface org.apache.spark.ml.optim.aggregator.DifferentiableLossAggregator
Merge two aggregators.
merge(AFTAggregator) - Method in class org.apache.spark.ml.regression.AFTAggregator
Merge another AFTAggregator, and update the loss and gradient of the objective function.
merge(IDF.DocumentFrequencyAggregator) - Method in class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
Merges another.
merge(MultivariateOnlineSummarizer) - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
Merge another MultivariateOnlineSummarizer, and update the statistical summary.
merge(int, U) - Method in interface org.apache.spark.partial.ApproximateEvaluator
 
merge(BUF, BUF) - Method in class org.apache.spark.sql.expressions.Aggregator
Merge two intermediate values.
merge(MutableAggregationBuffer, Row) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
Merges two aggregation buffers and stores the updated buffer values back to buffer1.
merge(AccumulatorV2<IN, OUT>) - Method in class org.apache.spark.util.AccumulatorV2
Merges another same-type accumulator into this one and update its state, i.e.
merge(AccumulatorV2<T, List<T>>) - Method in class org.apache.spark.util.CollectionAccumulator
 
merge(AccumulatorV2<Double, Double>) - Method in class org.apache.spark.util.DoubleAccumulator
 
merge(AccumulatorV2<T, R>) - Method in class org.apache.spark.util.LegacyAccumulatorWrapper
 
merge(AccumulatorV2<Long, Long>) - Method in class org.apache.spark.util.LongAccumulator
 
merge(double) - Method in class org.apache.spark.util.StatCounter
Add a value into this StatCounter, updating the internal statistics.
merge(TraversableOnce<Object>) - Method in class org.apache.spark.util.StatCounter
Add multiple values into this StatCounter, updating the internal statistics.
merge(StatCounter) - Method in class org.apache.spark.util.StatCounter
Merge another StatCounter into this one, adding up the internal statistics.
mergeCombiners() - Method in class org.apache.spark.Aggregator
 
mergeInPlace(BloomFilter) - Method in class org.apache.spark.util.sketch.BloomFilter
Combines this bloom filter with another bloom filter by performing a bitwise OR of the underlying data.
mergeInPlace(CountMinSketch) - Method in class org.apache.spark.util.sketch.CountMinSketch
Merges another CountMinSketch with this one in place.
mergeOffsets(PartitionOffset[]) - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.ContinuousReader
Merge partitioned offsets coming from ContinuousInputPartitionReader instances for each partition to a single global offset.
mergeValue() - Method in class org.apache.spark.Aggregator
 
message() - Method in class org.apache.spark.FetchFailed
 
message() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutorFailed
 
message() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveWorker
 
message() - Static method in class org.apache.spark.scheduler.ExecutorKilled
 
message() - Static method in class org.apache.spark.scheduler.LossReasonPending
 
message() - Method in exception org.apache.spark.sql.AnalysisException
 
message() - Method in exception org.apache.spark.sql.streaming.StreamingQueryException
 
message() - Method in class org.apache.spark.sql.streaming.StreamingQueryStatus
 
MetaAlgorithmReadWrite - Class in org.apache.spark.ml.util
Default Meta-Algorithm read and write implementation.
MetaAlgorithmReadWrite() - Constructor for class org.apache.spark.ml.util.MetaAlgorithmReadWrite
 
Metadata - Class in org.apache.spark.sql.types
Metadata is a wrapper over Map[String, Any] that limits the value type to simple ones: Boolean, Long, Double, String, Metadata, Array[Boolean], Array[Long], Array[Double], Array[String], and Array[Metadata].
metadata() - Method in class org.apache.spark.sql.types.StructField
 
metadata() - Method in class org.apache.spark.streaming.scheduler.StreamInputInfo
 
METADATA_KEY_DESCRIPTION() - Static method in class org.apache.spark.streaming.scheduler.StreamInputInfo
The key for description in StreamInputInfo.metadata.
MetadataBuilder - Class in org.apache.spark.sql.types
Builder for Metadata.
MetadataBuilder() - Constructor for class org.apache.spark.sql.types.MetadataBuilder
 
metadataDescription() - Method in class org.apache.spark.streaming.scheduler.StreamInputInfo
 
MetadataUtils - Class in org.apache.spark.ml.util
Helper utilities for algorithms using ML metadata
MetadataUtils() - Constructor for class org.apache.spark.ml.util.MetadataUtils
 
Method(String, Function2<Object, Object, Object>) - Constructor for class org.apache.spark.mllib.stat.test.ChiSqTest.Method
 
method() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
 
Method$() - Constructor for class org.apache.spark.mllib.stat.test.ChiSqTest.Method$
 
MethodIdentifier<T> - Class in org.apache.spark.util
Helper class to identify a method.
MethodIdentifier(Class<T>, String, String) - Constructor for class org.apache.spark.util.MethodIdentifier
 
methodName() - Method in interface org.apache.spark.mllib.stat.test.StreamingTestMethod
 
methodName() - Static method in class org.apache.spark.mllib.stat.test.StudentTTest
 
methodName() - Static method in class org.apache.spark.mllib.stat.test.WelchTTest
 
METRIC_COMPILATION_TIME() - Static method in class org.apache.spark.metrics.source.CodegenMetrics
Histogram of the time it took to compile source code text (in milliseconds).
METRIC_FILE_CACHE_HITS() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
Tracks the total number of files served from the file status cache instead of discovered.
METRIC_FILES_DISCOVERED() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
Tracks the total number of files discovered off of the filesystem by InMemoryFileIndex.
METRIC_GENERATED_CLASS_BYTECODE_SIZE() - Static method in class org.apache.spark.metrics.source.CodegenMetrics
Histogram of the bytecode size of each class generated by CodeGenerator.
METRIC_GENERATED_METHOD_BYTECODE_SIZE() - Static method in class org.apache.spark.metrics.source.CodegenMetrics
Histogram of the bytecode size of each method in classes generated by CodeGenerator.
METRIC_HIVE_CLIENT_CALLS() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
Tracks the total number of Hive client calls (e.g.
METRIC_PARALLEL_LISTING_JOB_COUNT() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
Tracks the total number of Spark jobs launched for parallel file listing.
METRIC_PARTITIONS_FETCHED() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
Tracks the total number of partition metadata entries fetched via the client api.
METRIC_SOURCE_CODE_SIZE() - Static method in class org.apache.spark.metrics.source.CodegenMetrics
Histogram of the length of source code text compiled by CodeGenerator (in characters).
metricName() - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
param for metric name in evaluation (supports "areaUnderROC" (default), "areaUnderPR")
metricName() - Method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
param for metric name in evaluation (supports "silhouette" (default))
metricName() - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
param for metric name in evaluation (supports "f1" (default), "weightedPrecision", "weightedRecall", "accuracy")
metricName() - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
Param for metric name in evaluation.
metricRegistry() - Static method in class org.apache.spark.metrics.source.CodegenMetrics
 
metricRegistry() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
 
metricRegistry() - Method in interface org.apache.spark.metrics.source.Source
 
metrics(String...) - Static method in class org.apache.spark.ml.stat.Summarizer
Given a list of metrics, provides a builder that it turns computes metrics from a column.
metrics(Seq<String>) - Static method in class org.apache.spark.ml.stat.Summarizer
Given a list of metrics, provides a builder that it turns computes metrics from a column.
metrics() - Method in class org.apache.spark.status.LiveExecutorStageSummary
 
metrics() - Method in class org.apache.spark.status.LiveStage
 
METRICS_PREFIX() - Static method in class org.apache.spark.InternalAccumulator
 
metricsSystem() - Method in class org.apache.spark.SparkEnv
 
MFDataGenerator - Class in org.apache.spark.mllib.util
:: DeveloperApi :: Generate RDD(s) containing data for Matrix Factorization.
MFDataGenerator() - Constructor for class org.apache.spark.mllib.util.MFDataGenerator
 
MicroBatchReader - Interface in org.apache.spark.sql.sources.v2.reader.streaming
A mix-in interface for DataSourceReader.
MicroBatchReadSupport - Interface in org.apache.spark.sql.sources.v2
A mix-in interface for DataSourceV2.
microF1Measure() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
Returns micro-averaged label-based f1-measure (equals to micro-averaged document-based f1-measure)
microPrecision() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
Returns micro-averaged label-based precision (equals to micro-averaged document-based precision)
microRecall() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
Returns micro-averaged label-based recall (equals to micro-averaged document-based recall)
mightContain(Object) - Method in class org.apache.spark.util.sketch.BloomFilter
Returns true if the element might have been put in this Bloom filter, false if this is definitely not the case.
mightContainBinary(byte[]) - Method in class org.apache.spark.util.sketch.BloomFilter
A specialized variant of BloomFilter.mightContain(Object) that only tests byte array items.
mightContainLong(long) - Method in class org.apache.spark.util.sketch.BloomFilter
A specialized variant of BloomFilter.mightContain(Object) that only tests long items.
mightContainString(String) - Method in class org.apache.spark.util.sketch.BloomFilter
A specialized variant of BloomFilter.mightContain(Object) that only tests String items.
milliseconds() - Method in class org.apache.spark.streaming.Duration
 
milliseconds(long) - Static method in class org.apache.spark.streaming.Durations
 
Milliseconds - Class in org.apache.spark.streaming
Helper object that creates instance of Duration representing a given number of milliseconds.
Milliseconds() - Constructor for class org.apache.spark.streaming.Milliseconds
 
milliseconds() - Method in class org.apache.spark.streaming.Time
 
millisToString(long) - Static method in class org.apache.spark.scheduler.StatsReportListener
Reformat a time interval in milliseconds to a prettier format for output
min() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Returns the minimum element from this RDD as defined by the default comparator natural order.
min(Comparator<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Returns the minimum element from this RDD as defined by the specified Comparator[T].
MIN() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
 
min() - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
min() - Method in interface org.apache.spark.ml.feature.MinMaxScalerParams
lower bound after transformation, shared by all features Default: 0.0
min(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
min(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
min() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
Minimum value of each dimension.
min() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
Minimum value of each column.
min(Ordering<T>) - Method in class org.apache.spark.rdd.RDD
Returns the min of this RDD as defined by the implicit Ordering[T].
min(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the minimum value of the expression in a group.
min(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the minimum value of the column in a group.
min(String...) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Compute the min value for each numeric column for each group.
min(Seq<String>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Compute the min value for each numeric column for each group.
min(Duration) - Method in class org.apache.spark.streaming.Duration
 
min(Time) - Method in class org.apache.spark.streaming.Time
 
min() - Method in class org.apache.spark.util.StatCounter
 
minBytesForPrecision() - Static method in class org.apache.spark.sql.types.Decimal
 
minConfidence() - Method in interface org.apache.spark.ml.fpm.FPGrowthParams
Minimal confidence for generating Association Rule.
minCount() - Method in interface org.apache.spark.ml.feature.Word2VecBase
The minimum number of times a token must appear to be included in the word2vec model's vocabulary.
minDF() - Method in interface org.apache.spark.ml.feature.CountVectorizerParams
Specifies the minimum number of different documents a term must appear in to be included in the vocabulary.
minDivisibleClusterSize() - Method in interface org.apache.spark.ml.clustering.BisectingKMeansParams
The minimum number of points (if greater than or equal to 1.0) or the minimum proportion of points (if less than 1.0) of a divisible cluster (default: 1.0).
minDocFreq() - Method in interface org.apache.spark.ml.feature.IDFBase
The minimum number of documents in which a term should appear.
minDocFreq() - Method in class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
 
minDocFreq() - Method in class org.apache.spark.mllib.feature.IDF
 
MinHashLSH - Class in org.apache.spark.ml.feature
:: Experimental ::
MinHashLSH(String) - Constructor for class org.apache.spark.ml.feature.MinHashLSH
 
MinHashLSH() - Constructor for class org.apache.spark.ml.feature.MinHashLSH
 
MinHashLSHModel - Class in org.apache.spark.ml.feature
:: Experimental ::
MINIMUM_ADJUSTED_SCALE() - Static method in class org.apache.spark.sql.types.DecimalType
 
minInfoGain() - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
Minimum information gain for a split to be considered at a tree node.
minInfoGain() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
minInstancesPerNode() - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
Minimum number of instances each child must have after split.
minInstancesPerNode() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
MinMax() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
 
MinMaxScaler - Class in org.apache.spark.ml.feature
Rescale each feature individually to a common range [min, max] linearly using column summary statistics, which is also known as min-max normalization or Rescaling.
MinMaxScaler(String) - Constructor for class org.apache.spark.ml.feature.MinMaxScaler
 
MinMaxScaler() - Constructor for class org.apache.spark.ml.feature.MinMaxScaler
 
MinMaxScalerModel - Class in org.apache.spark.ml.feature
Model fitted by MinMaxScaler.
MinMaxScalerParams - Interface in org.apache.spark.ml.feature
minorVersion(String) - Static method in class org.apache.spark.util.VersionUtils
Given a Spark version string, return the minor version number.
minSamplingRate() - Static method in class org.apache.spark.util.random.BinomialBounds
 
minShare() - Method in interface org.apache.spark.scheduler.Schedulable
 
minSupport() - Method in interface org.apache.spark.ml.fpm.FPGrowthParams
Minimal support level of the frequent pattern.
minSupport() - Method in class org.apache.spark.ml.fpm.PrefixSpan
Param for the minimal support level (default: 0.1).
minTF() - Method in interface org.apache.spark.ml.feature.CountVectorizerParams
Filter to ignore rare words in a document.
minTokenLength() - Method in class org.apache.spark.ml.feature.RegexTokenizer
Minimum token length, greater than or equal to 0.
minus(RDD<Tuple2<Object, VD>>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
minus(VertexRDD<VD>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
minus(RDD<Tuple2<Object, VD>>) - Method in class org.apache.spark.graphx.VertexRDD
For each VertexId present in both this and other, minus will act as a set difference operation returning only those unique VertexId's present in this.
minus(VertexRDD<VD>) - Method in class org.apache.spark.graphx.VertexRDD
For each VertexId present in both this and other, minus will act as a set difference operation returning only those unique VertexId's present in this.
minus(Object) - Method in class org.apache.spark.sql.Column
Subtraction.
minus(Decimal, Decimal) - Method in interface org.apache.spark.sql.types.Decimal.DecimalIsConflicted
 
minus(Duration) - Method in class org.apache.spark.streaming.Duration
 
minus(Time) - Method in class org.apache.spark.streaming.Time
 
minus(Duration) - Method in class org.apache.spark.streaming.Time
 
minute(Column) - Static method in class org.apache.spark.sql.functions
Extracts the minutes as an integer from a given date/timestamp/string.
minutes() - Static method in class org.apache.spark.scheduler.StatsReportListener
 
minutes(long) - Static method in class org.apache.spark.streaming.Durations
 
Minutes - Class in org.apache.spark.streaming
Helper object that creates instance of Duration representing a given number of minutes.
Minutes() - Constructor for class org.apache.spark.streaming.Minutes
 
minVal() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
 
missingValue() - Method in interface org.apache.spark.ml.feature.ImputerParams
The placeholder for the missing values.
mkList() - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
mkString() - Method in interface org.apache.spark.sql.Row
Displays all elements of this sequence in a string (without a separator).
mkString(String) - Method in interface org.apache.spark.sql.Row
Displays all elements of this sequence in a string using a separator string.
mkString(String, String, String) - Method in interface org.apache.spark.sql.Row
Displays all elements of this traversable or iterator in a string using start, end, and separator strings.
mkString(String, String, String) - Method in class org.apache.spark.status.api.v1.StackTrace
 
ML_ATTR() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
 
mlDenseMatrixToMLlibDenseMatrix(DenseMatrix) - Static method in class org.apache.spark.mllib.linalg.MatrixImplicits
 
mlDenseVectorToMLlibDenseVector(DenseVector) - Static method in class org.apache.spark.mllib.linalg.VectorImplicits
 
MLFormatRegister - Interface in org.apache.spark.ml.util
ML export formats for should implement this trait so that users can specify a shortname rather than the fully qualified class name of the exporter.
mllibDenseMatrixToMLDenseMatrix(DenseMatrix) - Static method in class org.apache.spark.mllib.linalg.MatrixImplicits
 
mllibDenseVectorToMLDenseVector(DenseVector) - Static method in class org.apache.spark.mllib.linalg.VectorImplicits
 
mllibMatrixToMLMatrix(Matrix) - Static method in class org.apache.spark.mllib.linalg.MatrixImplicits
 
mllibSparseMatrixToMLSparseMatrix(SparseMatrix) - Static method in class org.apache.spark.mllib.linalg.MatrixImplicits
 
mllibSparseVectorToMLSparseVector(SparseVector) - Static method in class org.apache.spark.mllib.linalg.VectorImplicits
 
mllibVectorToMLVector(Vector) - Static method in class org.apache.spark.mllib.linalg.VectorImplicits
 
mlMatrixToMLlibMatrix(Matrix) - Static method in class org.apache.spark.mllib.linalg.MatrixImplicits
 
MLPairRDDFunctions<K,V> - Class in org.apache.spark.mllib.rdd
:: DeveloperApi :: Machine learning specific Pair RDD functions.
MLPairRDDFunctions(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Constructor for class org.apache.spark.mllib.rdd.MLPairRDDFunctions
 
MLReadable<T> - Interface in org.apache.spark.ml.util
Trait for objects that provide MLReader.
MLReader<T> - Class in org.apache.spark.ml.util
Abstract class for utility classes that can load ML instances.
MLReader() - Constructor for class org.apache.spark.ml.util.MLReader
 
mlSparseMatrixToMLlibSparseMatrix(SparseMatrix) - Static method in class org.apache.spark.mllib.linalg.MatrixImplicits
 
mlSparseVectorToMLlibSparseVector(SparseVector) - Static method in class org.apache.spark.mllib.linalg.VectorImplicits
 
MLUtils - Class in org.apache.spark.mllib.util
Helper methods to load, save and pre-process data used in MLLib.
MLUtils() - Constructor for class org.apache.spark.mllib.util.MLUtils
 
mlVectorToMLlibVector(Vector) - Static method in class org.apache.spark.mllib.linalg.VectorImplicits
 
MLWritable - Interface in org.apache.spark.ml.util
Trait for classes that provide MLWriter.
MLWriter - Class in org.apache.spark.ml.util
Abstract class for utility classes that can save ML instances in Spark's internal format.
MLWriter() - Constructor for class org.apache.spark.ml.util.MLWriter
 
MLWriterFormat - Interface in org.apache.spark.ml.util
Abstract class to be implemented by objects that provide ML exportability.
mod(Object) - Method in class org.apache.spark.sql.Column
Modulo (a.k.a.
mode(SaveMode) - Method in class org.apache.spark.sql.DataFrameWriter
Specifies the behavior when data or table already exists.
mode(String) - Method in class org.apache.spark.sql.DataFrameWriter
Specifies the behavior when data or table already exists.
mode() - Method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
 
model(Vector) - Method in interface org.apache.spark.ml.ann.Topology
 
model(long) - Method in interface org.apache.spark.ml.ann.Topology
 
Model<M extends Model<M>> - Class in org.apache.spark.ml
:: DeveloperApi :: A fitted model, i.e., a Transformer produced by an Estimator.
Model() - Constructor for class org.apache.spark.ml.Model
 
models() - Method in class org.apache.spark.ml.classification.OneVsRestModel
 
modelType() - Method in interface org.apache.spark.ml.classification.NaiveBayesParams
The model type which is a string (case-sensitive).
modelType() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
 
modelType() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data
 
MODULE$ - Static variable in class org.apache.spark.AccumulatorParam.DoubleAccumulatorParam$
Deprecated.
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.AccumulatorParam.FloatAccumulatorParam$
Deprecated.
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.AccumulatorParam.IntAccumulatorParam$
Deprecated.
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.AccumulatorParam.LongAccumulatorParam$
Deprecated.
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.AccumulatorParam.StringAccumulatorParam$
Deprecated.
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.graphx.PartitionStrategy.CanonicalRandomVertexCut$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.graphx.PartitionStrategy.EdgePartition1D$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.graphx.PartitionStrategy.EdgePartition2D$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.graphx.PartitionStrategy.RandomVertexCut$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.internal.io.FileCommitProtocol.EmptyTaskCommitMessage$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.InternalAccumulator.input$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.InternalAccumulator.output$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.InternalAccumulator.shuffleRead$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.InternalAccumulator.shuffleWrite$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette.ClusterStats$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.feature.Word2VecModel.Word2VecModelWriter$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.Pipeline.SharedReadWrite$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.recommendation.ALS.InBlock$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.recommendation.ALS.Rating$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.recommendation.ALS.RatingBlock$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.CLogLog$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Family$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.FamilyAndLink$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Identity$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Inverse$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Link$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Log$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Logit$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Probit$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Sqrt$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Tweedie$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ml.tree.EnsembleModelReadWrite.EnsembleNodeData$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$.Data$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$.Data$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.clustering.BisectingKMeansModel.SaveLoadV1_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.clustering.BisectingKMeansModel.SaveLoadV2_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.clustering.KMeansModel.SaveLoadV1_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.clustering.KMeansModel.SaveLoadV2_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.clustering.PowerIterationClustering.Assignment$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel.SaveLoadV1_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$.Data$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.fpm.FPGrowthModel.SaveLoadV1_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.fpm.PrefixSpan.Postfix$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.fpm.PrefixSpan.Prefix$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.fpm.PrefixSpanModel.SaveLoadV1_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel.SaveLoadV1_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$.Data$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.stat.test.ChiSqTest.Method$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.stat.test.ChiSqTest.NullHypothesis$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTest.NullHypothesis$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.rdd.HadoopRDD.HadoopMapPartitionsWithSplitRDD$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.rdd.NewHadoopRDD.NewHadoopMapPartitionsWithSplitRDD$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.GetExecutorLossReason$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillExecutors$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillExecutorsOnHost$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.LaunchTask$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterClusterManager$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisteredExecutor$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutorFailed$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveWorker$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RetrieveLastAllocatedExecutorId$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RetrieveSparkAppConfig$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.ReviveOffers$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SetupDriver$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.Shutdown$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SparkAppConfig$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopDriver$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopExecutor$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopExecutors$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.UpdateDelegationTokens$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.sql.hive.HiveShim.HiveFunctionWrapper$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.sql.hive.HiveStrategies.HiveTableScans$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.sql.hive.HiveStrategies.Scripts$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.sql.RelationalGroupedDataset.CubeType$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.sql.RelationalGroupedDataset.GroupByType$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.sql.RelationalGroupedDataset.PivotType$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.sql.RelationalGroupedDataset.RollupType$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.sql.types.Decimal.DecimalAsIfIntegral$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.sql.types.Decimal.DecimalIsFractional$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.sql.types.DecimalType.Expression$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.sql.types.DecimalType.Fixed$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.BlockLocationsAndStatus$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.BlockManagerHeartbeat$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetBlockStatus$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetExecutorEndpointRef$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetLocations$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetLocationsAndStatus$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetLocationsMultipleBlockIds$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetMatchingBlockIds$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetMemoryStatus$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetPeers$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetStorageStatus$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.HasCachedBlocks$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveBlock$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveBroadcast$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveExecutor$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveRdd$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveShuffle$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.ReplicateBlock$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.StopBlockManagerMaster$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.TriggerThreadDump$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo$
Static reference to the singleton instance of this Scala object.
MODULE$ - Static variable in class org.apache.spark.ui.JettyUtils.ServletParams$
Static reference to the singleton instance of this Scala object.
monotonically_increasing_id() - Static method in class org.apache.spark.sql.functions
A column expression that generates monotonically increasing 64-bit integers.
monotonicallyIncreasingId() - Static method in class org.apache.spark.sql.functions
Deprecated.
Use monotonically_increasing_id(). Since 2.0.0.
month(Column) - Static method in class org.apache.spark.sql.functions
Extracts the month as an integer from a given date/timestamp/string.
months_between(Column, Column) - Static method in class org.apache.spark.sql.functions
Returns number of months between dates start and end.
months_between(Column, Column, boolean) - Static method in class org.apache.spark.sql.functions
Returns number of months between dates end and start.
msDurationToString(long) - Static method in class org.apache.spark.util.Utils
Returns a human-readable string representing a duration such as "35ms"
MsSqlServerDialect - Class in org.apache.spark.sql.jdbc
 
MsSqlServerDialect() - Constructor for class org.apache.spark.sql.jdbc.MsSqlServerDialect
 
mu() - Method in class org.apache.spark.mllib.stat.distribution.MultivariateGaussian
 
MulticlassClassificationEvaluator - Class in org.apache.spark.ml.evaluation
:: Experimental :: Evaluator for multiclass classification, which expects two input columns: prediction and label.
MulticlassClassificationEvaluator(String) - Constructor for class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
 
MulticlassClassificationEvaluator() - Constructor for class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
 
multiclassMetrics() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
 
MulticlassMetrics - Class in org.apache.spark.mllib.evaluation
Evaluator for multiclass classification.
MulticlassMetrics(RDD<Tuple2<Object, Object>>) - Constructor for class org.apache.spark.mllib.evaluation.MulticlassMetrics
 
MultilabelMetrics - Class in org.apache.spark.mllib.evaluation
Evaluator for multilabel classification.
MultilabelMetrics(RDD<Tuple2<double[], double[]>>) - Constructor for class org.apache.spark.mllib.evaluation.MultilabelMetrics
 
multiLabelValidator(int) - Static method in class org.apache.spark.mllib.util.DataValidators
Function to check if labels used for k class multi-label classification are in the range of {0, 1, ..., k - 1}.
MultilayerPerceptronClassificationModel - Class in org.apache.spark.ml.classification
Classification model based on the Multilayer Perceptron.
MultilayerPerceptronClassifier - Class in org.apache.spark.ml.classification
Classifier trainer based on the Multilayer Perceptron.
MultilayerPerceptronClassifier(String) - Constructor for class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
 
MultilayerPerceptronClassifier() - Constructor for class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
 
MultilayerPerceptronParams - Interface in org.apache.spark.ml.classification
Params for Multilayer Perceptron.
multiply(DenseMatrix) - Method in interface org.apache.spark.ml.linalg.Matrix
Convenience method for Matrix-DenseMatrix multiplication.
multiply(DenseVector) - Method in interface org.apache.spark.ml.linalg.Matrix
Convenience method for Matrix-DenseVector multiplication.
multiply(Vector) - Method in interface org.apache.spark.ml.linalg.Matrix
Convenience method for Matrix-Vector multiplication.
multiply(BlockMatrix) - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
Left multiplies this BlockMatrix to other, another BlockMatrix.
multiply(BlockMatrix, int) - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
Left multiplies this BlockMatrix to other, another BlockMatrix.
multiply(Matrix) - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
Multiply this matrix by a local matrix on the right.
multiply(Matrix) - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
Multiply this matrix by a local matrix on the right.
multiply(DenseMatrix) - Method in interface org.apache.spark.mllib.linalg.Matrix
Convenience method for Matrix-DenseMatrix multiplication.
multiply(DenseVector) - Method in interface org.apache.spark.mllib.linalg.Matrix
Convenience method for Matrix-DenseVector multiplication.
multiply(Vector) - Method in interface org.apache.spark.mllib.linalg.Matrix
Convenience method for Matrix-Vector multiplication.
multiply(Object) - Method in class org.apache.spark.sql.Column
Multiplication of this expression and another expression.
MultivariateGaussian - Class in org.apache.spark.ml.stat.distribution
This class provides basic functionality for a Multivariate Gaussian (Normal) Distribution.
MultivariateGaussian(Vector, Matrix) - Constructor for class org.apache.spark.ml.stat.distribution.MultivariateGaussian
 
MultivariateGaussian - Class in org.apache.spark.mllib.stat.distribution
:: DeveloperApi :: This class provides basic functionality for a Multivariate Gaussian (Normal) Distribution.
MultivariateGaussian(Vector, Matrix) - Constructor for class org.apache.spark.mllib.stat.distribution.MultivariateGaussian
 
MultivariateOnlineSummarizer - Class in org.apache.spark.mllib.stat
:: DeveloperApi :: MultivariateOnlineSummarizer implements MultivariateStatisticalSummary to compute the mean, variance, minimum, maximum, counts, and nonzero counts for instances in sparse or dense vector format in an online fashion.
MultivariateOnlineSummarizer() - Constructor for class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
 
MultivariateStatisticalSummary - Interface in org.apache.spark.mllib.stat
Trait for multivariate statistical summary of a data matrix.
MutableAggregationBuffer - Class in org.apache.spark.sql.expressions
A Row representing a mutable aggregation buffer.
MutableAggregationBuffer() - Constructor for class org.apache.spark.sql.expressions.MutableAggregationBuffer
 
MutablePair<T1,T2> - Class in org.apache.spark.util
:: DeveloperApi :: A tuple of 2 elements.
MutablePair(T1, T2) - Constructor for class org.apache.spark.util.MutablePair
 
MutablePair() - Constructor for class org.apache.spark.util.MutablePair
No-arg constructor for serialization
MutableURLClassLoader - Class in org.apache.spark.util
URL class loader that exposes the `addURL` method in URLClassLoader.
MutableURLClassLoader(URL[], ClassLoader) - Constructor for class org.apache.spark.util.MutableURLClassLoader
 
myName() - Method in class org.apache.spark.util.InnerClosureFinder
 
MySQLDialect - Class in org.apache.spark.sql.jdbc
 
MySQLDialect() - Constructor for class org.apache.spark.sql.jdbc.MySQLDialect
 

N

n() - Method in class org.apache.spark.ml.feature.NGram
Minimum n-gram length, greater than or equal to 1.
n() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
 
na() - Method in class org.apache.spark.sql.Dataset
Returns a DataFrameNaFunctions for working with missing data.
NaiveBayes - Class in org.apache.spark.ml.classification
Naive Bayes Classifiers.
NaiveBayes(String) - Constructor for class org.apache.spark.ml.classification.NaiveBayes
 
NaiveBayes() - Constructor for class org.apache.spark.ml.classification.NaiveBayes
 
NaiveBayes - Class in org.apache.spark.mllib.classification
Trains a Naive Bayes model given an RDD of (label, features) pairs.
NaiveBayes(double) - Constructor for class org.apache.spark.mllib.classification.NaiveBayes
 
NaiveBayes() - Constructor for class org.apache.spark.mllib.classification.NaiveBayes
 
NaiveBayesModel - Class in org.apache.spark.ml.classification
Model produced by NaiveBayes param: pi log of class priors, whose dimension is C (number of classes) param: theta log of class conditional probabilities, whose dimension is C (number of classes) by D (number of features)
NaiveBayesModel - Class in org.apache.spark.mllib.classification
Model for Naive Bayes Classifiers.
NaiveBayesModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.classification
 
NaiveBayesModel.SaveLoadV1_0$.Data - Class in org.apache.spark.mllib.classification
Model data for model import/export
NaiveBayesModel.SaveLoadV1_0$.Data$ - Class in org.apache.spark.mllib.classification
 
NaiveBayesModel.SaveLoadV2_0$ - Class in org.apache.spark.mllib.classification
 
NaiveBayesModel.SaveLoadV2_0$.Data - Class in org.apache.spark.mllib.classification
Model data for model import/export
NaiveBayesModel.SaveLoadV2_0$.Data$ - Class in org.apache.spark.mllib.classification
 
NaiveBayesParams - Interface in org.apache.spark.ml.classification
Params for Naive Bayes Classifiers.
name() - Method in class org.apache.spark.Accumulable
Deprecated.
 
name() - Method in interface org.apache.spark.api.java.JavaRDDLike
 
name() - Method in class org.apache.spark.ml.attribute.Attribute
Name of the attribute.
name() - Method in class org.apache.spark.ml.attribute.AttributeGroup
 
NAME() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
 
name() - Method in class org.apache.spark.ml.attribute.AttributeType
 
name() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
 
name() - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
name() - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
name() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
name() - Method in class org.apache.spark.ml.param.Param
 
name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
 
name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
 
name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Identity$
 
name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Inverse$
 
name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Log$
 
name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
 
name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Sqrt$
 
name() - Method in class org.apache.spark.mllib.stat.test.ChiSqTest.Method
 
name() - Method in class org.apache.spark.rdd.RDD
A friendly name for this RDD
name() - Method in class org.apache.spark.scheduler.AccumulableInfo
 
name() - Method in class org.apache.spark.scheduler.AsyncEventQueue
 
name() - Method in interface org.apache.spark.scheduler.Schedulable
 
name() - Method in class org.apache.spark.scheduler.StageInfo
 
name() - Method in interface org.apache.spark.SparkStageInfo
 
name() - Method in class org.apache.spark.SparkStageInfoImpl
 
name() - Method in class org.apache.spark.sql.catalog.Column
 
name() - Method in class org.apache.spark.sql.catalog.Database
 
name() - Method in class org.apache.spark.sql.catalog.Function
 
name() - Method in class org.apache.spark.sql.catalog.Table
 
name(String) - Method in class org.apache.spark.sql.Column
Gives the column a name (alias).
name() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Returns the user-specified name of the query, or null if not specified.
name() - Method in class org.apache.spark.sql.streaming.StreamingQueryListener.QueryStartedEvent
 
name() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
 
name(String) - Method in class org.apache.spark.sql.TypedColumn
Gives the TypedColumn a name (alias).
name() - Method in class org.apache.spark.sql.types.StructField
 
name() - Method in class org.apache.spark.status.api.v1.AccumulableInfo
 
name() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
 
name() - Method in class org.apache.spark.status.api.v1.JobData
 
name() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
 
name() - Method in class org.apache.spark.status.api.v1.StageData
 
name() - Method in class org.apache.spark.status.api.v1.streaming.OutputOperationInfo
 
name() - Method in class org.apache.spark.storage.BlockId
A globally unique identifier for this Block.
name() - Method in class org.apache.spark.storage.BroadcastBlockId
 
name() - Method in class org.apache.spark.storage.RDDBlockId
 
name() - Method in class org.apache.spark.storage.RDDInfo
 
name() - Method in class org.apache.spark.storage.ShuffleBlockId
 
name() - Method in class org.apache.spark.storage.ShuffleDataBlockId
 
name() - Method in class org.apache.spark.storage.ShuffleIndexBlockId
 
name() - Method in class org.apache.spark.storage.StreamBlockId
 
name() - Method in class org.apache.spark.storage.TaskResultBlockId
 
name() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
 
name() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
 
name() - Method in class org.apache.spark.util.AccumulatorV2
Returns the name of this accumulator, can only be called after registration.
name() - Method in class org.apache.spark.util.MethodIdentifier
 
namedThreadFactory(String) - Static method in class org.apache.spark.util.ThreadUtils
Create a thread factory that names threads with a prefix and also sets the threads to daemon.
names() - Method in class org.apache.spark.ml.feature.VectorSlicer
An array of feature names to select features from a vector column.
names() - Method in class org.apache.spark.sql.types.StructType
Returns all field names in an array.
nameToObjectMap() - Static method in class org.apache.spark.mllib.stat.correlation.CorrelationNames
 
nanSafeCompareDoubles(double, double) - Static method in class org.apache.spark.util.Utils
NaN-safe version of java.lang.Double.compare() which allows NaN values to be compared according to semantics where NaN == NaN and NaN is greater than any non-NaN double.
nanSafeCompareFloats(float, float) - Static method in class org.apache.spark.util.Utils
NaN-safe version of java.lang.Float.compare() which allows NaN values to be compared according to semantics where NaN == NaN and NaN is greater than any non-NaN float.
nanvl(Column, Column) - Static method in class org.apache.spark.sql.functions
Returns col1 if it is not NaN, or col2 if col1 is NaN.
NarrowDependency<T> - Class in org.apache.spark
:: DeveloperApi :: Base class for dependencies where each partition of the child RDD depends on a small number of partitions of the parent RDD.
NarrowDependency(RDD<T>) - Constructor for class org.apache.spark.NarrowDependency
 
ndcgAt(int) - Method in class org.apache.spark.mllib.evaluation.RankingMetrics
Compute the average NDCG value of all the queries, truncated at ranking position k.
needConversion() - Method in class org.apache.spark.sql.sources.BaseRelation
Whether does it need to convert the objects in Row to internal representation, for example: java.lang.String to UTF8String java.lang.Decimal to Decimal
needsReconfiguration() - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.ContinuousReader
The execution engine will call this method in every epoch to determine if new input partitions need to be generated, which may be required if for example the underlying source system has had partitions added or removed.
negate(Column) - Static method in class org.apache.spark.sql.functions
Unary minus, i.e.
negate(Decimal) - Method in interface org.apache.spark.sql.types.Decimal.DecimalIsConflicted
 
newAccumulatorInfos(Iterable<AccumulableInfo>) - Static method in class org.apache.spark.status.LiveEntityHelpers
 
newAPIHadoopFile(String, Class<F>, Class<K>, Class<V>, Configuration) - Method in class org.apache.spark.api.java.JavaSparkContext
Get an RDD for a given Hadoop file with an arbitrary new API InputFormat and extra configuration options to pass to the input format.
newAPIHadoopFile(String, ClassTag<K>, ClassTag<V>, ClassTag<F>) - Method in class org.apache.spark.SparkContext
Smarter version of newApiHadoopFile that uses class tags to figure out the classes of keys, values and the org.apache.hadoop.mapreduce.InputFormat (new MapReduce API) so that user don't need to pass them directly.
newAPIHadoopFile(String, Class<F>, Class<K>, Class<V>, Configuration) - Method in class org.apache.spark.SparkContext
Get an RDD for a given Hadoop file with an arbitrary new API InputFormat and extra configuration options to pass to the input format.
newAPIHadoopRDD(Configuration, Class<F>, Class<K>, Class<V>) - Method in class org.apache.spark.api.java.JavaSparkContext
Get an RDD for a given Hadoop file with an arbitrary new API InputFormat and extra configuration options to pass to the input format.
newAPIHadoopRDD(Configuration, Class<F>, Class<K>, Class<V>) - Method in class org.apache.spark.SparkContext
Get an RDD for a given Hadoop file with an arbitrary new API InputFormat and extra configuration options to pass to the input format.
newBooleanArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newBooleanEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newBooleanSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
Deprecated.
use newSequenceEncoder
newBoxedBooleanEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newBoxedByteEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newBoxedDoubleEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newBoxedFloatEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newBoxedIntEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newBoxedLongEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newBoxedShortEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newBroadcast(T, boolean, long, ClassTag<T>) - Method in interface org.apache.spark.broadcast.BroadcastFactory
Creates a new broadcast variable.
newByteArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newByteEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newByteSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
Deprecated.
use newSequenceEncoder
newDaemonCachedThreadPool(String) - Static method in class org.apache.spark.util.ThreadUtils
Wrapper over newCachedThreadPool.
newDaemonCachedThreadPool(String, int, int) - Static method in class org.apache.spark.util.ThreadUtils
Create a cached thread pool whose max number of threads is maxThreadNumber.
newDaemonFixedThreadPool(int, String) - Static method in class org.apache.spark.util.ThreadUtils
Wrapper over newFixedThreadPool.
newDaemonSingleThreadExecutor(String) - Static method in class org.apache.spark.util.ThreadUtils
Wrapper over newSingleThreadExecutor.
newDaemonSingleThreadScheduledExecutor(String) - Static method in class org.apache.spark.util.ThreadUtils
Wrapper over ScheduledThreadPoolExecutor.
newDaemonThreadPoolScheduledExecutor(String, int) - Static method in class org.apache.spark.util.ThreadUtils
Wrapper over ScheduledThreadPoolExecutor.
newDateEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newDoubleArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newDoubleEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newDoubleSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
Deprecated.
use newSequenceEncoder
newFloatArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newFloatEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newFloatSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
Deprecated.
use newSequenceEncoder
newForkJoinPool(String, int) - Static method in class org.apache.spark.util.ThreadUtils
Construct a new Scala ForkJoinPool with a specified max parallelism and name prefix.
NewHadoopMapPartitionsWithSplitRDD$() - Constructor for class org.apache.spark.rdd.NewHadoopRDD.NewHadoopMapPartitionsWithSplitRDD$
 
NewHadoopRDD<K,V> - Class in org.apache.spark.rdd
:: DeveloperApi :: An RDD that provides core functionality for reading data stored in Hadoop (e.g., files in HDFS, sources in HBase, or S3), using the new MapReduce API (org.apache.hadoop.mapreduce).
NewHadoopRDD(SparkContext, Class<? extends InputFormat<K, V>>, Class<K>, Class<V>, Configuration) - Constructor for class org.apache.spark.rdd.NewHadoopRDD
 
NewHadoopRDD.NewHadoopMapPartitionsWithSplitRDD$ - Class in org.apache.spark.rdd
 
newId() - Static method in class org.apache.spark.util.AccumulatorContext
Returns a globally unique ID for a new AccumulatorV2.
newInstance() - Method in class org.apache.spark.serializer.JavaSerializer
 
newInstance() - Method in class org.apache.spark.serializer.KryoSerializer
 
newInstance() - Method in class org.apache.spark.serializer.Serializer
Creates a new SerializerInstance.
newIntArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newIntEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newIntSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
Deprecated.
use newSequenceEncoder
newJavaDecimalEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newKryo() - Method in class org.apache.spark.serializer.KryoSerializer
 
newKryoOutput() - Method in class org.apache.spark.serializer.KryoSerializer
 
newLongArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newLongEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newLongSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
Deprecated.
use newSequenceEncoder
newMapEncoder(TypeTags.TypeTag<T>) - Method in class org.apache.spark.sql.SQLImplicits
 
newProductArrayEncoder(TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.SQLImplicits
 
newProductEncoder(TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.LowPrioritySQLImplicits
 
newProductSeqEncoder(TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.SQLImplicits
Deprecated.
use newSequenceEncoder
newScalaDecimalEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newSequenceEncoder(TypeTags.TypeTag<T>) - Method in class org.apache.spark.sql.SQLImplicits
 
newSession() - Method in interface org.apache.spark.sql.hive.client.HiveClient
Return a HiveClient as new session, that will share the class loader and Hive client
newSession() - Method in class org.apache.spark.sql.hive.HiveContext
Deprecated.
Returns a new HiveContext as new session, which will have separated SQLConf, UDF/UDAF, temporary tables and SessionState, but sharing the same CacheManager, IsolatedClientLoader and Hive client (both of execution and metadata) with existing HiveContext.
newSession() - Method in class org.apache.spark.sql.SparkSession
Start a new session with isolated SQL configurations, temporary tables, registered functions are isolated, but sharing the underlying SparkContext and cached data.
newSession() - Method in class org.apache.spark.sql.SQLContext
Returns a SQLContext as new session, with separated SQL configurations, temporary tables, registered functions, but sharing the same SparkContext, cached data and other things.
newSetEncoder(TypeTags.TypeTag<T>) - Method in class org.apache.spark.sql.SQLImplicits
Notice that we serialize Set to Catalyst array.
newShortArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newShortEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newShortSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
Deprecated.
use newSequenceEncoder
newStringArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newStringEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newStringSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
Deprecated.
use newSequenceEncoder
newTaskTempFile(TaskAttemptContext, Option<String>, String) - Method in class org.apache.spark.internal.io.FileCommitProtocol
Notifies the commit protocol to add a new file, and gets back the full path that should be used.
newTaskTempFile(TaskAttemptContext, Option<String>, String) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
 
newTaskTempFileAbsPath(TaskAttemptContext, String, String) - Method in class org.apache.spark.internal.io.FileCommitProtocol
Similar to newTaskTempFile(), but allows files to committed to an absolute output location.
newTaskTempFileAbsPath(TaskAttemptContext, String, String) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
 
newTemporaryConfiguration(boolean) - Static method in class org.apache.spark.sql.hive.HiveUtils
Constructs a configuration for hive, where the metastore is located in a temp directory.
newTimeStampEncoder() - Method in class org.apache.spark.sql.SQLImplicits
 
newVersionExternalTempPath(Path, Configuration, String) - Method in interface org.apache.spark.sql.hive.execution.SaveAsHiveFile
 
next() - Method in class org.apache.spark.InterruptibleIterator
 
next() - Method in interface org.apache.spark.mllib.clustering.LDAOptimizer
 
next() - Method in interface org.apache.spark.sql.sources.v2.reader.InputPartitionReader
Proceed to next record, returns false if there is no more records.
next() - Method in class org.apache.spark.status.LiveRDDPartition
 
next_day(Column, String) - Static method in class org.apache.spark.sql.functions
Returns the first date which is later than the value of the date column that is on the specified day of the week.
nextValue() - Method in class org.apache.spark.mllib.random.ExponentialGenerator
 
nextValue() - Method in class org.apache.spark.mllib.random.GammaGenerator
 
nextValue() - Method in class org.apache.spark.mllib.random.LogNormalGenerator
 
nextValue() - Method in class org.apache.spark.mllib.random.PoissonGenerator
 
nextValue() - Method in interface org.apache.spark.mllib.random.RandomDataGenerator
Returns an i.i.d.
nextValue() - Method in class org.apache.spark.mllib.random.StandardNormalGenerator
 
nextValue() - Method in class org.apache.spark.mllib.random.UniformGenerator
 
nextValue() - Method in class org.apache.spark.mllib.random.WeibullGenerator
 
NGram - Class in org.apache.spark.ml.feature
A feature transformer that converts the input array of strings into an array of n-grams.
NGram(String) - Constructor for class org.apache.spark.ml.feature.NGram
 
NGram() - Constructor for class org.apache.spark.ml.feature.NGram
 
NioBufferedFileInputStream - Class in org.apache.spark.io
InputStream implementation which uses direct buffer to read a file to avoid extra copy of data between Java and native memory which happens when using BufferedInputStream.
NioBufferedFileInputStream(File, int) - Constructor for class org.apache.spark.io.NioBufferedFileInputStream
 
NioBufferedFileInputStream(File) - Constructor for class org.apache.spark.io.NioBufferedFileInputStream
 
NNLS - Class in org.apache.spark.mllib.optimization
Object used to solve nonnegative least squares problems using a modified projected gradient method.
NNLS() - Constructor for class org.apache.spark.mllib.optimization.NNLS
 
NNLS.Workspace - Class in org.apache.spark.mllib.optimization
 
NO_PREF() - Static method in class org.apache.spark.scheduler.TaskLocality
 
NO_RESOURCE - Static variable in class org.apache.spark.launcher.SparkLauncher
A special value for the resource that tells Spark to not try to process the app resource as a file.
Node - Class in org.apache.spark.ml.tree
Decision tree node interface.
Node() - Constructor for class org.apache.spark.ml.tree.Node
 
Node - Class in org.apache.spark.mllib.tree.model
:: DeveloperApi :: Node in a decision tree.
Node(int, Predict, double, boolean, Option<Split>, Option<Node>, Option<Node>, Option<InformationGainStats>) - Constructor for class org.apache.spark.mllib.tree.model.Node
 
node() - Method in class org.apache.spark.scheduler.BlacklistedExecutor
 
NODE_LOCAL() - Static method in class org.apache.spark.scheduler.TaskLocality
 
nodeBlacklist() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors
 
NodeData(int, double, double, double[], double, int, int, DecisionTreeModelReadWrite.SplitData) - Constructor for class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
 
nodeData() - Method in class org.apache.spark.ml.tree.EnsembleModelReadWrite.EnsembleNodeData
 
NodeData(int, int, org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0.PredictData, double, boolean, Option<org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0.SplitData>, Option<Object>, Option<Object>, Option<Object>) - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
 
NodeData$() - Constructor for class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData$
 
NodeData$() - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData$
 
nodeId() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
 
noLocality() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
 
Nominal() - Static method in class org.apache.spark.ml.attribute.AttributeType
Nominal type.
NominalAttribute - Class in org.apache.spark.ml.attribute
:: DeveloperApi :: A nominal attribute.
NONE - Static variable in class org.apache.spark.api.java.StorageLevels
 
None - Static variable in class org.apache.spark.graphx.TripletFields
None of the triplet fields are exposed.
NONE() - Static method in class org.apache.spark.scheduler.SchedulingMode
 
NONE() - Static method in class org.apache.spark.storage.StorageLevel
 
nonLocalPaths(String, boolean) - Static method in class org.apache.spark.util.Utils
Return all non-local paths from a comma-separated list of paths.
nonnegative() - Method in interface org.apache.spark.ml.recommendation.ALSParams
Param for whether to apply nonnegativity constraints.
nonNegativeHash(Object) - Static method in class org.apache.spark.util.Utils
 
nonNegativeMod(int, int) - Static method in class org.apache.spark.util.Utils
 
NoopDialect - Class in org.apache.spark.sql.jdbc
NOOP dialect object, always returning the neutral element.
NoopDialect() - Constructor for class org.apache.spark.sql.jdbc.NoopDialect
 
norm(Vector, double) - Static method in class org.apache.spark.ml.linalg.Vectors
Returns the p-norm of this vector.
norm(Vector, double) - Static method in class org.apache.spark.mllib.linalg.Vectors
Returns the p-norm of this vector.
NormalEquationSolver - Interface in org.apache.spark.ml.optim
Interface for classes that solve the normal equations locally.
normalizeDuration(long) - Static method in class org.apache.spark.streaming.ui.UIUtils
Find the best TimeUnit for converting milliseconds to a friendly string.
Normalizer - Class in org.apache.spark.ml.feature
Normalize a vector to have unit norm using the given p-norm.
Normalizer(String) - Constructor for class org.apache.spark.ml.feature.Normalizer
 
Normalizer() - Constructor for class org.apache.spark.ml.feature.Normalizer
 
Normalizer - Class in org.apache.spark.mllib.feature
Normalizes samples individually to unit L^p^ norm
Normalizer(double) - Constructor for class org.apache.spark.mllib.feature.Normalizer
 
Normalizer() - Constructor for class org.apache.spark.mllib.feature.Normalizer
 
normalizeToProbabilitiesInPlace(DenseVector) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
Normalize a vector of raw predictions to be a multinomial probability vector, in place.
normalJavaRDD(JavaSparkContext, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Java-friendly version of RandomRDDs.normalRDD.
normalJavaRDD(JavaSparkContext, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.normalJavaRDD with the default seed.
normalJavaRDD(JavaSparkContext, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.normalJavaRDD with the default number of partitions and the default seed.
normalJavaVectorRDD(JavaSparkContext, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Java-friendly version of RandomRDDs.normalVectorRDD.
normalJavaVectorRDD(JavaSparkContext, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.normalJavaVectorRDD with the default seed.
normalJavaVectorRDD(JavaSparkContext, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.normalJavaVectorRDD with the default number of partitions and the default seed.
normalRDD(SparkContext, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Generates an RDD comprised of i.i.d. samples from the standard normal distribution.
normalVectorRDD(SparkContext, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from the standard normal distribution.
normL1(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
normL1(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
normL1() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
L1 norm of each dimension.
normL1() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
L1 norm of each column
normL2(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
normL2(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
normL2() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
L2 (Euclidean) norm of each dimension.
normL2() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
Euclidean magnitude of each column
normPdf(double, double, double, double) - Static method in class org.apache.spark.mllib.stat.KernelDensity
Evaluates the PDF of a normal distribution.
not(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
not(Column) - Static method in class org.apache.spark.sql.functions
Inversion of boolean expression, i.e.
Not - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff child is evaluated to false.
Not(Filter) - Constructor for class org.apache.spark.sql.sources.Not
 
notEqual(Object) - Method in class org.apache.spark.sql.Column
Inequality test.
NoTimeout() - Static method in class org.apache.spark.sql.streaming.GroupStateTimeout
No timeout.
ntile(int) - Static method in class org.apache.spark.sql.functions
Window function: returns the ntile group id (from 1 to n inclusive) in an ordered window partition.
nullable() - Method in class org.apache.spark.sql.catalog.Column
 
nullable() - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
Returns true when the UDF can return a nullable value.
nullable() - Method in class org.apache.spark.sql.types.StructField
 
nullDeviance() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
The deviance for the null model.
nullHypothesis() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
 
nullHypothesis() - Method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTestResult
 
nullHypothesis() - Method in interface org.apache.spark.mllib.stat.test.StreamingTestMethod
 
nullHypothesis() - Static method in class org.apache.spark.mllib.stat.test.StudentTTest
 
nullHypothesis() - Method in interface org.apache.spark.mllib.stat.test.TestResult
Null hypothesis of the test.
nullHypothesis() - Static method in class org.apache.spark.mllib.stat.test.WelchTTest
 
NullHypothesis$() - Constructor for class org.apache.spark.mllib.stat.test.ChiSqTest.NullHypothesis$
 
NullHypothesis$() - Constructor for class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTest.NullHypothesis$
 
NullType - Static variable in class org.apache.spark.sql.types.DataTypes
Gets the NullType object.
NullType - Class in org.apache.spark.sql.types
The data type representing NULL values.
NullType() - Constructor for class org.apache.spark.sql.types.NullType
 
NUM_ATTRIBUTES() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
 
NUM_PARTITIONS() - Static method in class org.apache.spark.ui.UIWorkloadGenerator
 
NUM_VALUES() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
 
numAccums() - Static method in class org.apache.spark.util.AccumulatorContext
Returns the number of accumulators registered.
numActiveBatches() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
numActiveOutputOps() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
 
numActiveReceivers() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
numActives() - Method in class org.apache.spark.ml.linalg.DenseMatrix
 
numActives() - Method in class org.apache.spark.ml.linalg.DenseVector
 
numActives() - Method in interface org.apache.spark.ml.linalg.Matrix
Find the number of values stored explicitly.
numActives() - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
numActives() - Method in class org.apache.spark.ml.linalg.SparseVector
 
numActives() - Method in interface org.apache.spark.ml.linalg.Vector
Number of active entries.
numActives() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
 
numActives() - Method in class org.apache.spark.mllib.linalg.DenseVector
 
numActives() - Method in interface org.apache.spark.mllib.linalg.Matrix
Find the number of values stored explicitly.
numActives() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
numActives() - Method in class org.apache.spark.mllib.linalg.SparseVector
 
numActives() - Method in interface org.apache.spark.mllib.linalg.Vector
Number of active entries.
numActiveStages() - Method in class org.apache.spark.status.api.v1.JobData
 
numActiveTasks() - Method in interface org.apache.spark.SparkStageInfo
 
numActiveTasks() - Method in class org.apache.spark.SparkStageInfoImpl
 
numActiveTasks() - Method in class org.apache.spark.status.api.v1.JobData
 
numActiveTasks() - Method in class org.apache.spark.status.api.v1.StageData
 
numAttributes() - Method in class org.apache.spark.ml.attribute.AttributeGroup
 
numAvailableOutputs() - Method in class org.apache.spark.ShuffleStatus
Number of partitions that have shuffle outputs.
numBins() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
 
numBuckets() - Method in interface org.apache.spark.ml.feature.QuantileDiscretizerBase
Number of buckets (quantiles, or categories) into which data points are grouped.
numBucketsArray() - Method in interface org.apache.spark.ml.feature.QuantileDiscretizerBase
Array of number of buckets (quantiles, or categories) into which data points are grouped.
numCachedPartitions() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
 
numCachedPartitions() - Method in class org.apache.spark.storage.RDDInfo
 
numCategories() - Method in class org.apache.spark.ml.tree.CategoricalSplit
 
numCategories() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData
 
numClasses() - Method in class org.apache.spark.ml.classification.ClassificationModel
Number of classes (values which the label can take).
numClasses() - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
 
numClasses() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
 
numClasses() - Method in class org.apache.spark.ml.classification.LinearSVCModel
 
numClasses() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
 
numClasses() - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
 
numClasses() - Method in class org.apache.spark.ml.classification.NaiveBayesModel
 
numClasses() - Method in class org.apache.spark.ml.classification.OneVsRestModel
 
numClasses() - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
 
numClasses() - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
 
numClasses() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
numColBlocks() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
 
numCols() - Method in class org.apache.spark.ml.linalg.DenseMatrix
 
numCols() - Method in interface org.apache.spark.ml.linalg.Matrix
Number of columns.
numCols() - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
numCols() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
 
numCols() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
 
numCols() - Method in class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
Gets or computes the number of columns.
numCols() - Method in interface org.apache.spark.mllib.linalg.distributed.DistributedMatrix
Gets or computes the number of columns.
numCols() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
 
numCols() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
Gets or computes the number of columns.
numCols() - Method in interface org.apache.spark.mllib.linalg.Matrix
Number of columns.
numCols() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
numCols() - Method in class org.apache.spark.sql.vectorized.ColumnarBatch
Returns the number of columns that make up this batch.
numCompletedIndices() - Method in class org.apache.spark.status.api.v1.JobData
 
numCompletedIndices() - Method in class org.apache.spark.status.api.v1.StageData
 
numCompletedOutputOps() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
 
numCompletedStages() - Method in class org.apache.spark.status.api.v1.JobData
 
numCompletedTasks() - Method in interface org.apache.spark.SparkStageInfo
 
numCompletedTasks() - Method in class org.apache.spark.SparkStageInfoImpl
 
numCompletedTasks() - Method in class org.apache.spark.status.api.v1.JobData
 
numCompleteTasks() - Method in class org.apache.spark.status.api.v1.StageData
 
numEdges() - Method in class org.apache.spark.graphx.GraphOps
The number of edges in the graph.
numElements() - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
numElements() - Method in class org.apache.spark.sql.vectorized.ColumnarMap
 
Numeric() - Static method in class org.apache.spark.ml.attribute.AttributeType
Numeric type.
NumericAttribute - Class in org.apache.spark.ml.attribute
:: DeveloperApi :: A numeric attribute with optional summary statistics.
NumericParser - Class in org.apache.spark.mllib.util
Simple parser for a numeric structure consisting of three types:
NumericParser() - Constructor for class org.apache.spark.mllib.util.NumericParser
 
numericRDDToDoubleRDDFunctions(RDD<T>, Numeric<T>) - Static method in class org.apache.spark.rdd.RDD
 
NumericType - Class in org.apache.spark.sql.types
Numeric data types.
NumericType() - Constructor for class org.apache.spark.sql.types.NumericType
 
numFailedOutputOps() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
 
numFailedStages() - Method in class org.apache.spark.status.api.v1.JobData
 
numFailedTasks() - Method in interface org.apache.spark.SparkStageInfo
 
numFailedTasks() - Method in class org.apache.spark.SparkStageInfoImpl
 
numFailedTasks() - Method in class org.apache.spark.status.api.v1.JobData
 
numFailedTasks() - Method in class org.apache.spark.status.api.v1.StageData
 
numFalseNegatives() - Method in interface org.apache.spark.mllib.evaluation.binary.BinaryConfusionMatrix
number of false negatives
numFalsePositives() - Method in interface org.apache.spark.mllib.evaluation.binary.BinaryConfusionMatrix
number of false positives
numFeatures() - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
 
numFeatures() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
 
numFeatures() - Method in class org.apache.spark.ml.classification.LinearSVCModel
 
numFeatures() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
 
numFeatures() - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
 
numFeatures() - Method in class org.apache.spark.ml.classification.NaiveBayesModel
 
numFeatures() - Method in class org.apache.spark.ml.classification.OneVsRestModel
 
numFeatures() - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
 
numFeatures() - Method in class org.apache.spark.ml.feature.FeatureHasher
Number of features.
numFeatures() - Method in class org.apache.spark.ml.feature.HashingTF
Number of features.
numFeatures() - Method in class org.apache.spark.ml.feature.VectorIndexerModel
 
numFeatures() - Method in class org.apache.spark.ml.PredictionModel
Returns the number of features the model was trained on.
numFeatures() - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
 
numFeatures() - Method in class org.apache.spark.ml.regression.GBTRegressionModel
 
numFeatures() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
 
numFeatures() - Method in class org.apache.spark.ml.regression.LinearRegressionModel
 
numFeatures() - Method in class org.apache.spark.ml.regression.RandomForestRegressionModel
 
numFeatures() - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
 
numFeatures() - Method in class org.apache.spark.mllib.feature.HashingTF
 
numFields() - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
numFolds() - Method in interface org.apache.spark.ml.tuning.CrossValidatorParams
Param for number of folds for cross validation.
numHashTables() - Method in interface org.apache.spark.ml.feature.LSHParams
Param for the number of hash tables used in LSH OR-amplification.
numInactiveReceivers() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
numInputRows() - Method in class org.apache.spark.sql.streaming.SourceProgress
 
numInputRows() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
The aggregate (across all sources) number of records processed in a trigger.
numInstances() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
Number of instances in DataFrame predictions.
numInstances() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
Number of instances in DataFrame predictions
numItemBlocks() - Method in interface org.apache.spark.ml.recommendation.ALSParams
Param for number of item blocks (positive).
numIter() - Method in class org.apache.spark.ml.clustering.ClusteringSummary
 
numIterations() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionTrainingSummary
 
numIterations() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
numKilledTasks() - Method in class org.apache.spark.status.api.v1.JobData
 
numKilledTasks() - Method in class org.apache.spark.status.api.v1.StageData
 
numNegatives() - Method in interface org.apache.spark.mllib.evaluation.binary.BinaryConfusionMatrix
number of negatives
numNodes() - Method in interface org.apache.spark.ml.tree.DecisionTreeModel
Number of nodes in tree, including leaf nodes.
numNodes() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
Get number of nodes in tree, including leaf nodes.
numNonzeros() - Method in class org.apache.spark.ml.linalg.DenseMatrix
 
numNonzeros() - Method in class org.apache.spark.ml.linalg.DenseVector
 
numNonzeros() - Method in interface org.apache.spark.ml.linalg.Matrix
Find the number of non-zero active values.
numNonzeros() - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
numNonzeros() - Method in class org.apache.spark.ml.linalg.SparseVector
 
numNonzeros() - Method in interface org.apache.spark.ml.linalg.Vector
Number of nonzero elements.
numNonZeros(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
numNonZeros(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
numNonzeros() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
 
numNonzeros() - Method in class org.apache.spark.mllib.linalg.DenseVector
 
numNonzeros() - Method in interface org.apache.spark.mllib.linalg.Matrix
Find the number of non-zero active values.
numNonzeros() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
numNonzeros() - Method in class org.apache.spark.mllib.linalg.SparseVector
 
numNonzeros() - Method in interface org.apache.spark.mllib.linalg.Vector
Number of nonzero elements.
numNonzeros() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
Number of nonzero elements in each dimension.
numNonzeros() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
Number of nonzero elements (including explicitly presented zero values) in each column.
numNulls() - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
 
numNulls() - Method in class org.apache.spark.sql.vectorized.ColumnVector
Returns the number of nulls in this column vector.
numOfPoints() - Method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette.ClusterStats
 
numPartitions() - Method in class org.apache.spark.HashPartitioner
 
numPartitions() - Method in interface org.apache.spark.ml.feature.Word2VecBase
Number of partitions for sentences of words.
numPartitions() - Method in interface org.apache.spark.ml.fpm.FPGrowthParams
Number of partitions (at least 1) used by parallel FP-growth.
numPartitions() - Method in class org.apache.spark.Partitioner
 
numPartitions() - Method in class org.apache.spark.RangePartitioner
 
numPartitions() - Method in class org.apache.spark.rdd.PartitionGroup
 
numPartitions() - Method in interface org.apache.spark.sql.sources.v2.reader.partitioning.Partitioning
Returns the number of partitions(i.e., InputPartitions) the data source outputs.
numPartitions() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
 
numPartitions() - Method in class org.apache.spark.storage.RDDInfo
 
numPartitions(int) - Method in class org.apache.spark.streaming.StateSpec
Set the number of partitions by which the state RDDs generated by mapWithState will be partitioned.
numPositives() - Method in interface org.apache.spark.mllib.evaluation.binary.BinaryConfusionMatrix
number of positives
numProcessedRecords() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
numReceivedRecords() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
numReceivers() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
numRecords() - Method in interface org.apache.spark.streaming.receiver.ReceivedBlockStoreResult
 
numRecords() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
The number of recorders received by the receivers in this batch.
numRecords() - Method in class org.apache.spark.streaming.scheduler.StreamInputInfo
 
numRetainedCompletedBatches() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
numRetries(SparkConf) - Static method in class org.apache.spark.util.RpcUtils
Returns the configured number of times to retry connecting
numRowBlocks() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
 
numRows() - Method in class org.apache.spark.ml.linalg.DenseMatrix
 
numRows() - Method in interface org.apache.spark.ml.linalg.Matrix
Number of rows.
numRows() - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
numRows() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
 
numRows() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
 
numRows() - Method in class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
Gets or computes the number of rows.
numRows() - Method in interface org.apache.spark.mllib.linalg.distributed.DistributedMatrix
Gets or computes the number of rows.
numRows() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
 
numRows() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
Gets or computes the number of rows.
numRows() - Method in interface org.apache.spark.mllib.linalg.Matrix
Number of rows.
numRows() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
numRows() - Method in interface org.apache.spark.sql.sources.v2.reader.Statistics
 
numRows() - Method in class org.apache.spark.sql.vectorized.ColumnarBatch
Returns the number of rows for read, including filtered rows.
numRowsTotal() - Method in class org.apache.spark.sql.streaming.StateOperatorProgress
 
numRowsUpdated() - Method in class org.apache.spark.sql.streaming.StateOperatorProgress
 
numRunningTasks() - Method in interface org.apache.spark.SparkExecutorInfo
 
numRunningTasks() - Method in class org.apache.spark.SparkExecutorInfoImpl
 
numSkippedStages() - Method in class org.apache.spark.status.api.v1.JobData
 
numSkippedTasks() - Method in class org.apache.spark.status.api.v1.JobData
 
numSpilledStages() - Method in class org.apache.spark.SpillListener
 
numStreamBlocks() - Method in class org.apache.spark.ui.storage.ExecutorStreamSummary
 
numTasks() - Method in class org.apache.spark.scheduler.StageInfo
 
numTasks() - Method in interface org.apache.spark.SparkStageInfo
 
numTasks() - Method in class org.apache.spark.SparkStageInfoImpl
 
numTasks() - Method in class org.apache.spark.status.api.v1.JobData
 
numTasks() - Method in class org.apache.spark.status.api.v1.StageData
 
numTopFeatures() - Method in interface org.apache.spark.ml.feature.ChiSqSelectorParams
Number of features that selector will select, ordered by ascending p-value.
numTopFeatures() - Method in class org.apache.spark.mllib.feature.ChiSqSelector
 
numTotalCompletedBatches() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
numTotalOutputOps() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
 
numTrees() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
Deprecated.
Use getNumTrees instead. This method will be removed in 3.0.0.
numTrees() - Method in class org.apache.spark.ml.regression.GBTRegressionModel
Deprecated.
Use getNumTrees instead. This method will be removed in 3.0.0.
numTrees() - Method in interface org.apache.spark.ml.tree.RandomForestParams
Number of trees to train (at least 1).
numTrueNegatives() - Method in interface org.apache.spark.mllib.evaluation.binary.BinaryConfusionMatrix
number of true negatives
numTruePositives() - Method in interface org.apache.spark.mllib.evaluation.binary.BinaryConfusionMatrix
number of true positives
numUserBlocks() - Method in interface org.apache.spark.ml.recommendation.ALSParams
Param for number of user blocks (positive).
numValues() - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
numVertices() - Method in class org.apache.spark.graphx.GraphOps
The number of vertices in the graph.

O

obj() - Method in class org.apache.spark.internal.io.FileCommitProtocol.TaskCommitMessage
 
objectFile(String, int) - Method in class org.apache.spark.api.java.JavaSparkContext
Load an RDD saved as a SequenceFile containing serialized objects, with NullWritable keys and BytesWritable values that contain a serialized partition.
objectFile(String) - Method in class org.apache.spark.api.java.JavaSparkContext
Load an RDD saved as a SequenceFile containing serialized objects, with NullWritable keys and BytesWritable values that contain a serialized partition.
objectFile(String, int, ClassTag<T>) - Method in class org.apache.spark.SparkContext
Load an RDD saved as a SequenceFile containing serialized objects, with NullWritable keys and BytesWritable values that contain a serialized partition.
objectiveHistory() - Method in class org.apache.spark.ml.classification.BinaryLogisticRegressionTrainingSummaryImpl
 
objectiveHistory() - Method in interface org.apache.spark.ml.classification.LogisticRegressionTrainingSummary
objective function (scaled loss + regularization) at each iteration.
objectiveHistory() - Method in class org.apache.spark.ml.classification.LogisticRegressionTrainingSummaryImpl
 
objectiveHistory() - Method in class org.apache.spark.ml.regression.LinearRegressionTrainingSummary
 
ObjectStreamClassMethods(ObjectStreamClass) - Constructor for class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
 
ObjectStreamClassMethods$() - Constructor for class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods$
 
ObjectType - Class in org.apache.spark.sql.types
 
ObjectType(Class<?>) - Constructor for class org.apache.spark.sql.types.ObjectType
 
ocvTypes() - Static method in class org.apache.spark.ml.image.ImageSchema
(Scala-specific) OpenCV type mapping supported
of(T) - Static method in class org.apache.spark.api.java.Optional
 
of(RDD<Tuple2<Object, Object>>) - Static method in class org.apache.spark.mllib.evaluation.AreaUnderCurve
Returns the area under the given curve.
of(Iterable<Tuple2<Object, Object>>) - Static method in class org.apache.spark.mllib.evaluation.AreaUnderCurve
Returns the area under the given curve.
of(JavaRDD<Tuple2<T, T>>) - Static method in class org.apache.spark.mllib.evaluation.RankingMetrics
Creates a RankingMetrics instance (for Java users).
OFF_HEAP - Static variable in class org.apache.spark.api.java.StorageLevels
 
OFF_HEAP() - Static method in class org.apache.spark.storage.StorageLevel
 
offHeapMemoryRemaining() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
 
offHeapMemoryUsed() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
 
offHeapUsed() - Method in class org.apache.spark.status.LiveRDDDistribution
 
Offset - Class in org.apache.spark.sql.sources.v2.reader.streaming
An abstract representation of progress through a MicroBatchReader or ContinuousReader.
Offset() - Constructor for class org.apache.spark.sql.sources.v2.reader.streaming.Offset
 
offsetBytes(String, long, long, long) - Static method in class org.apache.spark.util.Utils
Return a string containing part of a file from byte 'start' to 'end'.
offsetBytes(Seq<File>, Seq<Object>, long, long) - Static method in class org.apache.spark.util.Utils
Return a string containing data across a set of files.
offsetCol() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
Param for offset column name.
ofNullable(T) - Static method in class org.apache.spark.api.java.Optional
 
ofRows(SparkSession, LogicalPlan) - Static method in class org.apache.spark.sql.Dataset
 
oldVersionExternalTempPath(Path, Configuration, String) - Method in interface org.apache.spark.sql.hive.execution.SaveAsHiveFile
 
onAddData(Object, Object) - Method in interface org.apache.spark.streaming.receiver.BlockGeneratorListener
Called after a data item is added into the BlockGenerator.
onApplicationEnd(SparkListenerApplicationEnd) - Method in class org.apache.spark.scheduler.SparkListener
 
onApplicationEnd(SparkListenerApplicationEnd) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when the application ends
onApplicationEnd(SparkListenerApplicationEnd) - Method in class org.apache.spark.SparkFirehoseListener
 
onApplicationStart(SparkListenerApplicationStart) - Method in class org.apache.spark.scheduler.SparkListener
 
onApplicationStart(SparkListenerApplicationStart) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when the application starts
onApplicationStart(SparkListenerApplicationStart) - Method in class org.apache.spark.SparkFirehoseListener
 
onBatchCompleted(JavaStreamingListenerBatchCompleted) - Method in interface org.apache.spark.streaming.api.java.PythonStreamingListener
Called when processing of a batch of jobs has completed.
onBatchCompleted(StreamingListenerBatchCompleted) - Method in class org.apache.spark.streaming.scheduler.StatsReportListener
 
onBatchCompleted(StreamingListenerBatchCompleted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
Called when processing of a batch of jobs has completed.
onBatchStarted(JavaStreamingListenerBatchStarted) - Method in interface org.apache.spark.streaming.api.java.PythonStreamingListener
Called when processing of a batch of jobs has started.
onBatchStarted(StreamingListenerBatchStarted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
Called when processing of a batch of jobs has started.
onBatchSubmitted(JavaStreamingListenerBatchSubmitted) - Method in interface org.apache.spark.streaming.api.java.PythonStreamingListener
Called when a batch of jobs has been submitted for processing.
onBatchSubmitted(StreamingListenerBatchSubmitted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
Called when a batch of jobs has been submitted for processing.
onBlockManagerAdded(SparkListenerBlockManagerAdded) - Method in class org.apache.spark.scheduler.SparkListener
 
onBlockManagerAdded(SparkListenerBlockManagerAdded) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when a new block manager has joined
onBlockManagerAdded(SparkListenerBlockManagerAdded) - Method in class org.apache.spark.SparkFirehoseListener
 
onBlockManagerRemoved(SparkListenerBlockManagerRemoved) - Method in class org.apache.spark.scheduler.SparkListener
 
onBlockManagerRemoved(SparkListenerBlockManagerRemoved) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when an existing block manager has been removed
onBlockManagerRemoved(SparkListenerBlockManagerRemoved) - Method in class org.apache.spark.SparkFirehoseListener
 
onBlockUpdated(SparkListenerBlockUpdated) - Method in class org.apache.spark.scheduler.SparkListener
 
onBlockUpdated(SparkListenerBlockUpdated) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when the driver receives a block update info.
onBlockUpdated(SparkListenerBlockUpdated) - Method in class org.apache.spark.SparkFirehoseListener
 
Once() - Static method in class org.apache.spark.sql.streaming.Trigger
A trigger that process only one batch of data in a streaming query then terminates the query.
OnceParser(Function1<Reader<Object>, Parsers.ParseResult<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
onComplete(Function1<Try<T>, U>, ExecutionContext) - Method in class org.apache.spark.ComplexFutureAction
 
onComplete(Function1<Try<T>, U>, ExecutionContext) - Method in interface org.apache.spark.FutureAction
When this action is completed, either through an exception, or a value, applies the provided function.
onComplete(Function1<R, BoxedUnit>) - Method in class org.apache.spark.partial.PartialResult
Set a handler to be called when this PartialResult completes.
onComplete(Function1<Try<T>, U>, ExecutionContext) - Method in class org.apache.spark.SimpleFutureAction
 
onConnected(RpcAddress) - Method in interface org.apache.spark.rpc.RpcEndpoint
Invoked when remoteAddress is connected to the current node.
onDataWriterCommit(WriterCommitMessage) - Method in interface org.apache.spark.sql.sources.v2.writer.DataSourceWriter
Handles a commit message on receiving from a successful data writer.
onDisconnected(RpcAddress) - Method in interface org.apache.spark.rpc.RpcEndpoint
Invoked when remoteAddress is lost.
OneHotEncoder - Class in org.apache.spark.ml.feature
Deprecated.
OneHotEncoderEstimator will be renamed OneHotEncoder and this OneHotEncoder will be removed in 3.0.0.
OneHotEncoder(String) - Constructor for class org.apache.spark.ml.feature.OneHotEncoder
Deprecated.
 
OneHotEncoder() - Constructor for class org.apache.spark.ml.feature.OneHotEncoder
Deprecated.
 
OneHotEncoderBase - Interface in org.apache.spark.ml.feature
Private trait for params and common methods for OneHotEncoderEstimator and OneHotEncoderModel
OneHotEncoderCommon - Class in org.apache.spark.ml.feature
Provides some helper methods used by both OneHotEncoder and OneHotEncoderEstimator.
OneHotEncoderCommon() - Constructor for class org.apache.spark.ml.feature.OneHotEncoderCommon
 
OneHotEncoderEstimator - Class in org.apache.spark.ml.feature
A one-hot encoder that maps a column of category indices to a column of binary vectors, with at most a single one-value per row that indicates the input category index.
OneHotEncoderEstimator(String) - Constructor for class org.apache.spark.ml.feature.OneHotEncoderEstimator
 
OneHotEncoderEstimator() - Constructor for class org.apache.spark.ml.feature.OneHotEncoderEstimator
 
OneHotEncoderModel - Class in org.apache.spark.ml.feature
param: categorySizes Original number of categories for each feature being encoded.
onEnvironmentUpdate(SparkListenerEnvironmentUpdate) - Method in class org.apache.spark.scheduler.SparkListener
 
onEnvironmentUpdate(SparkListenerEnvironmentUpdate) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when environment properties have been updated
onEnvironmentUpdate(SparkListenerEnvironmentUpdate) - Method in class org.apache.spark.SparkFirehoseListener
 
onError(Throwable) - Method in interface org.apache.spark.rpc.RpcEndpoint
Invoked when any exception is thrown during handling messages.
onError(String, Throwable) - Method in interface org.apache.spark.streaming.receiver.BlockGeneratorListener
Called when an error has occurred in the BlockGenerator.
ones(int, int) - Static method in class org.apache.spark.ml.linalg.DenseMatrix
Generate a DenseMatrix consisting of ones.
ones(int, int) - Static method in class org.apache.spark.ml.linalg.Matrices
Generate a DenseMatrix consisting of ones.
ones(int, int) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
Generate a DenseMatrix consisting of ones.
ones(int, int) - Static method in class org.apache.spark.mllib.linalg.Matrices
Generate a DenseMatrix consisting of ones.
OneSampleTwoSided() - Method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTest.NullHypothesis$
 
OneToOneDependency<T> - Class in org.apache.spark
:: DeveloperApi :: Represents a one-to-one dependency between partitions of the parent and child RDDs.
OneToOneDependency(RDD<T>) - Constructor for class org.apache.spark.OneToOneDependency
 
onEvent(SparkListenerEvent) - Method in class org.apache.spark.SparkFirehoseListener
 
OneVsRest - Class in org.apache.spark.ml.classification
Reduction of Multiclass Classification to Binary Classification.
OneVsRest(String) - Constructor for class org.apache.spark.ml.classification.OneVsRest
 
OneVsRest() - Constructor for class org.apache.spark.ml.classification.OneVsRest
 
OneVsRestModel - Class in org.apache.spark.ml.classification
Model produced by OneVsRest.
OneVsRestParams - Interface in org.apache.spark.ml.classification
Params for OneVsRest.
onExecutorAdded(SparkListenerExecutorAdded) - Method in class org.apache.spark.scheduler.SparkListener
 
onExecutorAdded(SparkListenerExecutorAdded) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when the driver registers a new executor.
onExecutorAdded(SparkListenerExecutorAdded) - Method in class org.apache.spark.SparkFirehoseListener
 
onExecutorBlacklisted(SparkListenerExecutorBlacklisted) - Method in class org.apache.spark.scheduler.SparkListener
 
onExecutorBlacklisted(SparkListenerExecutorBlacklisted) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when the driver blacklists an executor for a Spark application.
onExecutorBlacklisted(SparkListenerExecutorBlacklisted) - Method in class org.apache.spark.SparkFirehoseListener
 
onExecutorBlacklistedForStage(SparkListenerExecutorBlacklistedForStage) - Method in class org.apache.spark.scheduler.SparkListener
 
onExecutorBlacklistedForStage(SparkListenerExecutorBlacklistedForStage) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when the driver blacklists an executor for a stage.
onExecutorBlacklistedForStage(SparkListenerExecutorBlacklistedForStage) - Method in class org.apache.spark.SparkFirehoseListener
 
onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate) - Method in class org.apache.spark.scheduler.SparkListener
 
onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when the driver receives task metrics from an executor in a heartbeat.
onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate) - Method in class org.apache.spark.SparkFirehoseListener
 
onExecutorRemoved(SparkListenerExecutorRemoved) - Method in class org.apache.spark.scheduler.SparkListener
 
onExecutorRemoved(SparkListenerExecutorRemoved) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when the driver removes an executor.
onExecutorRemoved(SparkListenerExecutorRemoved) - Method in class org.apache.spark.SparkFirehoseListener
 
onExecutorUnblacklisted(SparkListenerExecutorUnblacklisted) - Method in class org.apache.spark.scheduler.SparkListener
 
onExecutorUnblacklisted(SparkListenerExecutorUnblacklisted) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when the driver re-enables a previously blacklisted executor.
onExecutorUnblacklisted(SparkListenerExecutorUnblacklisted) - Method in class org.apache.spark.SparkFirehoseListener
 
onFail(Function1<Exception, BoxedUnit>) - Method in class org.apache.spark.partial.PartialResult
Set a handler to be called if this PartialResult's job fails.
onFailure(Throwable) - Method in interface org.apache.spark.rpc.netty.OutboxMessage
 
onFailure(String, QueryExecution, Exception) - Method in interface org.apache.spark.sql.util.QueryExecutionListener
A callback function that will be called when a query execution failed.
onGenerateBlock(StreamBlockId) - Method in interface org.apache.spark.streaming.receiver.BlockGeneratorListener
Called when a new block of data is generated by the block generator.
onHeapMemoryRemaining() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
 
onHeapMemoryUsed() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
 
onHeapUsed() - Method in class org.apache.spark.status.LiveRDDDistribution
 
onJobEnd(SparkListenerJobEnd) - Method in class org.apache.spark.scheduler.SparkListener
 
onJobEnd(SparkListenerJobEnd) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when a job ends
onJobEnd(SparkListenerJobEnd) - Method in class org.apache.spark.SparkFirehoseListener
 
onJobStart(SparkListenerJobStart) - Method in class org.apache.spark.scheduler.SparkListener
 
onJobStart(SparkListenerJobStart) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when a job starts
onJobStart(SparkListenerJobStart) - Method in class org.apache.spark.SparkFirehoseListener
 
OnlineLDAOptimizer - Class in org.apache.spark.mllib.clustering
:: DeveloperApi ::
OnlineLDAOptimizer() - Constructor for class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
 
onNetworkError(Throwable, RpcAddress) - Method in interface org.apache.spark.rpc.RpcEndpoint
Invoked when some network error happens in the connection between the current node and remoteAddress.
onNodeBlacklisted(SparkListenerNodeBlacklisted) - Method in class org.apache.spark.scheduler.SparkListener
 
onNodeBlacklisted(SparkListenerNodeBlacklisted) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when the driver blacklists a node for a Spark application.
onNodeBlacklisted(SparkListenerNodeBlacklisted) - Method in class org.apache.spark.SparkFirehoseListener
 
onNodeBlacklistedForStage(SparkListenerNodeBlacklistedForStage) - Method in class org.apache.spark.scheduler.SparkListener
 
onNodeBlacklistedForStage(SparkListenerNodeBlacklistedForStage) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when the driver blacklists a node for a stage.
onNodeBlacklistedForStage(SparkListenerNodeBlacklistedForStage) - Method in class org.apache.spark.SparkFirehoseListener
 
onNodeUnblacklisted(SparkListenerNodeUnblacklisted) - Method in class org.apache.spark.scheduler.SparkListener
 
onNodeUnblacklisted(SparkListenerNodeUnblacklisted) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when the driver re-enables a previously blacklisted node.
onNodeUnblacklisted(SparkListenerNodeUnblacklisted) - Method in class org.apache.spark.SparkFirehoseListener
 
onOtherEvent(SparkListenerEvent) - Method in class org.apache.spark.scheduler.SparkListener
 
onOtherEvent(SparkListenerEvent) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when other events like SQL-specific events are posted.
onOtherEvent(SparkListenerEvent) - Method in class org.apache.spark.SparkFirehoseListener
 
onOutputOperationCompleted(JavaStreamingListenerOutputOperationCompleted) - Method in interface org.apache.spark.streaming.api.java.PythonStreamingListener
Called when processing of a job of a batch has completed.
onOutputOperationCompleted(StreamingListenerOutputOperationCompleted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
Called when processing of a job of a batch has completed.
onOutputOperationStarted(JavaStreamingListenerOutputOperationStarted) - Method in interface org.apache.spark.streaming.api.java.PythonStreamingListener
Called when processing of a job of a batch has started.
onOutputOperationStarted(StreamingListenerOutputOperationStarted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
Called when processing of a job of a batch has started.
onPushBlock(StreamBlockId, ArrayBuffer<?>) - Method in interface org.apache.spark.streaming.receiver.BlockGeneratorListener
Called when a new block is ready to be pushed.
onQueryProgress(StreamingQueryListener.QueryProgressEvent) - Method in class org.apache.spark.sql.streaming.StreamingQueryListener
Called when there is some status update (ingestion rate updated, etc.)
onQueryStarted(StreamingQueryListener.QueryStartedEvent) - Method in class org.apache.spark.sql.streaming.StreamingQueryListener
Called when a query is started.
onQueryTerminated(StreamingQueryListener.QueryTerminatedEvent) - Method in class org.apache.spark.sql.streaming.StreamingQueryListener
Called when a query is stopped, with or without error.
onReceiverError(JavaStreamingListenerReceiverError) - Method in interface org.apache.spark.streaming.api.java.PythonStreamingListener
Called when a receiver has reported an error
onReceiverError(StreamingListenerReceiverError) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
Called when a receiver has reported an error
onReceiverStarted(JavaStreamingListenerReceiverStarted) - Method in interface org.apache.spark.streaming.api.java.PythonStreamingListener
Called when a receiver has been started
onReceiverStarted(StreamingListenerReceiverStarted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
Called when a receiver has been started
onReceiverStopped(JavaStreamingListenerReceiverStopped) - Method in interface org.apache.spark.streaming.api.java.PythonStreamingListener
Called when a receiver has been stopped
onReceiverStopped(StreamingListenerReceiverStopped) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
Called when a receiver has been stopped
onSpeculativeTaskSubmitted(SparkListenerSpeculativeTaskSubmitted) - Method in class org.apache.spark.scheduler.SparkListener
 
onSpeculativeTaskSubmitted(SparkListenerSpeculativeTaskSubmitted) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when a speculative task is submitted
onSpeculativeTaskSubmitted(SparkListenerSpeculativeTaskSubmitted) - Method in class org.apache.spark.SparkFirehoseListener
 
onStageCompleted(SparkListenerStageCompleted) - Method in class org.apache.spark.scheduler.SparkListener
 
onStageCompleted(SparkListenerStageCompleted) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when a stage completes successfully or fails, with information on the completed stage.
onStageCompleted(SparkListenerStageCompleted) - Method in class org.apache.spark.scheduler.StatsReportListener
 
onStageCompleted(SparkListenerStageCompleted) - Method in class org.apache.spark.SparkFirehoseListener
 
onStageCompleted(SparkListenerStageCompleted) - Method in class org.apache.spark.SpillListener
 
onStageSubmitted(SparkListenerStageSubmitted) - Method in class org.apache.spark.scheduler.SparkListener
 
onStageSubmitted(SparkListenerStageSubmitted) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when a stage is submitted
onStageSubmitted(SparkListenerStageSubmitted) - Method in class org.apache.spark.SparkFirehoseListener
 
OnStart - Class in org.apache.spark.rpc.netty
 
OnStart() - Constructor for class org.apache.spark.rpc.netty.OnStart
 
onStart() - Method in interface org.apache.spark.rpc.RpcEndpoint
Invoked before RpcEndpoint starts to handle any message.
onStart() - Method in class org.apache.spark.streaming.receiver.Receiver
This method is called by the system when the receiver is started.
OnStop - Class in org.apache.spark.rpc.netty
 
OnStop() - Constructor for class org.apache.spark.rpc.netty.OnStop
 
onStop() - Method in interface org.apache.spark.rpc.RpcEndpoint
Invoked when RpcEndpoint is stopping.
onStop() - Method in class org.apache.spark.streaming.receiver.Receiver
This method is called by the system when the receiver is stopped.
onStreamingStarted(JavaStreamingListenerStreamingStarted) - Method in interface org.apache.spark.streaming.api.java.PythonStreamingListener
Called when the streaming has been started
onStreamingStarted(StreamingListenerStreamingStarted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
Called when the streaming has been started
onSuccess(String, QueryExecution, long) - Method in interface org.apache.spark.sql.util.QueryExecutionListener
A callback function that will be called when a query executed successfully.
onTaskCommit(FileCommitProtocol.TaskCommitMessage) - Method in class org.apache.spark.internal.io.FileCommitProtocol
Called on the driver after a task commits.
onTaskCompletion(TaskContext) - Method in interface org.apache.spark.util.TaskCompletionListener
 
onTaskEnd(SparkListenerTaskEnd) - Method in class org.apache.spark.scheduler.SparkListener
 
onTaskEnd(SparkListenerTaskEnd) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when a task ends
onTaskEnd(SparkListenerTaskEnd) - Method in class org.apache.spark.scheduler.StatsReportListener
 
onTaskEnd(SparkListenerTaskEnd) - Method in class org.apache.spark.SparkFirehoseListener
 
onTaskEnd(SparkListenerTaskEnd) - Method in class org.apache.spark.SpillListener
 
onTaskFailure(TaskContext, Throwable) - Method in interface org.apache.spark.util.TaskFailureListener
 
onTaskGettingResult(SparkListenerTaskGettingResult) - Method in class org.apache.spark.scheduler.SparkListener
 
onTaskGettingResult(SparkListenerTaskGettingResult) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when a task begins remotely fetching its result (will not be called for tasks that do not need to fetch the result remotely).
onTaskGettingResult(SparkListenerTaskGettingResult) - Method in class org.apache.spark.SparkFirehoseListener
 
onTaskStart(SparkListenerTaskStart) - Method in class org.apache.spark.scheduler.SparkListener
 
onTaskStart(SparkListenerTaskStart) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when a task starts
onTaskStart(SparkListenerTaskStart) - Method in class org.apache.spark.SparkFirehoseListener
 
onUnpersistRDD(SparkListenerUnpersistRDD) - Method in class org.apache.spark.scheduler.SparkListener
 
onUnpersistRDD(SparkListenerUnpersistRDD) - Method in interface org.apache.spark.scheduler.SparkListenerInterface
Called when an RDD is manually unpersisted by the application
onUnpersistRDD(SparkListenerUnpersistRDD) - Method in class org.apache.spark.SparkFirehoseListener
 
OOM() - Static method in class org.apache.spark.util.SparkExitCode
The default uncaught exception handler was reached, and the uncaught exception was an
open() - Method in class org.apache.spark.input.PortableDataStream
Create a new DataInputStream from the split and context.
open(long, long) - Method in class org.apache.spark.sql.ForeachWriter
Called when starting to process one partition of new data in the executor.
open(File, M, ClassTag<M>) - Static method in class org.apache.spark.status.KVUtils
Open or create a LevelDB store.
ops() - Method in class org.apache.spark.graphx.Graph
The associated GraphOps object.
opt(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
optimize(RDD<Tuple2<Object, Vector>>, Vector) - Method in class org.apache.spark.mllib.optimization.GradientDescent
:: DeveloperApi :: Runs gradient descent on the given training data.
optimize(RDD<Tuple2<Object, Vector>>, Vector) - Method in class org.apache.spark.mllib.optimization.LBFGS
 
optimize(RDD<Tuple2<Object, Vector>>, Vector) - Method in interface org.apache.spark.mllib.optimization.Optimizer
Solve the provided convex optimization problem.
optimizeDocConcentration() - Method in interface org.apache.spark.ml.clustering.LDAParams
For Online optimizer only (currently): optimizer = "online".
optimizer() - Method in interface org.apache.spark.ml.clustering.LDAParams
Optimizer or inference algorithm used to estimate the LDA model.
optimizer() - Method in class org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
 
optimizer() - Method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
 
optimizer() - Method in class org.apache.spark.mllib.classification.SVMWithSGD
 
Optimizer - Interface in org.apache.spark.mllib.optimization
:: DeveloperApi :: Trait for optimization problem solvers.
optimizer() - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
The optimizer to solve the problem.
optimizer() - Method in class org.apache.spark.mllib.regression.LassoWithSGD
 
optimizer() - Method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
 
optimizer() - Method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
 
option(String, String) - Method in class org.apache.spark.ml.util.MLWriter
Adds an option to the underlying MLWriter.
option(String, String) - Method in class org.apache.spark.sql.DataFrameReader
Adds an input option for the underlying data source.
option(String, boolean) - Method in class org.apache.spark.sql.DataFrameReader
Adds an input option for the underlying data source.
option(String, long) - Method in class org.apache.spark.sql.DataFrameReader
Adds an input option for the underlying data source.
option(String, double) - Method in class org.apache.spark.sql.DataFrameReader
Adds an input option for the underlying data source.
option(String, String) - Method in class org.apache.spark.sql.DataFrameWriter
Adds an output option for the underlying data source.
option(String, boolean) - Method in class org.apache.spark.sql.DataFrameWriter
Adds an output option for the underlying data source.
option(String, long) - Method in class org.apache.spark.sql.DataFrameWriter
Adds an output option for the underlying data source.
option(String, double) - Method in class org.apache.spark.sql.DataFrameWriter
Adds an output option for the underlying data source.
option(String, String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Adds an input option for the underlying data source.
option(String, boolean) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Adds an input option for the underlying data source.
option(String, long) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Adds an input option for the underlying data source.
option(String, double) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Adds an input option for the underlying data source.
option(String, String) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Adds an output option for the underlying data source.
option(String, boolean) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Adds an output option for the underlying data source.
option(String, long) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Adds an output option for the underlying data source.
option(String, double) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Adds an output option for the underlying data source.
Optional<T> - Class in org.apache.spark.api.java
Like java.util.Optional in Java 8, scala.Option in Scala, and com.google.common.base.Optional in Google Guava, this class represents a value of a given type that may or may not exist.
options(Map<String, String>) - Method in class org.apache.spark.sql.DataFrameReader
(Scala-specific) Adds input options for the underlying data source.
options(Map<String, String>) - Method in class org.apache.spark.sql.DataFrameReader
Adds input options for the underlying data source.
options(Map<String, String>) - Method in class org.apache.spark.sql.DataFrameWriter
(Scala-specific) Adds output options for the underlying data source.
options(Map<String, String>) - Method in class org.apache.spark.sql.DataFrameWriter
Adds output options for the underlying data source.
options(Map<String, String>) - Method in class org.apache.spark.sql.streaming.DataStreamReader
(Scala-specific) Adds input options for the underlying data source.
options(Map<String, String>) - Method in class org.apache.spark.sql.streaming.DataStreamReader
(Java-specific) Adds input options for the underlying data source.
options(Map<String, String>) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
(Scala-specific) Adds output options for the underlying data source.
options(Map<String, String>) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Adds output options for the underlying data source.
optionSparkSession() - Method in interface org.apache.spark.ml.util.BaseReadWrite
 
optionToOptional(Option<T>) - Static method in class org.apache.spark.api.java.JavaUtils
 
or(T) - Method in class org.apache.spark.api.java.Optional
 
or(Column) - Method in class org.apache.spark.sql.Column
Boolean OR.
Or - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff at least one of left or right evaluates to true.
Or(Filter, Filter) - Constructor for class org.apache.spark.sql.sources.Or
 
OracleDialect - Class in org.apache.spark.sql.jdbc
 
OracleDialect() - Constructor for class org.apache.spark.sql.jdbc.OracleDialect
 
orc(String...) - Method in class org.apache.spark.sql.DataFrameReader
Loads ORC files and returns the result as a DataFrame.
orc(String) - Method in class org.apache.spark.sql.DataFrameReader
Loads an ORC file and returns the result as a DataFrame.
orc(Seq<String>) - Method in class org.apache.spark.sql.DataFrameReader
Loads ORC files and returns the result as a DataFrame.
orc(String) - Method in class org.apache.spark.sql.DataFrameWriter
Saves the content of the DataFrame in ORC format at the specified path.
orc(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Loads a ORC file stream, returning the result as a DataFrame.
OrcFileFormat - Class in org.apache.spark.sql.hive.orc
FileFormat for reading ORC files.
OrcFileFormat() - Constructor for class org.apache.spark.sql.hive.orc.OrcFileFormat
 
OrcFileOperator - Class in org.apache.spark.sql.hive.orc
 
OrcFileOperator() - Constructor for class org.apache.spark.sql.hive.orc.OrcFileOperator
 
OrcFilters - Class in org.apache.spark.sql.hive.orc
Helper object for building ORC SearchArguments, which are used for ORC predicate push-down.
OrcFilters() - Constructor for class org.apache.spark.sql.hive.orc.OrcFilters
 
orderBy(String, String...) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset sorted by the given expressions.
orderBy(Column...) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset sorted by the given expressions.
orderBy(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset sorted by the given expressions.
orderBy(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset sorted by the given expressions.
orderBy(String, String...) - Static method in class org.apache.spark.sql.expressions.Window
Creates a WindowSpec with the ordering defined.
orderBy(Column...) - Static method in class org.apache.spark.sql.expressions.Window
Creates a WindowSpec with the ordering defined.
orderBy(String, Seq<String>) - Static method in class org.apache.spark.sql.expressions.Window
Creates a WindowSpec with the ordering defined.
orderBy(Seq<Column>) - Static method in class org.apache.spark.sql.expressions.Window
Creates a WindowSpec with the ordering defined.
orderBy(String, String...) - Method in class org.apache.spark.sql.expressions.WindowSpec
Defines the ordering columns in a WindowSpec.
orderBy(Column...) - Method in class org.apache.spark.sql.expressions.WindowSpec
Defines the ordering columns in a WindowSpec.
orderBy(String, Seq<String>) - Method in class org.apache.spark.sql.expressions.WindowSpec
Defines the ordering columns in a WindowSpec.
orderBy(Seq<Column>) - Method in class org.apache.spark.sql.expressions.WindowSpec
Defines the ordering columns in a WindowSpec.
OrderedRDDFunctions<K,V,P extends scala.Product2<K,V>> - Class in org.apache.spark.rdd
Extra functions available on RDDs of (key, value) pairs where the key is sortable through an implicit conversion.
OrderedRDDFunctions(RDD<P>, Ordering<K>, ClassTag<K>, ClassTag<V>, ClassTag<P>) - Constructor for class org.apache.spark.rdd.OrderedRDDFunctions
 
ordering() - Static method in class org.apache.spark.streaming.Time
 
ORDINAL() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
 
orElse(T) - Method in class org.apache.spark.api.java.Optional
 
org.apache.spark - package org.apache.spark
Core Spark classes in Scala.
org.apache.spark.api.java - package org.apache.spark.api.java
Spark Java programming APIs.
org.apache.spark.api.java.function - package org.apache.spark.api.java.function
Set of interfaces to represent functions in Spark's Java API.
org.apache.spark.api.r - package org.apache.spark.api.r
 
org.apache.spark.broadcast - package org.apache.spark.broadcast
Spark's broadcast variables, used to broadcast immutable datasets to all nodes.
org.apache.spark.graphx - package org.apache.spark.graphx
ALPHA COMPONENT GraphX is a graph processing framework built on top of Spark.
org.apache.spark.graphx.impl - package org.apache.spark.graphx.impl
 
org.apache.spark.graphx.lib - package org.apache.spark.graphx.lib
Various analytics functions for graphs.
org.apache.spark.graphx.util - package org.apache.spark.graphx.util
Collections of utilities used by graphx.
org.apache.spark.input - package org.apache.spark.input
 
org.apache.spark.internal - package org.apache.spark.internal
 
org.apache.spark.internal.config - package org.apache.spark.internal.config
 
org.apache.spark.internal.io - package org.apache.spark.internal.io
 
org.apache.spark.io - package org.apache.spark.io
IO codecs used for compression.
org.apache.spark.launcher - package org.apache.spark.launcher
Library for launching Spark applications programmatically.
org.apache.spark.mapred - package org.apache.spark.mapred
 
org.apache.spark.metrics.sink - package org.apache.spark.metrics.sink
 
org.apache.spark.metrics.source - package org.apache.spark.metrics.source
 
org.apache.spark.ml - package org.apache.spark.ml
DataFrame-based machine learning APIs to let users quickly assemble and configure practical machine learning pipelines.
org.apache.spark.ml.ann - package org.apache.spark.ml.ann
 
org.apache.spark.ml.attribute - package org.apache.spark.ml.attribute
ML attributes
org.apache.spark.ml.classification - package org.apache.spark.ml.classification
 
org.apache.spark.ml.clustering - package org.apache.spark.ml.clustering
 
org.apache.spark.ml.evaluation - package org.apache.spark.ml.evaluation
 
org.apache.spark.ml.feature - package org.apache.spark.ml.feature
Feature transformers The `ml.feature` package provides common feature transformers that help convert raw data or features into more suitable forms for model fitting.
org.apache.spark.ml.fpm - package org.apache.spark.ml.fpm
 
org.apache.spark.ml.image - package org.apache.spark.ml.image
 
org.apache.spark.ml.impl - package org.apache.spark.ml.impl
 
org.apache.spark.ml.linalg - package org.apache.spark.ml.linalg
 
org.apache.spark.ml.optim - package org.apache.spark.ml.optim
 
org.apache.spark.ml.optim.aggregator - package org.apache.spark.ml.optim.aggregator
 
org.apache.spark.ml.optim.loss - package org.apache.spark.ml.optim.loss
 
org.apache.spark.ml.param - package org.apache.spark.ml.param
 
org.apache.spark.ml.param.shared - package org.apache.spark.ml.param.shared
 
org.apache.spark.ml.r - package org.apache.spark.ml.r
 
org.apache.spark.ml.recommendation - package org.apache.spark.ml.recommendation
 
org.apache.spark.ml.regression - package org.apache.spark.ml.regression
 
org.apache.spark.ml.source.image - package org.apache.spark.ml.source.image
 
org.apache.spark.ml.source.libsvm - package org.apache.spark.ml.source.libsvm
 
org.apache.spark.ml.stat - package org.apache.spark.ml.stat
 
org.apache.spark.ml.stat.distribution - package org.apache.spark.ml.stat.distribution
 
org.apache.spark.ml.tree - package org.apache.spark.ml.tree
 
org.apache.spark.ml.tree.impl - package org.apache.spark.ml.tree.impl
 
org.apache.spark.ml.tuning - package org.apache.spark.ml.tuning
 
org.apache.spark.ml.util - package org.apache.spark.ml.util
 
org.apache.spark.mllib - package org.apache.spark.mllib
RDD-based machine learning APIs (in maintenance mode).
org.apache.spark.mllib.classification - package org.apache.spark.mllib.classification
 
org.apache.spark.mllib.classification.impl - package org.apache.spark.mllib.classification.impl
 
org.apache.spark.mllib.clustering - package org.apache.spark.mllib.clustering
 
org.apache.spark.mllib.evaluation - package org.apache.spark.mllib.evaluation
 
org.apache.spark.mllib.evaluation.binary - package org.apache.spark.mllib.evaluation.binary
 
org.apache.spark.mllib.feature - package org.apache.spark.mllib.feature
 
org.apache.spark.mllib.fpm - package org.apache.spark.mllib.fpm
 
org.apache.spark.mllib.linalg - package org.apache.spark.mllib.linalg
 
org.apache.spark.mllib.linalg.distributed - package org.apache.spark.mllib.linalg.distributed
 
org.apache.spark.mllib.optimization - package org.apache.spark.mllib.optimization
 
org.apache.spark.mllib.pmml - package org.apache.spark.mllib.pmml
 
org.apache.spark.mllib.pmml.export - package org.apache.spark.mllib.pmml.export
 
org.apache.spark.mllib.random - package org.apache.spark.mllib.random
 
org.apache.spark.mllib.rdd - package org.apache.spark.mllib.rdd
 
org.apache.spark.mllib.recommendation - package org.apache.spark.mllib.recommendation
 
org.apache.spark.mllib.regression - package org.apache.spark.mllib.regression
 
org.apache.spark.mllib.regression.impl - package org.apache.spark.mllib.regression.impl
 
org.apache.spark.mllib.stat - package org.apache.spark.mllib.stat
 
org.apache.spark.mllib.stat.correlation - package org.apache.spark.mllib.stat.correlation
 
org.apache.spark.mllib.stat.distribution - package org.apache.spark.mllib.stat.distribution
 
org.apache.spark.mllib.stat.test - package org.apache.spark.mllib.stat.test
 
org.apache.spark.mllib.tree - package org.apache.spark.mllib.tree
 
org.apache.spark.mllib.tree.configuration - package org.apache.spark.mllib.tree.configuration
 
org.apache.spark.mllib.tree.impurity - package org.apache.spark.mllib.tree.impurity
 
org.apache.spark.mllib.tree.loss - package org.apache.spark.mllib.tree.loss
 
org.apache.spark.mllib.tree.model - package org.apache.spark.mllib.tree.model
 
org.apache.spark.mllib.util - package org.apache.spark.mllib.util
 
org.apache.spark.partial - package org.apache.spark.partial
 
org.apache.spark.rdd - package org.apache.spark.rdd
Provides implementation's of various RDDs.
org.apache.spark.rpc - package org.apache.spark.rpc
 
org.apache.spark.rpc.netty - package org.apache.spark.rpc.netty
 
org.apache.spark.scheduler - package org.apache.spark.scheduler
Spark's DAG scheduler.
org.apache.spark.scheduler.cluster - package org.apache.spark.scheduler.cluster
 
org.apache.spark.scheduler.local - package org.apache.spark.scheduler.local
 
org.apache.spark.security - package org.apache.spark.security
 
org.apache.spark.serializer - package org.apache.spark.serializer
Pluggable serializers for RDD and shuffle data.
org.apache.spark.sql - package org.apache.spark.sql
 
org.apache.spark.sql.api.java - package org.apache.spark.sql.api.java
Allows the execution of relational queries, including those expressed in SQL using Spark.
org.apache.spark.sql.api.r - package org.apache.spark.sql.api.r
 
org.apache.spark.sql.catalog - package org.apache.spark.sql.catalog
 
org.apache.spark.sql.expressions - package org.apache.spark.sql.expressions
 
org.apache.spark.sql.expressions.javalang - package org.apache.spark.sql.expressions.javalang
 
org.apache.spark.sql.expressions.scalalang - package org.apache.spark.sql.expressions.scalalang
 
org.apache.spark.sql.hive - package org.apache.spark.sql.hive
 
org.apache.spark.sql.hive.client - package org.apache.spark.sql.hive.client
 
org.apache.spark.sql.hive.execution - package org.apache.spark.sql.hive.execution
 
org.apache.spark.sql.hive.orc - package org.apache.spark.sql.hive.orc
 
org.apache.spark.sql.jdbc - package org.apache.spark.sql.jdbc
 
org.apache.spark.sql.sources - package org.apache.spark.sql.sources
 
org.apache.spark.sql.sources.v2 - package org.apache.spark.sql.sources.v2
 
org.apache.spark.sql.sources.v2.reader - package org.apache.spark.sql.sources.v2.reader
 
org.apache.spark.sql.sources.v2.reader.partitioning - package org.apache.spark.sql.sources.v2.reader.partitioning
 
org.apache.spark.sql.sources.v2.reader.streaming - package org.apache.spark.sql.sources.v2.reader.streaming
 
org.apache.spark.sql.sources.v2.writer - package org.apache.spark.sql.sources.v2.writer
 
org.apache.spark.sql.sources.v2.writer.streaming - package org.apache.spark.sql.sources.v2.writer.streaming
 
org.apache.spark.sql.streaming - package org.apache.spark.sql.streaming
 
org.apache.spark.sql.types - package org.apache.spark.sql.types
 
org.apache.spark.sql.util - package org.apache.spark.sql.util
 
org.apache.spark.sql.vectorized - package org.apache.spark.sql.vectorized
 
org.apache.spark.status - package org.apache.spark.status
 
org.apache.spark.status.api.v1 - package org.apache.spark.status.api.v1
 
org.apache.spark.status.api.v1.streaming - package org.apache.spark.status.api.v1.streaming
 
org.apache.spark.storage - package org.apache.spark.storage
 
org.apache.spark.storage.memory - package org.apache.spark.storage.memory
 
org.apache.spark.streaming - package org.apache.spark.streaming
 
org.apache.spark.streaming.api.java - package org.apache.spark.streaming.api.java
Java APIs for spark streaming.
org.apache.spark.streaming.dstream - package org.apache.spark.streaming.dstream
Various implementations of DStreams.
org.apache.spark.streaming.kinesis - package org.apache.spark.streaming.kinesis
 
org.apache.spark.streaming.receiver - package org.apache.spark.streaming.receiver
 
org.apache.spark.streaming.scheduler - package org.apache.spark.streaming.scheduler
 
org.apache.spark.streaming.scheduler.rate - package org.apache.spark.streaming.scheduler.rate
 
org.apache.spark.streaming.ui - package org.apache.spark.streaming.ui
 
org.apache.spark.streaming.util - package org.apache.spark.streaming.util
 
org.apache.spark.ui - package org.apache.spark.ui
 
org.apache.spark.ui.jobs - package org.apache.spark.ui.jobs
 
org.apache.spark.ui.storage - package org.apache.spark.ui.storage
 
org.apache.spark.util - package org.apache.spark.util
Spark utilities.
org.apache.spark.util.logging - package org.apache.spark.util.logging
 
org.apache.spark.util.random - package org.apache.spark.util.random
Utilities for random number generation.
org.apache.spark.util.sketch - package org.apache.spark.util.sketch
 
original() - Method in interface org.apache.spark.security.CryptoStreamUtils.BaseErrorHandler
The underlying stream that is being wrapped by the encrypted stream, so that it can be closed even if there's an error in the crypto layer.
originalMax() - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
 
originalMin() - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
 
orNull() - Method in class org.apache.spark.api.java.Optional
 
other() - Method in class org.apache.spark.scheduler.RuntimePercentage
 
otherVertexAttr(long) - Method in class org.apache.spark.graphx.EdgeTriplet
Given one vertex in the edge return the other vertex.
otherVertexId(long) - Method in class org.apache.spark.graphx.Edge
Given one vertex in the edge return the other vertex.
otherwise(Object) - Method in class org.apache.spark.sql.Column
Evaluates a list of conditions and returns one of multiple possible result expressions.
Out() - Static method in class org.apache.spark.graphx.EdgeDirection
Edges originating from a vertex.
OutboxMessage - Interface in org.apache.spark.rpc.netty
 
outDegrees() - Method in class org.apache.spark.graphx.GraphOps
The out-degree of each vertex in the graph.
outerJoinVertices(RDD<Tuple2<Object, U>>, Function3<Object, VD, Option<U>, VD2>, ClassTag<U>, ClassTag<VD2>, Predef.$eq$colon$eq<VD, VD2>) - Method in class org.apache.spark.graphx.Graph
Joins the vertices with entries in the table RDD and merges the results using mapFunc.
outerJoinVertices(RDD<Tuple2<Object, U>>, Function3<Object, VD, Option<U>, VD2>, ClassTag<U>, ClassTag<VD2>, Predef.$eq$colon$eq<VD, VD2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
 
output() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
 
OUTPUT() - Static method in class org.apache.spark.ui.ToolTips
 
output$() - Constructor for class org.apache.spark.InternalAccumulator.output$
 
OUTPUT_FORMAT() - Static method in class org.apache.spark.sql.hive.execution.HiveOptions
 
OUTPUT_METRICS_PREFIX() - Static method in class org.apache.spark.InternalAccumulator
 
OUTPUT_RECORDS() - Static method in class org.apache.spark.status.TaskIndexNames
 
OUTPUT_SIZE() - Static method in class org.apache.spark.status.TaskIndexNames
 
outputBytes() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
outputBytes() - Method in class org.apache.spark.status.api.v1.StageData
 
outputCol() - Method in interface org.apache.spark.ml.param.shared.HasOutputCol
Param for output column name.
outputCols() - Method in interface org.apache.spark.ml.param.shared.HasOutputCols
Param for output column names.
outputColumnNames() - Method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
 
outputColumnNames() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
 
outputColumnNames() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
 
OutputCommitCoordinationMessage - Interface in org.apache.spark.scheduler
 
outputCommitCoordinator() - Method in class org.apache.spark.SparkEnv
 
outputEncoder() - Method in class org.apache.spark.sql.expressions.Aggregator
Specifies the Encoder for the final output value type.
outputFormat() - Method in class org.apache.spark.sql.hive.execution.HiveOptions
 
OutputMetricDistributions - Class in org.apache.spark.status.api.v1
 
OutputMetrics - Class in org.apache.spark.status.api.v1
 
outputMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
outputMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 
outputMode(OutputMode) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Specifies how data of a streaming DataFrame/Dataset is written to a streaming sink.
outputMode(String) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Specifies how data of a streaming DataFrame/Dataset is written to a streaming sink.
OutputMode - Class in org.apache.spark.sql.streaming
OutputMode describes what data will be written to a streaming sink when there is new data available in a streaming DataFrame/Dataset.
OutputMode() - Constructor for class org.apache.spark.sql.streaming.OutputMode
 
OutputOperationInfo - Class in org.apache.spark.status.api.v1.streaming
 
OutputOperationInfo - Class in org.apache.spark.streaming.scheduler
:: DeveloperApi :: Class having information on output operations.
OutputOperationInfo(Time, int, String, String, Option<Object>, Option<Object>, Option<String>) - Constructor for class org.apache.spark.streaming.scheduler.OutputOperationInfo
 
outputOperationInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationCompleted
 
outputOperationInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationStarted
 
outputOperationInfos() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
 
outputOpId() - Method in class org.apache.spark.status.api.v1.streaming.OutputOperationInfo
 
outputPartitioning() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
 
outputPartitioning() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsReportPartitioning
Returns the output data partitioning that this reader guarantees.
outputRecords() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
outputRecords() - Method in class org.apache.spark.status.api.v1.StageData
 
outputRowFormat() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
outputRowFormatMap() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
outputSerdeClass() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
outputSerdeProps() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
over(WindowSpec) - Method in class org.apache.spark.sql.Column
Defines a windowing column.
over() - Method in class org.apache.spark.sql.Column
Defines an empty analytic clause.
overallScore(Dataset<Row>, Column) - Static method in class org.apache.spark.ml.evaluation.CosineSilhouette
 
overallScore(Dataset<Row>, Column) - Static method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette
 
overwrite() - Method in class org.apache.spark.ml.util.MLWriter
Overwrites if the output path already exists.
overwrite() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
 
overwrite() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
 

P

p() - Method in class org.apache.spark.ml.feature.Normalizer
Normalization in L^p^ space.
PagedTable<T> - Interface in org.apache.spark.ui
A paged table that will generate a HTML table for a specified page and also the page navigation.
pageLink(int) - Method in interface org.apache.spark.ui.PagedTable
Return a link to jump to a page.
pageNavigation(int, int, int) - Method in interface org.apache.spark.ui.PagedTable
Return a page navigation.
pageNumberFormField() - Method in interface org.apache.spark.ui.PagedTable
 
pageRank(double, double) - Method in class org.apache.spark.graphx.GraphOps
Run a dynamic version of PageRank returning a graph with vertex attributes containing the PageRank and edge attributes containing the normalized edge weight.
PageRank - Class in org.apache.spark.graphx.lib
PageRank algorithm implementation.
PageRank() - Constructor for class org.apache.spark.graphx.lib.PageRank
 
pageSizeFormField() - Method in interface org.apache.spark.ui.PagedTable
 
PairDStreamFunctions<K,V> - Class in org.apache.spark.streaming.dstream
Extra functions available on DStream of (key, value) pairs through an implicit conversion.
PairDStreamFunctions(DStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>, Ordering<K>) - Constructor for class org.apache.spark.streaming.dstream.PairDStreamFunctions
 
PairFlatMapFunction<T,K,V> - Interface in org.apache.spark.api.java.function
A function that returns zero or more key-value pair records from each input record.
PairFunction<T,K,V> - Interface in org.apache.spark.api.java.function
A function that returns key-value pairs (Tuple2<K, V>), and can be used to construct PairRDDs.
PairRDDFunctions<K,V> - Class in org.apache.spark.rdd
Extra functions available on RDDs of (key, value) pairs through an implicit conversion.
PairRDDFunctions(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>, Ordering<K>) - Constructor for class org.apache.spark.rdd.PairRDDFunctions
 
PairwiseRRDD<T> - Class in org.apache.spark.api.r
Form an RDD[(Int, Array[Byte])] from key-value pairs returned from R.
PairwiseRRDD(RDD<T>, int, byte[], String, byte[], Object[], ClassTag<T>) - Constructor for class org.apache.spark.api.r.PairwiseRRDD
 
parallelism() - Method in interface org.apache.spark.ml.param.shared.HasParallelism
The number of threads to use when running parallel algorithms.
parallelize(List<T>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
Distribute a local Scala collection to form an RDD.
parallelize(List<T>) - Method in class org.apache.spark.api.java.JavaSparkContext
Distribute a local Scala collection to form an RDD.
parallelize(Seq<T>, int, ClassTag<T>) - Method in class org.apache.spark.SparkContext
Distribute a local Scala collection to form an RDD.
parallelizeDoubles(List<Double>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
Distribute a local Scala collection to form an RDD.
parallelizeDoubles(List<Double>) - Method in class org.apache.spark.api.java.JavaSparkContext
Distribute a local Scala collection to form an RDD.
parallelizePairs(List<Tuple2<K, V>>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
Distribute a local Scala collection to form an RDD.
parallelizePairs(List<Tuple2<K, V>>) - Method in class org.apache.spark.api.java.JavaSparkContext
Distribute a local Scala collection to form an RDD.
Param<T> - Class in org.apache.spark.ml.param
:: DeveloperApi :: A param with self-contained documentation and optionally default value.
Param(String, String, String, Function1<T, Object>) - Constructor for class org.apache.spark.ml.param.Param
 
Param(Identifiable, String, String, Function1<T, Object>) - Constructor for class org.apache.spark.ml.param.Param
 
Param(String, String, String) - Constructor for class org.apache.spark.ml.param.Param
 
Param(Identifiable, String, String) - Constructor for class org.apache.spark.ml.param.Param
 
param() - Method in class org.apache.spark.ml.param.ParamPair
 
ParamGridBuilder - Class in org.apache.spark.ml.tuning
Builder for a param grid used in grid search-based model selection.
ParamGridBuilder() - Constructor for class org.apache.spark.ml.tuning.ParamGridBuilder
 
ParamMap - Class in org.apache.spark.ml.param
A param to value map.
ParamMap() - Constructor for class org.apache.spark.ml.param.ParamMap
Creates an empty param map.
paramMap() - Method in interface org.apache.spark.ml.param.Params
Internal param map for user-supplied values.
ParamPair<T> - Class in org.apache.spark.ml.param
A param and its value.
ParamPair(Param<T>, T) - Constructor for class org.apache.spark.ml.param.ParamPair
 
Params - Interface in org.apache.spark.ml.param
:: DeveloperApi :: Trait for components that take parameters.
params() - Method in interface org.apache.spark.ml.param.Params
Returns all params sorted by their names.
ParamValidators - Class in org.apache.spark.ml.param
:: DeveloperApi :: Factory methods for common validation functions for Param.isValid.
ParamValidators() - Constructor for class org.apache.spark.ml.param.ParamValidators
 
parent() - Method in class org.apache.spark.ml.Model
The parent estimator that produced this model.
parent() - Method in class org.apache.spark.ml.param.Param
 
parent() - Method in interface org.apache.spark.scheduler.Schedulable
 
ParentClassLoader - Class in org.apache.spark.util
A class loader which makes some protected methods in ClassLoader accessible.
ParentClassLoader(ClassLoader) - Constructor for class org.apache.spark.util.ParentClassLoader
 
parentIds() - Method in class org.apache.spark.scheduler.StageInfo
 
parentIds() - Method in class org.apache.spark.storage.RDDInfo
 
parentIndex(int) - Static method in class org.apache.spark.mllib.tree.model.Node
Get the parent index of the given node, or 0 if it is the root.
parmap(Col, String, int, Function1<I, O>, CanBuildFrom<Col, Future<O>, Col>, CanBuildFrom<Col, O, Col>) - Static method in class org.apache.spark.util.ThreadUtils
Transforms input collection by applying the given function to each element in parallel fashion.
parquet(String...) - Method in class org.apache.spark.sql.DataFrameReader
Loads a Parquet file, returning the result as a DataFrame.
parquet(String) - Method in class org.apache.spark.sql.DataFrameReader
Loads a Parquet file, returning the result as a DataFrame.
parquet(Seq<String>) - Method in class org.apache.spark.sql.DataFrameReader
Loads a Parquet file, returning the result as a DataFrame.
parquet(String) - Method in class org.apache.spark.sql.DataFrameWriter
Saves the content of the DataFrame in Parquet format at the specified path.
parquet(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Loads a Parquet file stream, returning the result as a DataFrame.
parquetFile(String...) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
As of 1.4.0, replaced by read().parquet().
parquetFile(Seq<String>) - Method in class org.apache.spark.sql.SQLContext
Deprecated.
Use read.parquet() instead. Since 1.4.0.
parse(String) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
parse(String) - Static method in class org.apache.spark.mllib.linalg.Vectors
Parses a string resulted from Vector.toString into a Vector.
parse(String) - Static method in class org.apache.spark.mllib.regression.LabeledPoint
Parses a string resulted from LabeledPoint#toString into an LabeledPoint.
parse(String) - Static method in class org.apache.spark.mllib.util.NumericParser
Parses a string into a Double, an Array[Double], or a Seq[Any].
parseAll(Parsers.Parser<T>, Reader<Object>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
parseAll(Parsers.Parser<T>, Reader) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
parseAll(Parsers.Parser<T>, CharSequence) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
parseHostPort(String) - Static method in class org.apache.spark.util.Utils
 
parseIgnoreCase(Class<E>, String) - Static method in class org.apache.spark.util.EnumUtil
 
Parser(Function1<Reader<Object>, Parsers.ParseResult<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
parseStandaloneMasterUrls(String) - Static method in class org.apache.spark.util.Utils
Split the comma delimited string of master URLs into a list.
PartialResult<R> - Class in org.apache.spark.partial
 
PartialResult(R, boolean) - Constructor for class org.apache.spark.partial.PartialResult
 
Partition - Interface in org.apache.spark
An identifier for a partition in an RDD.
partition() - Method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
 
partition() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
 
partition(String) - Method in class org.apache.spark.status.LiveRDD
 
partitionBy(Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
Return a copy of the RDD partitioned using the specified partitioner.
partitionBy(PartitionStrategy) - Method in class org.apache.spark.graphx.Graph
Repartitions the edges in the graph according to partitionStrategy.
partitionBy(PartitionStrategy, int) - Method in class org.apache.spark.graphx.Graph
Repartitions the edges in the graph according to partitionStrategy.
partitionBy(PartitionStrategy) - Method in class org.apache.spark.graphx.impl.GraphImpl
 
partitionBy(PartitionStrategy, int) - Method in class org.apache.spark.graphx.impl.GraphImpl
 
partitionBy(Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return a copy of the RDD partitioned using the specified partitioner.
partitionBy(String...) - Method in class org.apache.spark.sql.DataFrameWriter
Partitions the output by the given columns on the file system.
partitionBy(Seq<String>) - Method in class org.apache.spark.sql.DataFrameWriter
Partitions the output by the given columns on the file system.
partitionBy(String, String...) - Static method in class org.apache.spark.sql.expressions.Window
Creates a WindowSpec with the partitioning defined.
partitionBy(Column...) - Static method in class org.apache.spark.sql.expressions.Window
Creates a WindowSpec with the partitioning defined.
partitionBy(String, Seq<String>) - Static method in class org.apache.spark.sql.expressions.Window
Creates a WindowSpec with the partitioning defined.
partitionBy(Seq<Column>) - Static method in class org.apache.spark.sql.expressions.Window
Creates a WindowSpec with the partitioning defined.
partitionBy(String, String...) - Method in class org.apache.spark.sql.expressions.WindowSpec
Defines the partitioning columns in a WindowSpec.
partitionBy(Column...) - Method in class org.apache.spark.sql.expressions.WindowSpec
Defines the partitioning columns in a WindowSpec.
partitionBy(String, Seq<String>) - Method in class org.apache.spark.sql.expressions.WindowSpec
Defines the partitioning columns in a WindowSpec.
partitionBy(Seq<Column>) - Method in class org.apache.spark.sql.expressions.WindowSpec
Defines the partitioning columns in a WindowSpec.
partitionBy(String...) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Partitions the output by the given columns on the file system.
partitionBy(Seq<String>) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Partitions the output by the given columns on the file system.
PartitionCoalescer - Interface in org.apache.spark.rdd
::DeveloperApi:: A PartitionCoalescer defines how to coalesce the partitions of a given RDD.
partitioner() - Method in interface org.apache.spark.api.java.JavaRDDLike
The partitioner of this RDD.
partitioner() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
If partitionsRDD already has a partitioner, use it.
partitioner() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
Partitioner - Class in org.apache.spark
An object that defines how the elements in a key-value pair RDD are partitioned by key.
Partitioner() - Constructor for class org.apache.spark.Partitioner
 
partitioner() - Method in class org.apache.spark.rdd.CoGroupedRDD
 
partitioner() - Method in class org.apache.spark.rdd.RDD
Optionally overridden by subclasses to specify how they are partitioned.
partitioner() - Method in class org.apache.spark.rdd.ShuffledRDD
 
partitioner() - Method in class org.apache.spark.ShuffleDependency
 
partitioner(Partitioner) - Method in class org.apache.spark.streaming.StateSpec
Set the partitioner by which the state RDDs generated by mapWithState will be partitioned.
PartitionGroup - Class in org.apache.spark.rdd
::DeveloperApi:: A group of Partitions param: prefLoc preferred location for the partition group
PartitionGroup(Option<String>) - Constructor for class org.apache.spark.rdd.PartitionGroup
 
partitionId() - Method in class org.apache.spark.BarrierTaskContext
 
partitionID() - Method in class org.apache.spark.TaskCommitDenied
 
partitionId() - Method in class org.apache.spark.TaskContext
The ID of the RDD partition that is computed by this task.
Partitioning - Interface in org.apache.spark.sql.sources.v2.reader.partitioning
An interface to represent the output data partitioning for a data source, which is returned by SupportsReportPartitioning.outputPartitioning().
PartitionLocations(RDD<?>) - Constructor for class org.apache.spark.rdd.DefaultPartitionCoalescer.PartitionLocations
 
PartitionOffset - Interface in org.apache.spark.sql.sources.v2.reader.streaming
Used for per-partition offsets in continuous processing.
PartitionPruningRDD<T> - Class in org.apache.spark.rdd
:: DeveloperApi :: An RDD used to prune RDD partitions/partitions so we can avoid launching tasks on all partitions.
PartitionPruningRDD(RDD<T>, Function1<Object, Object>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.PartitionPruningRDD
 
partitions() - Method in interface org.apache.spark.api.java.JavaRDDLike
Set of partitions in this RDD.
partitions() - Method in class org.apache.spark.rdd.PartitionGroup
 
partitions() - Method in class org.apache.spark.rdd.RDD
Get the array of partitions of this RDD, taking into account whether the RDD is checkpointed or not.
partitions() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
 
partitionsRDD() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
partitionsRDD() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
PartitionStrategy - Interface in org.apache.spark.graphx
Represents the way edges are assigned to edge partitions based on their source and destination vertex IDs.
PartitionStrategy.CanonicalRandomVertexCut$ - Class in org.apache.spark.graphx
Assigns edges to partitions by hashing the source and destination vertex IDs in a canonical direction, resulting in a random vertex cut that colocates all edges between two vertices, regardless of direction.
PartitionStrategy.EdgePartition1D$ - Class in org.apache.spark.graphx
Assigns edges to partitions using only the source vertex ID, colocating edges with the same source.
PartitionStrategy.EdgePartition2D$ - Class in org.apache.spark.graphx
Assigns edges to partitions using a 2D partitioning of the sparse edge adjacency matrix, guaranteeing a 2 * sqrt(numParts) bound on vertex replication.
PartitionStrategy.RandomVertexCut$ - Class in org.apache.spark.graphx
Assigns edges to partitions by hashing the source and destination vertex IDs, resulting in a random vertex cut that colocates all same-direction edges between two vertices.
partsWithLocs() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer.PartitionLocations
 
partsWithoutLocs() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer.PartitionLocations
 
path() - Method in class org.apache.spark.scheduler.InputFormatInfo
 
path() - Method in class org.apache.spark.scheduler.SplitInfo
 
PATH_KEY - Static variable in class org.apache.spark.sql.sources.v2.DataSourceOptions
The option key for singular path.
paths() - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
Returns all the paths specified by both the singular path option and the multiple paths option.
PATHS_KEY - Static variable in class org.apache.spark.sql.sources.v2.DataSourceOptions
The option key for multiple paths.
pattern() - Method in class org.apache.spark.ml.feature.RegexTokenizer
Regex pattern used to match delimiters if gaps is true or tokens if gaps is false.
pc() - Method in class org.apache.spark.ml.feature.PCAModel
 
pc() - Method in class org.apache.spark.mllib.feature.PCAModel
 
PCA - Class in org.apache.spark.ml.feature
PCA trains a model to project vectors to a lower dimensional space of the top PCA!.k principal components.
PCA(String) - Constructor for class org.apache.spark.ml.feature.PCA
 
PCA() - Constructor for class org.apache.spark.ml.feature.PCA
 
PCA - Class in org.apache.spark.mllib.feature
A feature transformer that projects vectors to a low-dimensional space using PCA.
PCA(int) - Constructor for class org.apache.spark.mllib.feature.PCA
 
PCAModel - Class in org.apache.spark.ml.feature
Model fitted by PCA.
PCAModel - Class in org.apache.spark.mllib.feature
Model fitted by PCA that can project vectors to a low-dimensional space using PCA.
PCAParams - Interface in org.apache.spark.ml.feature
Params for PCA and PCAModel.
PCAUtil - Class in org.apache.spark.mllib.feature
 
PCAUtil() - Constructor for class org.apache.spark.mllib.feature.PCAUtil
 
pdf(Vector) - Method in class org.apache.spark.ml.stat.distribution.MultivariateGaussian
Returns density of this multivariate Gaussian at given point, x
pdf(Vector) - Method in class org.apache.spark.mllib.stat.distribution.MultivariateGaussian
Returns density of this multivariate Gaussian at given point, x
PEAK_EXECUTION_MEMORY() - Static method in class org.apache.spark.InternalAccumulator
 
PEAK_EXECUTION_MEMORY() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
 
PEAK_EXECUTION_MEMORY() - Static method in class org.apache.spark.ui.ToolTips
 
PEAK_MEM() - Static method in class org.apache.spark.status.TaskIndexNames
 
peakExecutionMemory() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
peakExecutionMemory() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 
PEARSON() - Static method in class org.apache.spark.mllib.stat.test.ChiSqTest
 
PearsonCorrelation - Class in org.apache.spark.mllib.stat.correlation
Compute Pearson correlation for two RDDs of the type RDD[Double] or the correlation matrix for an RDD of the type RDD[Vector].
PearsonCorrelation() - Constructor for class org.apache.spark.mllib.stat.correlation.PearsonCorrelation
 
percent_rank() - Static method in class org.apache.spark.sql.functions
Window function: returns the relative rank (i.e.
percentile() - Method in interface org.apache.spark.ml.feature.ChiSqSelectorParams
Percentile of features that selector will select, ordered by statistics value descending.
percentile() - Method in class org.apache.spark.mllib.feature.ChiSqSelector
 
percentiles() - Static method in class org.apache.spark.scheduler.StatsReportListener
 
percentilesHeader() - Static method in class org.apache.spark.scheduler.StatsReportListener
 
persist(StorageLevel) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Set this RDD's storage level to persist its values across operations after the first time it is computed.
persist(StorageLevel) - Method in class org.apache.spark.api.java.JavaPairRDD
Set this RDD's storage level to persist its values across operations after the first time it is computed.
persist(StorageLevel) - Method in class org.apache.spark.api.java.JavaRDD
Set this RDD's storage level to persist its values across operations after the first time it is computed.
persist(StorageLevel) - Method in class org.apache.spark.graphx.Graph
Caches the vertices and edges associated with this graph at the specified storage level, ignoring any target storage levels previously set.
persist(StorageLevel) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
Persists the edge partitions at the specified storage level, ignoring any existing target storage level.
persist(StorageLevel) - Method in class org.apache.spark.graphx.impl.GraphImpl
 
persist(StorageLevel) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
Persists the vertex partitions at the specified storage level, ignoring any existing target storage level.
persist(StorageLevel) - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
Persists the underlying RDD with the specified storage level.
persist(StorageLevel) - Method in class org.apache.spark.rdd.HadoopRDD
 
persist(StorageLevel) - Method in class org.apache.spark.rdd.NewHadoopRDD
 
persist(StorageLevel) - Method in class org.apache.spark.rdd.RDD
Set this RDD's storage level to persist its values across operations after the first time it is computed.
persist() - Method in class org.apache.spark.rdd.RDD
Persist this RDD with the default storage level (MEMORY_ONLY).
persist() - Method in class org.apache.spark.sql.Dataset
Persist this Dataset with the default storage level (MEMORY_AND_DISK).
persist(StorageLevel) - Method in class org.apache.spark.sql.Dataset
Persist this Dataset with the given storage level.
persist() - Method in class org.apache.spark.streaming.api.java.JavaDStream
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
persist(StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaDStream
Persist the RDDs of this DStream with the given storage level
persist() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
persist(StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Persist the RDDs of this DStream with the given storage level
persist(StorageLevel) - Method in class org.apache.spark.streaming.dstream.DStream
Persist the RDDs of this DStream with the given storage level
persist() - Method in class org.apache.spark.streaming.dstream.DStream
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
personalizedPageRank(long, double, double) - Method in class org.apache.spark.graphx.GraphOps
Run personalized PageRank for a given vertex, such that all random walks are started relative to the source node.
phrase(Parsers.Parser<T>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
pi() - Method in class org.apache.spark.ml.classification.NaiveBayesModel
 
pi() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
 
pi() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$.Data
 
pi() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data
 
pickBin(Partition, RDD<?>, double, DefaultPartitionCoalescer.PartitionLocations) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
Takes a parent RDD partition and decides which of the partition groups to put it in Takes locality into account, but also uses power of 2 choices to load balance It strikes a balance between the two using the balanceSlack variable
pickRandomVertex() - Method in class org.apache.spark.graphx.GraphOps
Picks a random vertex from the graph and returns its ID.
pipe(String) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return an RDD created by piping elements to a forked external process.
pipe(List<String>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return an RDD created by piping elements to a forked external process.
pipe(List<String>, Map<String, String>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return an RDD created by piping elements to a forked external process.
pipe(List<String>, Map<String, String>, boolean, int) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return an RDD created by piping elements to a forked external process.
pipe(List<String>, Map<String, String>, boolean, int, String) - Method in interface org.apache.spark.api.java.JavaRDDLike
Return an RDD created by piping elements to a forked external process.
pipe(String) - Method in class org.apache.spark.rdd.RDD
Return an RDD created by piping elements to a forked external process.
pipe(String, Map<String, String>) - Method in class org.apache.spark.rdd.RDD
Return an RDD created by piping elements to a forked external process.
pipe(Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, int, String) - Method in class org.apache.spark.rdd.RDD
Return an RDD created by piping elements to a forked external process.
Pipeline - Class in org.apache.spark.ml
A simple pipeline, which acts as an estimator.
Pipeline(String) - Constructor for class org.apache.spark.ml.Pipeline
 
Pipeline() - Constructor for class org.apache.spark.ml.Pipeline
 
Pipeline.SharedReadWrite$ - Class in org.apache.spark.ml
Methods for MLReader and MLWriter shared between Pipeline and PipelineModel
PipelineModel - Class in org.apache.spark.ml
Represents a fitted pipeline.
PipelineStage - Class in org.apache.spark.ml
:: DeveloperApi :: A stage in a pipeline, either an Estimator or a Transformer.
PipelineStage() - Constructor for class org.apache.spark.ml.PipelineStage
 
pivot(String) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Pivots a column of the current DataFrame and performs the specified aggregation.
pivot(String, Seq<Object>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Pivots a column of the current DataFrame and performs the specified aggregation.
pivot(String, List<Object>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
(Java-specific) Pivots a column of the current DataFrame and performs the specified aggregation.
pivot(Column) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Pivots a column of the current DataFrame and performs the specified aggregation.
pivot(Column, Seq<Object>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Pivots a column of the current DataFrame and performs the specified aggregation.
pivot(Column, List<Object>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
(Java-specific) Pivots a column of the current DataFrame and performs the specified aggregation.
PivotType$() - Constructor for class org.apache.spark.sql.RelationalGroupedDataset.PivotType$
 
plan() - Method in exception org.apache.spark.sql.AnalysisException
 
planBatchInputPartitions() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsScanColumnarBatch
Similar to DataSourceReader.planInputPartitions(), but returns columnar data in batches.
planInputPartitions() - Method in interface org.apache.spark.sql.sources.v2.reader.DataSourceReader
Returns a list of InputPartitions.
planInputPartitions() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsScanColumnarBatch
 
plus(Object) - Method in class org.apache.spark.sql.Column
Sum of this expression and another expression.
plus(Decimal, Decimal) - Method in interface org.apache.spark.sql.types.Decimal.DecimalIsConflicted
 
plus(Duration) - Method in class org.apache.spark.streaming.Duration
 
plus(Duration) - Method in class org.apache.spark.streaming.Time
 
pmml() - Method in interface org.apache.spark.mllib.pmml.export.PMMLModelExport
Holder of the exported model in PMML format
PMMLExportable - Interface in org.apache.spark.mllib.pmml
:: DeveloperApi :: Export model to the PMML format Predictive Model Markup Language (PMML) is an XML-based file format developed by the Data Mining Group (www.dmg.org).
PMMLKMeansModelWriter - Class in org.apache.spark.ml.clustering
A writer for KMeans that handles the "pmml" format
PMMLKMeansModelWriter() - Constructor for class org.apache.spark.ml.clustering.PMMLKMeansModelWriter
 
PMMLLinearRegressionModelWriter - Class in org.apache.spark.ml.regression
A writer for LinearRegression that handles the "pmml" format
PMMLLinearRegressionModelWriter() - Constructor for class org.apache.spark.ml.regression.PMMLLinearRegressionModelWriter
 
PMMLModelExport - Interface in org.apache.spark.mllib.pmml.export
 
PMMLModelExportFactory - Class in org.apache.spark.mllib.pmml.export
 
PMMLModelExportFactory() - Constructor for class org.apache.spark.mllib.pmml.export.PMMLModelExportFactory
 
pmod(Column, Column) - Static method in class org.apache.spark.sql.functions
Returns the positive value of dividend mod divisor.
point() - Method in class org.apache.spark.mllib.feature.VocabWord
 
POINTS() - Static method in class org.apache.spark.mllib.clustering.StreamingKMeans
 
pointSilhouetteCoefficient(Set<Object>, double, long, Function1<Object, Object>) - Static method in class org.apache.spark.ml.evaluation.CosineSilhouette
 
pointSilhouetteCoefficient(Set<Object>, double, long, Function1<Object, Object>) - Static method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette
 
POISON_PILL() - Static method in class org.apache.spark.scheduler.AsyncEventQueue
 
Poisson$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
 
PoissonBounds - Class in org.apache.spark.util.random
Utility functions that help us determine bounds on adjusted sampling rate to guarantee exact sample sizes with high confidence when sampling with replacement.
PoissonBounds() - Constructor for class org.apache.spark.util.random.PoissonBounds
 
PoissonGenerator - Class in org.apache.spark.mllib.random
:: DeveloperApi :: Generates i.i.d.
PoissonGenerator(double) - Constructor for class org.apache.spark.mllib.random.PoissonGenerator
 
poissonJavaRDD(JavaSparkContext, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Java-friendly version of RandomRDDs.poissonRDD.
poissonJavaRDD(JavaSparkContext, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.poissonJavaRDD with the default seed.
poissonJavaRDD(JavaSparkContext, double, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.poissonJavaRDD with the default number of partitions and the default seed.
poissonJavaVectorRDD(JavaSparkContext, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Java-friendly version of RandomRDDs.poissonVectorRDD.
poissonJavaVectorRDD(JavaSparkContext, double, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.poissonJavaVectorRDD with the default seed.
poissonJavaVectorRDD(JavaSparkContext, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.poissonJavaVectorRDD with the default number of partitions and the default seed.
poissonRDD(SparkContext, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Generates an RDD comprised of i.i.d. samples from the Poisson distribution with the input mean.
PoissonSampler<T> - Class in org.apache.spark.util.random
:: DeveloperApi :: A sampler for sampling with replacement, based on values drawn from Poisson distribution.
PoissonSampler(double, boolean) - Constructor for class org.apache.spark.util.random.PoissonSampler
 
PoissonSampler(double) - Constructor for class org.apache.spark.util.random.PoissonSampler
 
poissonVectorRDD(SparkContext, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from the Poisson distribution with the input mean.
PolynomialExpansion - Class in org.apache.spark.ml.feature
Perform feature expansion in a polynomial space.
PolynomialExpansion(String) - Constructor for class org.apache.spark.ml.feature.PolynomialExpansion
 
PolynomialExpansion() - Constructor for class org.apache.spark.ml.feature.PolynomialExpansion
 
popStdev() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Compute the population standard deviation of this RDD's elements.
popStdev() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
Compute the population standard deviation of this RDD's elements.
popStdev() - Method in class org.apache.spark.util.StatCounter
Return the population standard deviation of the values.
popVariance() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Compute the population variance of this RDD's elements.
popVariance() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
Compute the population variance of this RDD's elements.
popVariance() - Method in class org.apache.spark.util.StatCounter
Return the population variance of the values.
port() - Method in interface org.apache.spark.SparkExecutorInfo
 
port() - Method in class org.apache.spark.SparkExecutorInfoImpl
 
port() - Method in class org.apache.spark.storage.BlockManagerId
 
PortableDataStream - Class in org.apache.spark.input
A class that allows DataStreams to be serialized and moved around by not creating them until they need to be read
PortableDataStream(CombineFileSplit, TaskAttemptContext, Integer) - Constructor for class org.apache.spark.input.PortableDataStream
 
portMaxRetries(SparkConf) - Static method in class org.apache.spark.util.Utils
Maximum number of retries when binding to a port before giving up.
posexplode(Column) - Static method in class org.apache.spark.sql.functions
Creates a new row for each element with position in the given array or map column.
posexplode_outer(Column) - Static method in class org.apache.spark.sql.functions
Creates a new row for each element with position in the given array or map column.
position() - Method in class org.apache.spark.storage.ReadableChannelFileRegion
 
positioned(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
post(SparkListenerEvent) - Method in class org.apache.spark.scheduler.AsyncEventQueue
 
Postfix$() - Constructor for class org.apache.spark.mllib.fpm.PrefixSpan.Postfix$
 
PostgresDialect - Class in org.apache.spark.sql.jdbc
 
PostgresDialect() - Constructor for class org.apache.spark.sql.jdbc.PostgresDialect
 
postStartHook() - Method in interface org.apache.spark.scheduler.TaskScheduler
 
postToAll(E) - Method in interface org.apache.spark.util.ListenerBus
Post the event to all registered listeners.
pow(Column, Column) - Static method in class org.apache.spark.sql.functions
Returns the value of the first argument raised to the power of the second argument.
pow(Column, String) - Static method in class org.apache.spark.sql.functions
Returns the value of the first argument raised to the power of the second argument.
pow(String, Column) - Static method in class org.apache.spark.sql.functions
Returns the value of the first argument raised to the power of the second argument.
pow(String, String) - Static method in class org.apache.spark.sql.functions
Returns the value of the first argument raised to the power of the second argument.
pow(Column, double) - Static method in class org.apache.spark.sql.functions
Returns the value of the first argument raised to the power of the second argument.
pow(String, double) - Static method in class org.apache.spark.sql.functions
Returns the value of the first argument raised to the power of the second argument.
pow(double, Column) - Static method in class org.apache.spark.sql.functions
Returns the value of the first argument raised to the power of the second argument.
pow(double, String) - Static method in class org.apache.spark.sql.functions
Returns the value of the first argument raised to the power of the second argument.
POW_10() - Static method in class org.apache.spark.sql.types.Decimal
 
PowerIterationClustering - Class in org.apache.spark.ml.clustering
:: Experimental :: Power Iteration Clustering (PIC), a scalable graph clustering algorithm developed by Lin and Cohen.
PowerIterationClustering() - Constructor for class org.apache.spark.ml.clustering.PowerIterationClustering
 
PowerIterationClustering - Class in org.apache.spark.mllib.clustering
Power Iteration Clustering (PIC), a scalable graph clustering algorithm developed by Lin and Cohen.
PowerIterationClustering() - Constructor for class org.apache.spark.mllib.clustering.PowerIterationClustering
Constructs a PIC instance with default parameters: {k: 2, maxIterations: 100, initMode: "random"}.
PowerIterationClustering.Assignment - Class in org.apache.spark.mllib.clustering
Cluster assignment.
PowerIterationClustering.Assignment$ - Class in org.apache.spark.mllib.clustering
 
PowerIterationClusteringModel - Class in org.apache.spark.mllib.clustering
Model produced by PowerIterationClustering.
PowerIterationClusteringModel(int, RDD<PowerIterationClustering.Assignment>) - Constructor for class org.apache.spark.mllib.clustering.PowerIterationClusteringModel
 
PowerIterationClusteringModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.clustering
 
PowerIterationClusteringParams - Interface in org.apache.spark.ml.clustering
Common params for PowerIterationClustering
pr() - Method in interface org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
Returns the precision-recall curve, which is a Dataframe containing two fields recall, precision with (0.0, 1.0) prepended to it.
pr() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
Returns the precision-recall curve, which is an RDD of (recall, precision), NOT (precision, recall), with (0.0, p) prepended to it, where p is the precision associated with the lowest recall on the curve.
preciseSize() - Method in interface org.apache.spark.storage.memory.MemoryEntryBuilder
 
Precision - Class in org.apache.spark.mllib.evaluation.binary
Precision.
Precision() - Constructor for class org.apache.spark.mllib.evaluation.binary.Precision
 
precision(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns precision for a given label (category)
precision() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Deprecated.
Use accuracy. Since 2.0.0.
precision() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
Returns document-based precision averaged by the number of documents
precision(double) - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
Returns precision for a given label (category)
precision() - Method in class org.apache.spark.sql.types.Decimal
 
precision() - Method in class org.apache.spark.sql.types.DecimalType
 
precisionAt(int) - Method in class org.apache.spark.mllib.evaluation.RankingMetrics
Compute the average precision of all the queries, truncated at ranking position k.
precisionByLabel() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns precision for each label (category).
precisionByThreshold() - Method in interface org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
Returns a dataframe with two fields (threshold, precision) curve.
precisionByThreshold() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
Returns the (threshold, precision) curve.
predict(Vector) - Method in interface org.apache.spark.ml.ann.TopologyModel
Prediction of the model.
predict(FeaturesType) - Method in class org.apache.spark.ml.classification.ClassificationModel
Predict label for the given features.
predict(Vector) - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
 
predict(Vector) - Method in class org.apache.spark.ml.classification.GBTClassificationModel
 
predict(Vector) - Method in class org.apache.spark.ml.classification.LinearSVCModel
 
predict(Vector) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
Predict label for the given feature vector.
predict(Vector) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
Predict label for the given features.
predict(FeaturesType) - Method in class org.apache.spark.ml.PredictionModel
Predict label for the given features.
predict(Vector) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
predict(Vector) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
 
predict(Vector) - Method in class org.apache.spark.ml.regression.GBTRegressionModel
 
predict(Vector) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
 
predict(Vector) - Method in class org.apache.spark.ml.regression.LinearRegressionModel
 
predict(Vector) - Method in class org.apache.spark.ml.regression.RandomForestRegressionModel
 
predict(RDD<Vector>) - Method in interface org.apache.spark.mllib.classification.ClassificationModel
Predict values for the given data set using the model trained.
predict(Vector) - Method in interface org.apache.spark.mllib.classification.ClassificationModel
Predict values for a single data point using the model trained.
predict(JavaRDD<Vector>) - Method in interface org.apache.spark.mllib.classification.ClassificationModel
Predict values for examples stored in a JavaRDD.
predict(RDD<Vector>) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
 
predict(Vector) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
 
predict(Vector) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
Predicts the index of the cluster that the input point belongs to.
predict(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
Predicts the indices of the clusters that the input points belong to.
predict(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
Java-friendly version of predict().
predict(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
Maps given points to their cluster indices.
predict(Vector) - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
Maps given point to its cluster index.
predict(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
Java-friendly version of predict()
predict(Vector) - Method in class org.apache.spark.mllib.clustering.KMeansModel
Returns the cluster index that a given point belongs to.
predict(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.KMeansModel
Maps given points to their cluster indices.
predict(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.clustering.KMeansModel
Maps given points to their cluster indices.
predict(int, int) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
Predict the rating of one user for one product.
predict(RDD<Tuple2<Object, Object>>) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
Predict the rating of many users for many products.
predict(JavaPairRDD<Integer, Integer>) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
Java-friendly version of MatrixFactorizationModel.predict.
predict(RDD<Vector>) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearModel
Predict values for the given data set using the model trained.
predict(Vector) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearModel
Predict values for a single data point using the model trained.
predict(RDD<Object>) - Method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
Predict labels for provided features.
predict(JavaDoubleRDD) - Method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
Predict labels for provided features.
predict(double) - Method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
Predict a single label.
predict(RDD<Vector>) - Method in interface org.apache.spark.mllib.regression.RegressionModel
Predict values for the given data set using the model trained.
predict(Vector) - Method in interface org.apache.spark.mllib.regression.RegressionModel
Predict values for a single data point using the model trained.
predict(JavaRDD<Vector>) - Method in interface org.apache.spark.mllib.regression.RegressionModel
Predict values for examples stored in a JavaRDD.
predict(Vector) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
Predict values for a single data point using the model trained.
predict(RDD<Vector>) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
Predict values for the given data set using the model trained.
predict(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
Predict values for the given data set using the model trained.
predict() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
 
predict() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData
 
predict() - Method in class org.apache.spark.mllib.tree.model.Node
 
predict(Vector) - Method in class org.apache.spark.mllib.tree.model.Node
predict value if node is not leaf
Predict - Class in org.apache.spark.mllib.tree.model
:: DeveloperApi :: Predicted value for a node param: predict predicted value param: prob probability of the label (classification only)
Predict(double, double) - Constructor for class org.apache.spark.mllib.tree.model.Predict
 
predict() - Method in class org.apache.spark.mllib.tree.model.Predict
 
PredictData(double, double) - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData
 
PredictData$() - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData$
 
prediction() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
 
prediction() - Method in class org.apache.spark.ml.tree.InternalNode
 
prediction() - Method in class org.apache.spark.ml.tree.LeafNode
 
prediction() - Method in class org.apache.spark.ml.tree.Node
Prediction a leaf node makes, or which an internal node would make if it were a leaf node
predictionCol() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Field in "predictions" which gives the prediction of each class.
predictionCol() - Method in class org.apache.spark.ml.classification.LogisticRegressionSummaryImpl
 
predictionCol() - Method in class org.apache.spark.ml.clustering.ClusteringSummary
 
predictionCol() - Method in interface org.apache.spark.ml.param.shared.HasPredictionCol
Param for prediction column name.
predictionCol() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
Field in "predictions" which gives the predicted value of each instance.
predictionCol() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
 
PredictionModel<FeaturesType,M extends PredictionModel<FeaturesType,M>> - Class in org.apache.spark.ml
:: DeveloperApi :: Abstraction for a model for prediction tasks (regression and classification).
PredictionModel() - Constructor for class org.apache.spark.ml.PredictionModel
 
predictions() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Dataframe output by the model's transform method.
predictions() - Method in class org.apache.spark.ml.classification.LogisticRegressionSummaryImpl
 
predictions() - Method in class org.apache.spark.ml.clustering.ClusteringSummary
 
predictions() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
Predictions output by the model's transform method.
predictions() - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
Predictions associated with the boundaries at the same index, monotone because of isotonic regression.
predictions() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
 
predictions() - Method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
 
predictOn(DStream<Vector>) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
Use the clustering model to make predictions on batches of data from a DStream.
predictOn(JavaDStream<Vector>) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
Java-friendly version of predictOn.
predictOn(DStream<Vector>) - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
Use the model to make predictions on batches of data from a DStream
predictOn(JavaDStream<Vector>) - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
Java-friendly version of predictOn.
predictOnValues(DStream<Tuple2<K, Vector>>, ClassTag<K>) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
Use the model to make predictions on the values of a DStream and carry over its keys.
predictOnValues(JavaPairDStream<K, Vector>) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
Java-friendly version of predictOnValues.
predictOnValues(DStream<Tuple2<K, Vector>>, ClassTag<K>) - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
Use the model to make predictions on the values of a DStream and carry over its keys.
predictOnValues(JavaPairDStream<K, Vector>) - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
Java-friendly version of predictOnValues.
Predictor<FeaturesType,Learner extends Predictor<FeaturesType,Learner,M>,M extends PredictionModel<FeaturesType,M>> - Class in org.apache.spark.ml
:: DeveloperApi :: Abstraction for prediction problems (regression and classification).
Predictor() - Constructor for class org.apache.spark.ml.Predictor
 
PredictorParams - Interface in org.apache.spark.ml
(private[ml]) Trait for parameters for prediction (regression and classification).
predictProbabilities(RDD<Vector>) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
Predict values for the given data set using the model trained.
predictProbabilities(Vector) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
Predict posterior class probabilities for a single data point using the model trained.
predictQuantiles(Vector) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
predictRaw(Vector) - Method in interface org.apache.spark.ml.ann.TopologyModel
Raw prediction of the model.
predictSoft(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
Given the input vectors, return the membership value of each vector to all mixture components.
predictSoft(Vector) - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
Given the input vector, return the membership values to all mixture components.
preferredLocation() - Method in class org.apache.spark.streaming.receiver.Receiver
Override this to specify a preferred location (hostname).
preferredLocations(Partition) - Method in class org.apache.spark.rdd.RDD
Get the preferred locations of a partition, taking into account whether the RDD is checkpointed.
preferredLocations() - Method in interface org.apache.spark.sql.sources.v2.reader.InputPartition
The preferred locations where the input partition reader returned by this partition can run faster, but Spark does not guarantee to run the input partition reader on these locations.
Prefix$() - Constructor for class org.apache.spark.mllib.fpm.PrefixSpan.Prefix$
 
prefixesToRewrite() - Method in class org.apache.spark.ml.feature.VectorAttributeRewriter
 
PrefixSpan - Class in org.apache.spark.ml.fpm
:: Experimental :: A parallel PrefixSpan algorithm to mine frequent sequential patterns.
PrefixSpan(String) - Constructor for class org.apache.spark.ml.fpm.PrefixSpan
 
PrefixSpan() - Constructor for class org.apache.spark.ml.fpm.PrefixSpan
 
PrefixSpan - Class in org.apache.spark.mllib.fpm
A parallel PrefixSpan algorithm to mine frequent sequential patterns.
PrefixSpan() - Constructor for class org.apache.spark.mllib.fpm.PrefixSpan
Constructs a default instance with default parameters {minSupport: 0.1, maxPatternLength: 10, maxLocalProjDBSize: 32000000L}.
PrefixSpan.FreqSequence<Item> - Class in org.apache.spark.mllib.fpm
Represents a frequent sequence.
PrefixSpan.Postfix$ - Class in org.apache.spark.mllib.fpm
 
PrefixSpan.Prefix$ - Class in org.apache.spark.mllib.fpm
 
PrefixSpanModel<Item> - Class in org.apache.spark.mllib.fpm
Model fitted by PrefixSpan param: freqSequences frequent sequences
PrefixSpanModel(RDD<PrefixSpan.FreqSequence<Item>>) - Constructor for class org.apache.spark.mllib.fpm.PrefixSpanModel
 
PrefixSpanModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.fpm
 
prefLoc() - Method in class org.apache.spark.rdd.PartitionGroup
 
pregel(A, int, EdgeDirection, Function3<Object, VD, A, VD>, Function1<EdgeTriplet<VD, ED>, Iterator<Tuple2<Object, A>>>, Function2<A, A, A>, ClassTag<A>) - Method in class org.apache.spark.graphx.GraphOps
Execute a Pregel-like iterative vertex-parallel abstraction.
Pregel - Class in org.apache.spark.graphx
Implements a Pregel-like bulk-synchronous message-passing API.
Pregel() - Constructor for class org.apache.spark.graphx.Pregel
 
prepareWritable(Writable, Seq<Tuple2<String, String>>) - Static method in class org.apache.spark.sql.hive.HiveShim
 
prepareWrite(SparkSession, Job, Map<String, String>, StructType) - Method in class org.apache.spark.sql.hive.execution.HiveFileFormat
 
prepareWrite(SparkSession, Job, Map<String, String>, StructType) - Method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
prependBaseUri(HttpServletRequest, String, String) - Static method in class org.apache.spark.ui.UIUtils
 
prettyJson() - Method in class org.apache.spark.sql.streaming.SinkProgress
The pretty (i.e.
prettyJson() - Method in class org.apache.spark.sql.streaming.SourceProgress
The pretty (i.e.
prettyJson() - Method in class org.apache.spark.sql.streaming.StateOperatorProgress
The pretty (i.e.
prettyJson() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
The pretty (i.e.
prettyJson() - Method in class org.apache.spark.sql.streaming.StreamingQueryStatus
The pretty (i.e.
prettyJson() - Static method in class org.apache.spark.sql.types.BinaryType
 
prettyJson() - Static method in class org.apache.spark.sql.types.BooleanType
 
prettyJson() - Static method in class org.apache.spark.sql.types.ByteType
 
prettyJson() - Static method in class org.apache.spark.sql.types.CalendarIntervalType
 
prettyJson() - Method in class org.apache.spark.sql.types.DataType
The pretty (i.e.
prettyJson() - Static method in class org.apache.spark.sql.types.DateType
 
prettyJson() - Static method in class org.apache.spark.sql.types.DoubleType
 
prettyJson() - Static method in class org.apache.spark.sql.types.FloatType
 
prettyJson() - Static method in class org.apache.spark.sql.types.IntegerType
 
prettyJson() - Static method in class org.apache.spark.sql.types.LongType
 
prettyJson() - Static method in class org.apache.spark.sql.types.NullType
 
prettyJson() - Static method in class org.apache.spark.sql.types.ShortType
 
prettyJson() - Static method in class org.apache.spark.sql.types.StringType
 
prettyJson() - Static method in class org.apache.spark.sql.types.TimestampType
 
prettyPrint() - Method in class org.apache.spark.streaming.Duration
 
prev() - Method in class org.apache.spark.rdd.ShuffledRDD
 
prev() - Method in class org.apache.spark.status.LiveRDDPartition
 
prevPageSizeFormField() - Method in interface org.apache.spark.ui.PagedTable
 
print() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Print the first ten elements of each RDD generated in this DStream.
print(int) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Print the first num elements of each RDD generated in this DStream.
print() - Method in class org.apache.spark.streaming.dstream.DStream
Print the first ten elements of each RDD generated in this DStream.
print(int) - Method in class org.apache.spark.streaming.dstream.DStream
Print the first num elements of each RDD generated in this DStream.
printErrorAndExit(String) - Method in interface org.apache.spark.util.CommandLineUtils
 
printMessage(String) - Method in interface org.apache.spark.util.CommandLineUtils
 
printSchema() - Method in class org.apache.spark.sql.Dataset
Prints the schema to the console in a nice tree format.
printStats() - Method in class org.apache.spark.streaming.scheduler.StatsReportListener
 
printStream() - Method in interface org.apache.spark.util.CommandLineUtils
 
printTreeString() - Method in class org.apache.spark.sql.types.StructType
 
prioritize(BlockManagerId, Seq<BlockManagerId>, HashSet<BlockManagerId>, BlockId, int) - Method in class org.apache.spark.storage.BasicBlockReplicationPolicy
Method to prioritize a bunch of candidate peers of a block manager.
prioritize(BlockManagerId, Seq<BlockManagerId>, HashSet<BlockManagerId>, BlockId, int) - Method in interface org.apache.spark.storage.BlockReplicationPolicy
Method to prioritize a bunch of candidate peers of a block
prioritize(BlockManagerId, Seq<BlockManagerId>, HashSet<BlockManagerId>, BlockId, int) - Method in class org.apache.spark.storage.RandomBlockReplicationPolicy
Method to prioritize a bunch of candidate peers of a block.
priority() - Method in interface org.apache.spark.scheduler.Schedulable
 
prob() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData
 
prob() - Method in class org.apache.spark.mllib.tree.model.Predict
 
ProbabilisticClassificationModel<FeaturesType,M extends ProbabilisticClassificationModel<FeaturesType,M>> - Class in org.apache.spark.ml.classification
:: DeveloperApi ::
ProbabilisticClassificationModel() - Constructor for class org.apache.spark.ml.classification.ProbabilisticClassificationModel
 
ProbabilisticClassifier<FeaturesType,E extends ProbabilisticClassifier<FeaturesType,E,M>,M extends ProbabilisticClassificationModel<FeaturesType,M>> - Class in org.apache.spark.ml.classification
:: DeveloperApi ::
ProbabilisticClassifier() - Constructor for class org.apache.spark.ml.classification.ProbabilisticClassifier
 
ProbabilisticClassifierParams - Interface in org.apache.spark.ml.classification
(private[classification]) Params for probabilistic classification.
probabilities() - Static method in class org.apache.spark.scheduler.StatsReportListener
 
probability() - Method in class org.apache.spark.ml.clustering.GaussianMixtureSummary
Probability of each cluster.
probabilityCol() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Field in "predictions" which gives the probability of each class as a vector.
probabilityCol() - Method in class org.apache.spark.ml.classification.LogisticRegressionSummaryImpl
 
probabilityCol() - Method in class org.apache.spark.ml.clustering.GaussianMixtureSummary
 
probabilityCol() - Method in interface org.apache.spark.ml.param.shared.HasProbabilityCol
Param for Column name for predicted class conditional probabilities.
Probit$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Probit$
 
process(T) - Method in class org.apache.spark.sql.ForeachWriter
Called to process the data in the executor side.
PROCESS_LOCAL() - Static method in class org.apache.spark.scheduler.TaskLocality
 
processAllAvailable() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Blocks until all available data in the source has been processed and committed to the sink.
processedRowsPerSecond() - Method in class org.apache.spark.sql.streaming.SourceProgress
 
processedRowsPerSecond() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
The aggregate (across all sources) rate at which Spark is processing data.
processingDelay() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
Time taken for the all jobs of this batch to finish processing from the time they started processing.
processingEndTime() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
 
processingStartTime() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
 
ProcessingTime - Class in org.apache.spark.sql.streaming
Deprecated.
use Trigger.ProcessingTime(intervalMs). Since 2.2.0.
ProcessingTime(long) - Constructor for class org.apache.spark.sql.streaming.ProcessingTime
Deprecated.
 
ProcessingTime(long) - Static method in class org.apache.spark.sql.streaming.Trigger
A trigger policy that runs a query periodically based on an interval in processing time.
ProcessingTime(long, TimeUnit) - Static method in class org.apache.spark.sql.streaming.Trigger
(Java-friendly) A trigger policy that runs a query periodically based on an interval in processing time.
ProcessingTime(Duration) - Static method in class org.apache.spark.sql.streaming.Trigger
(Scala-friendly) A trigger policy that runs a query periodically based on an interval in processing time.
ProcessingTime(String) - Static method in class org.apache.spark.sql.streaming.Trigger
A trigger policy that runs a query periodically based on an interval in processing time.
processingTime() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
 
ProcessingTimeTimeout() - Static method in class org.apache.spark.sql.streaming.GroupStateTimeout
Timeout based on processing time.
processStreamByLine(String, InputStream, Function1<String, BoxedUnit>) - Static method in class org.apache.spark.util.Utils
Return and start a daemon thread that processes the content of the input stream line by line.
producedAttributes() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
 
product() - Method in class org.apache.spark.mllib.recommendation.Rating
 
product(TypeTags.TypeTag<T>) - Static method in class org.apache.spark.sql.Encoders
An encoder for Scala's product type (tuples, case classes, etc).
productArity() - Static method in class org.apache.spark.ExpireDeadHosts
 
productArity() - Static method in class org.apache.spark.ml.feature.Dot
 
productArity() - Static method in class org.apache.spark.Resubmitted
 
productArity() - Static method in class org.apache.spark.rpc.netty.OnStart
 
productArity() - Static method in class org.apache.spark.rpc.netty.OnStop
 
productArity() - Static method in class org.apache.spark.scheduler.AllJobsCancelled
 
productArity() - Static method in class org.apache.spark.scheduler.JobSucceeded
 
productArity() - Static method in class org.apache.spark.scheduler.ResubmitFailedStages
 
productArity() - Static method in class org.apache.spark.scheduler.StopCoordinator
 
productArity() - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
productArity() - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
productArity() - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
productArity() - Static method in class org.apache.spark.sql.types.BinaryType
 
productArity() - Static method in class org.apache.spark.sql.types.BooleanType
 
productArity() - Static method in class org.apache.spark.sql.types.ByteType
 
productArity() - Static method in class org.apache.spark.sql.types.CalendarIntervalType
 
productArity() - Static method in class org.apache.spark.sql.types.DateType
 
productArity() - Static method in class org.apache.spark.sql.types.DoubleType
 
productArity() - Static method in class org.apache.spark.sql.types.FloatType
 
productArity() - Static method in class org.apache.spark.sql.types.IntegerType
 
productArity() - Static method in class org.apache.spark.sql.types.LongType
 
productArity() - Static method in class org.apache.spark.sql.types.NullType
 
productArity() - Static method in class org.apache.spark.sql.types.ShortType
 
productArity() - Static method in class org.apache.spark.sql.types.StringType
 
productArity() - Static method in class org.apache.spark.sql.types.TimestampType
 
productArity() - Static method in class org.apache.spark.StopMapOutputTracker
 
productArity() - Static method in class org.apache.spark.streaming.kinesis.DefaultCredentials
 
productArity() - Static method in class org.apache.spark.streaming.scheduler.AllReceiverIds
 
productArity() - Static method in class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
 
productArity() - Static method in class org.apache.spark.streaming.scheduler.StopAllReceivers
 
productArity() - Static method in class org.apache.spark.Success
 
productArity() - Static method in class org.apache.spark.TaskResultLost
 
productArity() - Static method in class org.apache.spark.TaskSchedulerIsSet
 
productArity() - Static method in class org.apache.spark.UnknownReason
 
productElement(int) - Static method in class org.apache.spark.ExpireDeadHosts
 
productElement(int) - Static method in class org.apache.spark.ml.feature.Dot
 
productElement(int) - Static method in class org.apache.spark.Resubmitted
 
productElement(int) - Static method in class org.apache.spark.rpc.netty.OnStart
 
productElement(int) - Static method in class org.apache.spark.rpc.netty.OnStop
 
productElement(int) - Static method in class org.apache.spark.scheduler.AllJobsCancelled
 
productElement(int) - Static method in class org.apache.spark.scheduler.JobSucceeded
 
productElement(int) - Static method in class org.apache.spark.scheduler.ResubmitFailedStages
 
productElement(int) - Static method in class org.apache.spark.scheduler.StopCoordinator
 
productElement(int) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
productElement(int) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
productElement(int) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
productElement(int) - Static method in class org.apache.spark.sql.types.BinaryType
 
productElement(int) - Static method in class org.apache.spark.sql.types.BooleanType
 
productElement(int) - Static method in class org.apache.spark.sql.types.ByteType
 
productElement(int) - Static method in class org.apache.spark.sql.types.CalendarIntervalType
 
productElement(int) - Static method in class org.apache.spark.sql.types.DateType
 
productElement(int) - Static method in class org.apache.spark.sql.types.DoubleType
 
productElement(int) - Static method in class org.apache.spark.sql.types.FloatType
 
productElement(int) - Static method in class org.apache.spark.sql.types.IntegerType
 
productElement(int) - Static method in class org.apache.spark.sql.types.LongType
 
productElement(int) - Static method in class org.apache.spark.sql.types.NullType
 
productElement(int) - Static method in class org.apache.spark.sql.types.ShortType
 
productElement(int) - Static method in class org.apache.spark.sql.types.StringType
 
productElement(int) - Static method in class org.apache.spark.sql.types.TimestampType
 
productElement(int) - Static method in class org.apache.spark.StopMapOutputTracker
 
productElement(int) - Static method in class org.apache.spark.streaming.kinesis.DefaultCredentials
 
productElement(int) - Static method in class org.apache.spark.streaming.scheduler.AllReceiverIds
 
productElement(int) - Static method in class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
 
productElement(int) - Static method in class org.apache.spark.streaming.scheduler.StopAllReceivers
 
productElement(int) - Static method in class org.apache.spark.Success
 
productElement(int) - Static method in class org.apache.spark.TaskResultLost
 
productElement(int) - Static method in class org.apache.spark.TaskSchedulerIsSet
 
productElement(int) - Static method in class org.apache.spark.UnknownReason
 
productFeatures() - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
 
productIterator() - Static method in class org.apache.spark.ExpireDeadHosts
 
productIterator() - Static method in class org.apache.spark.ml.feature.Dot
 
productIterator() - Static method in class org.apache.spark.Resubmitted
 
productIterator() - Static method in class org.apache.spark.rpc.netty.OnStart
 
productIterator() - Static method in class org.apache.spark.rpc.netty.OnStop
 
productIterator() - Static method in class org.apache.spark.scheduler.AllJobsCancelled
 
productIterator() - Static method in class org.apache.spark.scheduler.JobSucceeded
 
productIterator() - Static method in class org.apache.spark.scheduler.ResubmitFailedStages
 
productIterator() - Static method in class org.apache.spark.scheduler.StopCoordinator
 
productIterator() - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
productIterator() - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
productIterator() - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
productIterator() - Static method in class org.apache.spark.sql.types.BinaryType
 
productIterator() - Static method in class org.apache.spark.sql.types.BooleanType
 
productIterator() - Static method in class org.apache.spark.sql.types.ByteType
 
productIterator() - Static method in class org.apache.spark.sql.types.CalendarIntervalType
 
productIterator() - Static method in class org.apache.spark.sql.types.DateType
 
productIterator() - Static method in class org.apache.spark.sql.types.DoubleType
 
productIterator() - Static method in class org.apache.spark.sql.types.FloatType
 
productIterator() - Static method in class org.apache.spark.sql.types.IntegerType
 
productIterator() - Static method in class org.apache.spark.sql.types.LongType
 
productIterator() - Static method in class org.apache.spark.sql.types.NullType
 
productIterator() - Static method in class org.apache.spark.sql.types.ShortType
 
productIterator() - Static method in class org.apache.spark.sql.types.StringType
 
productIterator() - Static method in class org.apache.spark.sql.types.TimestampType
 
productIterator() - Static method in class org.apache.spark.StopMapOutputTracker
 
productIterator() - Static method in class org.apache.spark.streaming.kinesis.DefaultCredentials
 
productIterator() - Static method in class org.apache.spark.streaming.scheduler.AllReceiverIds
 
productIterator() - Static method in class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
 
productIterator() - Static method in class org.apache.spark.streaming.scheduler.StopAllReceivers
 
productIterator() - Static method in class org.apache.spark.Success
 
productIterator() - Static method in class org.apache.spark.TaskResultLost
 
productIterator() - Static method in class org.apache.spark.TaskSchedulerIsSet
 
productIterator() - Static method in class org.apache.spark.UnknownReason
 
productPrefix() - Static method in class org.apache.spark.ExpireDeadHosts
 
productPrefix() - Static method in class org.apache.spark.ml.feature.Dot
 
productPrefix() - Static method in class org.apache.spark.Resubmitted
 
productPrefix() - Static method in class org.apache.spark.rpc.netty.OnStart
 
productPrefix() - Static method in class org.apache.spark.rpc.netty.OnStop
 
productPrefix() - Static method in class org.apache.spark.scheduler.AllJobsCancelled
 
productPrefix() - Static method in class org.apache.spark.scheduler.JobSucceeded
 
productPrefix() - Static method in class org.apache.spark.scheduler.ResubmitFailedStages
 
productPrefix() - Static method in class org.apache.spark.scheduler.StopCoordinator
 
productPrefix() - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
productPrefix() - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
productPrefix() - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 
productPrefix() - Static method in class org.apache.spark.sql.types.BinaryType
 
productPrefix() - Static method in class org.apache.spark.sql.types.BooleanType
 
productPrefix() - Static method in class org.apache.spark.sql.types.ByteType
 
productPrefix() - Static method in class org.apache.spark.sql.types.CalendarIntervalType
 
productPrefix() - Static method in class org.apache.spark.sql.types.DateType
 
productPrefix() - Static method in class org.apache.spark.sql.types.DoubleType
 
productPrefix() - Static method in class org.apache.spark.sql.types.FloatType
 
productPrefix() - Static method in class org.apache.spark.sql.types.IntegerType
 
productPrefix() - Static method in class org.apache.spark.sql.types.LongType
 
productPrefix() - Static method in class org.apache.spark.sql.types.NullType
 
productPrefix() - Static method in class org.apache.spark.sql.types.ShortType
 
productPrefix() - Static method in class org.apache.spark.sql.types.StringType
 
productPrefix() - Static method in class org.apache.spark.sql.types.TimestampType
 
productPrefix() - Static method in class org.apache.spark.StopMapOutputTracker
 
productPrefix() - Static method in class org.apache.spark.streaming.kinesis.DefaultCredentials
 
productPrefix() - Static method in class org.apache.spark.streaming.scheduler.AllReceiverIds
 
productPrefix() - Static method in class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
 
productPrefix() - Static method in class org.apache.spark.streaming.scheduler.StopAllReceivers
 
productPrefix() - Static method in class org.apache.spark.Success
 
productPrefix() - Static method in class org.apache.spark.TaskResultLost
 
productPrefix() - Static method in class org.apache.spark.TaskSchedulerIsSet
 
productPrefix() - Static method in class org.apache.spark.UnknownReason
 
progress() - Method in class org.apache.spark.sql.streaming.StreamingQueryListener.QueryProgressEvent
 
project(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
 
project(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
 
properties() - Method in class org.apache.spark.scheduler.SparkListenerJobStart
 
properties() - Method in class org.apache.spark.scheduler.SparkListenerStageSubmitted
 
propertiesFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
propertiesToJson(Properties) - Static method in class org.apache.spark.util.JsonProtocol
 
provider() - Static method in class org.apache.spark.streaming.kinesis.DefaultCredentials
 
provider() - Method in interface org.apache.spark.streaming.kinesis.SparkAWSCredentials
Return an AWSCredentialProvider instance that can be used by the Kinesis Client Library to authenticate to AWS services (Kinesis, CloudWatch and DynamoDB).
proxyBase() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
 
pruneColumns(StructType) - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsPushDownRequiredColumns
Applies column pruning w.r.t.
PrunedFilteredScan - Interface in org.apache.spark.sql.sources
A BaseRelation that can eliminate unneeded columns and filter using selected predicates before producing an RDD containing all matching tuples as Row objects.
PrunedScan - Interface in org.apache.spark.sql.sources
A BaseRelation that can eliminate unneeded columns before producing an RDD containing all of its tuples as Row objects.
Pseudorandom - Interface in org.apache.spark.util.random
:: DeveloperApi :: A class with pseudorandom behavior.
pushedFilters() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsPushDownFilters
Returns the filters that are pushed to the data source via SupportsPushDownFilters.pushFilters(Filter[]).
pushFilters(Filter[]) - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsPushDownFilters
Pushes down filters, and returns filters that need to be evaluated after scanning.
put(ParamPair<?>...) - Method in class org.apache.spark.ml.param.ParamMap
Puts a list of param pairs (overwrites if the input params exists).
put(Param<T>, T) - Method in class org.apache.spark.ml.param.ParamMap
Puts a (param, value) pair (overwrites if the input param exists).
put(Seq<ParamPair<?>>) - Method in class org.apache.spark.ml.param.ParamMap
Puts a list of param pairs (overwrites if the input params exists).
put(Object) - Method in class org.apache.spark.util.sketch.BloomFilter
Puts an item into this BloomFilter.
putBinary(byte[]) - Method in class org.apache.spark.util.sketch.BloomFilter
A specialized variant of BloomFilter.put(Object) that only supports byte array items.
putBoolean(String, boolean) - Method in class org.apache.spark.sql.types.MetadataBuilder
Puts a Boolean.
putBooleanArray(String, boolean[]) - Method in class org.apache.spark.sql.types.MetadataBuilder
Puts a Boolean array.
putDouble(String, double) - Method in class org.apache.spark.sql.types.MetadataBuilder
Puts a Double.
putDoubleArray(String, double[]) - Method in class org.apache.spark.sql.types.MetadataBuilder
Puts a Double array.
putLong(String, long) - Method in class org.apache.spark.sql.types.MetadataBuilder
Puts a Long.
putLong(long) - Method in class org.apache.spark.util.sketch.BloomFilter
A specialized variant of BloomFilter.put(Object) that only supports long items.
putLongArray(String, long[]) - Method in class org.apache.spark.sql.types.MetadataBuilder
Puts a Long array.
putMetadata(String, Metadata) - Method in class org.apache.spark.sql.types.MetadataBuilder
Puts a Metadata.
putMetadataArray(String, Metadata[]) - Method in class org.apache.spark.sql.types.MetadataBuilder
Puts a Metadata array.
putNull(String) - Method in class org.apache.spark.sql.types.MetadataBuilder
Puts a null.
putString(String, String) - Method in class org.apache.spark.sql.types.MetadataBuilder
Puts a String.
putString(String) - Method in class org.apache.spark.util.sketch.BloomFilter
A specialized variant of BloomFilter.put(Object) that only supports String items.
putStringArray(String, String[]) - Method in class org.apache.spark.sql.types.MetadataBuilder
Puts a String array.
pValue() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
 
pValue() - Method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTestResult
 
pValue() - Method in interface org.apache.spark.mllib.stat.test.TestResult
The probability of obtaining a test statistic result at least as extreme as the one that was actually observed, assuming that the null hypothesis is true.
pValues() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionTrainingSummary
Two-sided p-value of estimated coefficients and intercept.
pValues() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
Two-sided p-value of estimated coefficients and intercept.
PythonStreamingListener - Interface in org.apache.spark.streaming.api.java
 
pyUDT() - Method in class org.apache.spark.mllib.linalg.VectorUDT
 

Q

Q() - Method in class org.apache.spark.mllib.linalg.QRDecomposition
 
QRDecomposition<QType,RType> - Class in org.apache.spark.mllib.linalg
Represents QR factors.
QRDecomposition(QType, RType) - Constructor for class org.apache.spark.mllib.linalg.QRDecomposition
 
quantileCalculationStrategy() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
QuantileDiscretizer - Class in org.apache.spark.ml.feature
QuantileDiscretizer takes a column with continuous features and outputs a column with binned categorical features.
QuantileDiscretizer(String) - Constructor for class org.apache.spark.ml.feature.QuantileDiscretizer
 
QuantileDiscretizer() - Constructor for class org.apache.spark.ml.feature.QuantileDiscretizer
 
QuantileDiscretizerBase - Interface in org.apache.spark.ml.feature
quantileProbabilities() - Method in interface org.apache.spark.ml.regression.AFTSurvivalRegressionParams
Param for quantile probabilities array.
quantiles() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
quantilesCol() - Method in interface org.apache.spark.ml.regression.AFTSurvivalRegressionParams
Param for quantiles column name.
QuantileStrategy - Class in org.apache.spark.mllib.tree.configuration
Enum for selecting the quantile calculation strategy
QuantileStrategy() - Constructor for class org.apache.spark.mllib.tree.configuration.QuantileStrategy
 
quarter(Column) - Static method in class org.apache.spark.sql.functions
Extracts the quarter as an integer from a given date/timestamp/string.
query() - Method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
 
query() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
 
query() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
 
queryExecution() - Method in class org.apache.spark.sql.Dataset
 
queryExecution() - Method in class org.apache.spark.sql.KeyValueGroupedDataset
 
QueryExecutionListener - Interface in org.apache.spark.sql.util
:: Experimental :: The interface of query execution listener that can be used to analyze execution metrics.
queryName(String) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Specifies the name of the StreamingQuery that can be started with start().
queueStream(Queue<JavaRDD<T>>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream from a queue of RDDs.
queueStream(Queue<JavaRDD<T>>, boolean) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream from a queue of RDDs.
queueStream(Queue<JavaRDD<T>>, boolean, JavaRDD<T>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream from a queue of RDDs.
queueStream(Queue<RDD<T>>, boolean, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
Create an input stream from a queue of RDDs.
queueStream(Queue<RDD<T>>, boolean, RDD<T>, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
Create an input stream from a queue of RDDs.
quot(Decimal, Decimal) - Method in class org.apache.spark.sql.types.Decimal.DecimalAsIfIntegral$
 
quoteIdentifier(String) - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
 
quoteIdentifier(String) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
 
quoteIdentifier(String) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
 
quoteIdentifier(String) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
Quotes the identifier.
quoteIdentifier(String) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
 
quoteIdentifier(String) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
 
quoteIdentifier(String) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
 
quoteIdentifier(String) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
 
quoteIdentifier(String) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
 
quoteIdentifier(String) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
 

R

R() - Method in class org.apache.spark.mllib.linalg.QRDecomposition
 
r2() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
Returns R^2^, the coefficient of determination.
r2() - Method in class org.apache.spark.mllib.evaluation.RegressionMetrics
Returns R^2^, the unadjusted coefficient of determination.
r2adj() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
Returns Adjusted R^2^, the adjusted coefficient of determination.
RACK_LOCAL() - Static method in class org.apache.spark.scheduler.TaskLocality
 
radians(Column) - Static method in class org.apache.spark.sql.functions
Converts an angle measured in degrees to an approximately equivalent angle measured in radians.
radians(String) - Static method in class org.apache.spark.sql.functions
Converts an angle measured in degrees to an approximately equivalent angle measured in radians.
rand(int, int, Random) - Static method in class org.apache.spark.ml.linalg.DenseMatrix
Generate a DenseMatrix consisting of i.i.d. uniform random numbers.
rand(int, int, Random) - Static method in class org.apache.spark.ml.linalg.Matrices
Generate a DenseMatrix consisting of i.i.d. uniform random numbers.
rand(int, int, Random) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
Generate a DenseMatrix consisting of i.i.d. uniform random numbers.
rand(int, int, Random) - Static method in class org.apache.spark.mllib.linalg.Matrices
Generate a DenseMatrix consisting of i.i.d. uniform random numbers.
rand(long) - Static method in class org.apache.spark.sql.functions
Generate a random column with independent and identically distributed (i.i.d.) samples from U[0.0, 1.0].
rand() - Static method in class org.apache.spark.sql.functions
Generate a random column with independent and identically distributed (i.i.d.) samples from U[0.0, 1.0].
randn(int, int, Random) - Static method in class org.apache.spark.ml.linalg.DenseMatrix
Generate a DenseMatrix consisting of i.i.d. gaussian random numbers.
randn(int, int, Random) - Static method in class org.apache.spark.ml.linalg.Matrices
Generate a DenseMatrix consisting of i.i.d. gaussian random numbers.
randn(int, int, Random) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
Generate a DenseMatrix consisting of i.i.d. gaussian random numbers.
randn(int, int, Random) - Static method in class org.apache.spark.mllib.linalg.Matrices
Generate a DenseMatrix consisting of i.i.d. gaussian random numbers.
randn(long) - Static method in class org.apache.spark.sql.functions
Generate a column with independent and identically distributed (i.i.d.) samples from the standard normal distribution.
randn() - Static method in class org.apache.spark.sql.functions
Generate a column with independent and identically distributed (i.i.d.) samples from the standard normal distribution.
random() - Method in class org.apache.spark.ml.image.SamplePathFilter
 
RANDOM() - Static method in class org.apache.spark.mllib.clustering.KMeans
 
random() - Static method in class org.apache.spark.util.Utils
 
RandomBlockReplicationPolicy - Class in org.apache.spark.storage
 
RandomBlockReplicationPolicy() - Constructor for class org.apache.spark.storage.RandomBlockReplicationPolicy
 
RandomDataGenerator<T> - Interface in org.apache.spark.mllib.random
:: DeveloperApi :: Trait for random data generators that generate i.i.d.
RandomForest - Class in org.apache.spark.ml.tree.impl
ALGORITHM
RandomForest() - Constructor for class org.apache.spark.ml.tree.impl.RandomForest
 
RandomForest - Class in org.apache.spark.mllib.tree
A class that implements a Random Forest learning algorithm for classification and regression.
RandomForest(Strategy, int, String, int) - Constructor for class org.apache.spark.mllib.tree.RandomForest
 
RandomForestClassificationModel - Class in org.apache.spark.ml.classification
Random Forest model for classification.
RandomForestClassifier - Class in org.apache.spark.ml.classification
Random Forest learning algorithm for classification.
RandomForestClassifier(String) - Constructor for class org.apache.spark.ml.classification.RandomForestClassifier
 
RandomForestClassifier() - Constructor for class org.apache.spark.ml.classification.RandomForestClassifier
 
RandomForestClassifierParams - Interface in org.apache.spark.ml.tree
 
RandomForestModel - Class in org.apache.spark.mllib.tree.model
Represents a random forest model.
RandomForestModel(Enumeration.Value, DecisionTreeModel[]) - Constructor for class org.apache.spark.mllib.tree.model.RandomForestModel
 
RandomForestParams - Interface in org.apache.spark.ml.tree
Parameters for Random Forest algorithms.
RandomForestRegressionModel - Class in org.apache.spark.ml.regression
Random Forest model for regression.
RandomForestRegressor - Class in org.apache.spark.ml.regression
Random Forest learning algorithm for regression.
RandomForestRegressor(String) - Constructor for class org.apache.spark.ml.regression.RandomForestRegressor
 
RandomForestRegressor() - Constructor for class org.apache.spark.ml.regression.RandomForestRegressor
 
RandomForestRegressorParams - Interface in org.apache.spark.ml.tree
 
randomize(TraversableOnce<T>, ClassTag<T>) - Static method in class org.apache.spark.util.Utils
Shuffle the elements of a collection into a random order, returning the result in a new collection.
randomizeInPlace(Object, Random) - Static method in class org.apache.spark.util.Utils
Shuffle the elements of an array into a random order, modifying the original array.
randomJavaRDD(JavaSparkContext, RandomDataGenerator<T>, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
:: DeveloperApi :: Generates an RDD comprised of i.i.d. samples produced by the input RandomDataGenerator.
randomJavaRDD(JavaSparkContext, RandomDataGenerator<T>, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
:: DeveloperApi :: RandomRDDs.randomJavaRDD with the default seed.
randomJavaRDD(JavaSparkContext, RandomDataGenerator<T>, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
:: DeveloperApi :: RandomRDDs.randomJavaRDD with the default seed & numPartitions
randomJavaVectorRDD(JavaSparkContext, RandomDataGenerator<Object>, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
:: DeveloperApi :: Java-friendly version of RandomRDDs.randomVectorRDD.
randomJavaVectorRDD(JavaSparkContext, RandomDataGenerator<Object>, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
:: DeveloperApi :: RandomRDDs.randomJavaVectorRDD with the default seed.
randomJavaVectorRDD(JavaSparkContext, RandomDataGenerator<Object>, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
:: DeveloperApi :: RandomRDDs.randomJavaVectorRDD with the default number of partitions and the default seed.
randomRDD(SparkContext, RandomDataGenerator<T>, long, int, long, ClassTag<T>) - Static method in class org.apache.spark.mllib.random.RandomRDDs
:: DeveloperApi :: Generates an RDD comprised of i.i.d. samples produced by the input RandomDataGenerator.
RandomRDDs - Class in org.apache.spark.mllib.random
Generator methods for creating RDDs comprised of i.i.d. samples from some distribution.
RandomRDDs() - Constructor for class org.apache.spark.mllib.random.RandomRDDs
 
RandomSampler<T,U> - Interface in org.apache.spark.util.random
:: DeveloperApi :: A pseudorandom sampler.
randomSplit(double[]) - Method in class org.apache.spark.api.java.JavaRDD
Randomly splits this RDD with the provided weights.
randomSplit(double[], long) - Method in class org.apache.spark.api.java.JavaRDD
Randomly splits this RDD with the provided weights.
randomSplit(double[], long) - Method in class org.apache.spark.rdd.RDD
Randomly splits this RDD with the provided weights.
randomSplit(double[], long) - Method in class org.apache.spark.sql.Dataset
Randomly splits this Dataset with the provided weights.
randomSplit(double[]) - Method in class org.apache.spark.sql.Dataset
Randomly splits this Dataset with the provided weights.
randomSplitAsList(double[], long) - Method in class org.apache.spark.sql.Dataset
Returns a Java list that contains randomly split Dataset with the provided weights.
randomVectorRDD(SparkContext, RandomDataGenerator<Object>, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
:: DeveloperApi :: Generates an RDD[Vector] with vectors containing i.i.d. samples produced by the input RandomDataGenerator.
RandomVertexCut$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.RandomVertexCut$
 
range(long, long, long, int) - Method in class org.apache.spark.SparkContext
Creates a new RDD[Long] containing elements from start to end(exclusive), increased by step every element.
range(long) - Method in class org.apache.spark.sql.SparkSession
:: Experimental :: Creates a Dataset with a single LongType column named id, containing elements in a range from 0 to end (exclusive) with step value 1.
range(long, long) - Method in class org.apache.spark.sql.SparkSession
:: Experimental :: Creates a Dataset with a single LongType column named id, containing elements in a range from start to end (exclusive) with step value 1.
range(long, long, long) - Method in class org.apache.spark.sql.SparkSession
:: Experimental :: Creates a Dataset with a single LongType column named id, containing elements in a range from start to end (exclusive) with a step value.
range(long, long, long, int) - Method in class org.apache.spark.sql.SparkSession
:: Experimental :: Creates a Dataset with a single LongType column named id, containing elements in a range from start to end (exclusive) with a step value, with partition number specified.
range(long) - Method in class org.apache.spark.sql.SQLContext
 
range(long, long) - Method in class org.apache.spark.sql.SQLContext
 
range(long, long, long) - Method in class org.apache.spark.sql.SQLContext
 
range(long, long, long, int) - Method in class org.apache.spark.sql.SQLContext
 
rangeBetween(long, long) - Static method in class org.apache.spark.sql.expressions.Window
Creates a WindowSpec with the frame boundaries defined, from start (inclusive) to end (inclusive).
rangeBetween(Column, Column) - Static method in class org.apache.spark.sql.expressions.Window
Deprecated.
Use the version with Long parameter types. Since 2.4.0.
rangeBetween(long, long) - Method in class org.apache.spark.sql.expressions.WindowSpec
Defines the frame boundaries, from start (inclusive) to end (inclusive).
rangeBetween(Column, Column) - Method in class org.apache.spark.sql.expressions.WindowSpec
Deprecated.
Use the version with Long parameter types. Since 2.4.0.
RangeDependency<T> - Class in org.apache.spark
:: DeveloperApi :: Represents a one-to-one dependency between ranges of partitions in the parent and child RDDs.
RangeDependency(RDD<T>, int, int, int) - Constructor for class org.apache.spark.RangeDependency
 
RangePartitioner<K,V> - Class in org.apache.spark
A Partitioner that partitions sortable records by range into roughly equal ranges.
RangePartitioner(int, RDD<? extends Product2<K, V>>, boolean, int, Ordering<K>, ClassTag<K>) - Constructor for class org.apache.spark.RangePartitioner
 
RangePartitioner(int, RDD<? extends Product2<K, V>>, boolean, Ordering<K>, ClassTag<K>) - Constructor for class org.apache.spark.RangePartitioner
 
rank() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
 
rank() - Method in class org.apache.spark.ml.recommendation.ALSModel
 
rank() - Method in interface org.apache.spark.ml.recommendation.ALSParams
Param for rank of the matrix factorization (positive).
rank() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
The numeric rank of the fitted linear model.
rank() - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
 
rank() - Static method in class org.apache.spark.sql.functions
Window function: returns the rank of rows within a window partition.
RankingMetrics<T> - Class in org.apache.spark.mllib.evaluation
Evaluator for ranking algorithms.
RankingMetrics(RDD<Tuple2<Object, Object>>, ClassTag<T>) - Constructor for class org.apache.spark.mllib.evaluation.RankingMetrics
 
RateEstimator - Interface in org.apache.spark.streaming.scheduler.rate
A component that estimates the rate at which an InputDStream should ingest records, based on updates at every batch completion.
Rating(ID, ID, float) - Constructor for class org.apache.spark.ml.recommendation.ALS.Rating
 
rating() - Method in class org.apache.spark.ml.recommendation.ALS.Rating
 
Rating - Class in org.apache.spark.mllib.recommendation
A more compact class to represent a rating than Tuple3[Int, Int, Double].
Rating(int, int, double) - Constructor for class org.apache.spark.mllib.recommendation.Rating
 
rating() - Method in class org.apache.spark.mllib.recommendation.Rating
 
Rating$() - Constructor for class org.apache.spark.ml.recommendation.ALS.Rating$
 
RatingBlock$() - Constructor for class org.apache.spark.ml.recommendation.ALS.RatingBlock$
 
ratingCol() - Method in interface org.apache.spark.ml.recommendation.ALSParams
Param for the column name for ratings.
ratioParam() - Static method in class org.apache.spark.ml.image.SamplePathFilter
 
raw2ProbabilityInPlace(Vector) - Method in interface org.apache.spark.ml.ann.TopologyModel
Probability of the model.
rawPredictionCol() - Method in interface org.apache.spark.ml.param.shared.HasRawPredictionCol
Param for raw prediction (a.k.a.
rawSocketStream(String, int, StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream from network source hostname:port, where data is received as serialized blocks (serialized using the Spark's serializer) that can be directly pushed into the block manager without deserializing them.
rawSocketStream(String, int) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream from network source hostname:port, where data is received as serialized blocks (serialized using the Spark's serializer) that can be directly pushed into the block manager without deserializing them.
rawSocketStream(String, int, StorageLevel, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
Create an input stream from network source hostname:port, where data is received as serialized blocks (serialized using the Spark's serializer) that can be directly pushed into the block manager without deserializing them.
RawTextHelper - Class in org.apache.spark.streaming.util
 
RawTextHelper() - Constructor for class org.apache.spark.streaming.util.RawTextHelper
 
RawTextSender - Class in org.apache.spark.streaming.util
A helper program that sends blocks of Kryo-serialized text strings out on a socket at a specified rate.
RawTextSender() - Constructor for class org.apache.spark.streaming.util.RawTextSender
 
RBackendAuthHandler - Class in org.apache.spark.api.r
Authentication handler for connections from the R process.
RBackendAuthHandler(String) - Constructor for class org.apache.spark.api.r.RBackendAuthHandler
 
rdd() - Method in class org.apache.spark.api.java.JavaDoubleRDD
 
rdd() - Method in class org.apache.spark.api.java.JavaPairRDD
 
rdd() - Method in class org.apache.spark.api.java.JavaRDD
 
rdd() - Method in interface org.apache.spark.api.java.JavaRDDLike
 
RDD() - Static method in class org.apache.spark.api.r.RRunnerModes
 
rdd() - Method in class org.apache.spark.Dependency
 
rdd() - Method in class org.apache.spark.NarrowDependency
 
RDD<T> - Class in org.apache.spark.rdd
A Resilient Distributed Dataset (RDD), the basic abstraction in Spark.
RDD(SparkContext, Seq<Dependency<?>>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.RDD
 
RDD(RDD<?>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.RDD
Construct an RDD with just a one-to-one dependency on one parent
rdd() - Method in class org.apache.spark.ShuffleDependency
 
rdd() - Method in class org.apache.spark.sql.Dataset
Represents the content of the Dataset as an RDD of T.
RDD() - Static method in class org.apache.spark.storage.BlockId
 
RDDBarrier<T> - Class in org.apache.spark.rdd
:: Experimental :: Wraps an RDD in a barrier stage, which forces Spark to launch tasks of this stage together.
RDDBlockId - Class in org.apache.spark.storage
 
RDDBlockId(int, int) - Constructor for class org.apache.spark.storage.RDDBlockId
 
rddBlocks() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
rddBlocks() - Method in class org.apache.spark.status.LiveExecutor
 
rddCleaned(int) - Method in interface org.apache.spark.CleanerListener
 
RDDDataDistribution - Class in org.apache.spark.status.api.v1
 
RDDFunctions<T> - Class in org.apache.spark.mllib.rdd
:: DeveloperApi :: Machine learning specific RDD functions.
RDDFunctions(RDD<T>, ClassTag<T>) - Constructor for class org.apache.spark.mllib.rdd.RDDFunctions
 
rddId() - Method in class org.apache.spark.CleanCheckpoint
 
rddId() - Method in class org.apache.spark.CleanRDD
 
rddId() - Method in class org.apache.spark.scheduler.SparkListenerUnpersistRDD
 
rddId() - Method in class org.apache.spark.storage.BlockManagerMessages.RemoveRdd
 
rddId() - Method in class org.apache.spark.storage.RDDBlockId
 
rddIds() - Method in class org.apache.spark.status.api.v1.StageData
 
RDDInfo - Class in org.apache.spark.storage
 
RDDInfo(int, String, int, StorageLevel, Seq<Object>, String, Option<org.apache.spark.rdd.RDDOperationScope>) - Constructor for class org.apache.spark.storage.RDDInfo
 
rddInfoFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
rddInfos() - Method in class org.apache.spark.scheduler.StageInfo
 
rddInfoToJson(RDDInfo) - Static method in class org.apache.spark.util.JsonProtocol
 
RDDPartitionInfo - Class in org.apache.spark.status.api.v1
 
RDDPartitionSeq - Class in org.apache.spark.status
A custom sequence of partitions based on a mutable linked list.
RDDPartitionSeq() - Constructor for class org.apache.spark.status.RDDPartitionSeq
 
rdds() - Method in class org.apache.spark.rdd.CoGroupedRDD
 
rdds() - Method in class org.apache.spark.rdd.UnionRDD
 
RDDStorageInfo - Class in org.apache.spark.status.api.v1
 
rddToAsyncRDDActions(RDD<T>, ClassTag<T>) - Static method in class org.apache.spark.rdd.RDD
 
rddToDatasetHolder(RDD<T>, Encoder<T>) - Method in class org.apache.spark.sql.SQLImplicits
Creates a Dataset from an RDD.
rddToOrderedRDDFunctions(RDD<Tuple2<K, V>>, Ordering<K>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.rdd.RDD
 
rddToPairRDDFunctions(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>, Ordering<K>) - Static method in class org.apache.spark.rdd.RDD
 
rddToSequenceFileRDDFunctions(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>, <any>, <any>) - Static method in class org.apache.spark.rdd.RDD
 
read() - Method in class org.apache.spark.io.NioBufferedFileInputStream
 
read(byte[], int, int) - Method in class org.apache.spark.io.NioBufferedFileInputStream
 
read() - Method in class org.apache.spark.io.ReadAheadInputStream
 
read(byte[], int, int) - Method in class org.apache.spark.io.ReadAheadInputStream
 
read() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
 
read() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
 
read() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
 
read() - Static method in class org.apache.spark.ml.classification.GBTClassifier
 
read() - Static method in class org.apache.spark.ml.classification.LinearSVC
 
read() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
 
read() - Static method in class org.apache.spark.ml.classification.LogisticRegression
 
read() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
 
read() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
 
read() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
 
read() - Static method in class org.apache.spark.ml.classification.NaiveBayes
 
read() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
 
read() - Static method in class org.apache.spark.ml.classification.OneVsRest
 
read() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
 
read() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
 
read() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
 
read() - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
 
read() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
 
read() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
 
read() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
 
read() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
 
read() - Static method in class org.apache.spark.ml.clustering.KMeans
 
read() - Static method in class org.apache.spark.ml.clustering.KMeansModel
 
read() - Static method in class org.apache.spark.ml.clustering.LDA
 
read() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
 
read() - Static method in class org.apache.spark.ml.clustering.PowerIterationClustering
 
read() - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
 
read() - Static method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
read() - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
 
read() - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
 
read() - Static method in class org.apache.spark.ml.feature.Binarizer
 
read() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
 
read() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
 
read() - Static method in class org.apache.spark.ml.feature.Bucketizer
 
read() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
 
read() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
 
read() - Static method in class org.apache.spark.ml.feature.ColumnPruner
 
read() - Static method in class org.apache.spark.ml.feature.CountVectorizer
 
read() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
 
read() - Static method in class org.apache.spark.ml.feature.DCT
 
read() - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
 
read() - Static method in class org.apache.spark.ml.feature.FeatureHasher
 
read() - Static method in class org.apache.spark.ml.feature.HashingTF
 
read() - Static method in class org.apache.spark.ml.feature.IDF
 
read() - Static method in class org.apache.spark.ml.feature.IDFModel
 
read() - Static method in class org.apache.spark.ml.feature.Imputer
 
read() - Static method in class org.apache.spark.ml.feature.ImputerModel
 
read() - Static method in class org.apache.spark.ml.feature.IndexToString
 
read() - Static method in class org.apache.spark.ml.feature.Interaction
 
read() - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
 
read() - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
 
read() - Static method in class org.apache.spark.ml.feature.MinHashLSH
 
read() - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
 
read() - Static method in class org.apache.spark.ml.feature.MinMaxScaler
 
read() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
 
read() - Static method in class org.apache.spark.ml.feature.NGram
 
read() - Static method in class org.apache.spark.ml.feature.Normalizer
 
read() - Static method in class org.apache.spark.ml.feature.OneHotEncoder
Deprecated.
 
read() - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
 
read() - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
 
read() - Static method in class org.apache.spark.ml.feature.PCA
 
read() - Static method in class org.apache.spark.ml.feature.PCAModel
 
read() - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
 
read() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
read() - Static method in class org.apache.spark.ml.feature.RegexTokenizer
 
read() - Static method in class org.apache.spark.ml.feature.RFormula
 
read() - Static method in class org.apache.spark.ml.feature.RFormulaModel
 
read() - Static method in class org.apache.spark.ml.feature.SQLTransformer
 
read() - Static method in class org.apache.spark.ml.feature.StandardScaler
 
read() - Static method in class org.apache.spark.ml.feature.StandardScalerModel
 
read() - Static method in class org.apache.spark.ml.feature.StopWordsRemover
 
read() - Static method in class org.apache.spark.ml.feature.StringIndexer
 
read() - Static method in class org.apache.spark.ml.feature.StringIndexerModel
 
read() - Static method in class org.apache.spark.ml.feature.Tokenizer
 
read() - Static method in class org.apache.spark.ml.feature.VectorAssembler
 
read() - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
 
read() - Static method in class org.apache.spark.ml.feature.VectorIndexer
 
read() - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
 
read() - Static method in class org.apache.spark.ml.feature.VectorSizeHint
 
read() - Static method in class org.apache.spark.ml.feature.VectorSlicer
 
read() - Static method in class org.apache.spark.ml.feature.Word2Vec
 
read() - Static method in class org.apache.spark.ml.feature.Word2VecModel
 
read() - Static method in class org.apache.spark.ml.fpm.FPGrowth
 
read() - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
 
read() - Static method in class org.apache.spark.ml.Pipeline
 
read() - Static method in class org.apache.spark.ml.PipelineModel
 
read() - Static method in class org.apache.spark.ml.recommendation.ALS
 
read() - Static method in class org.apache.spark.ml.recommendation.ALSModel
 
read() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
 
read() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
read() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
 
read() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
 
read() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
 
read() - Static method in class org.apache.spark.ml.regression.GBTRegressor
 
read() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
 
read() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
 
read() - Static method in class org.apache.spark.ml.regression.IsotonicRegression
 
read() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
 
read() - Static method in class org.apache.spark.ml.regression.LinearRegression
 
read() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
 
read() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
 
read() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
 
read() - Static method in class org.apache.spark.ml.tuning.CrossValidator
 
read() - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
 
read() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
 
read() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
 
read() - Method in interface org.apache.spark.ml.util.DefaultParamsReadable
 
read() - Method in interface org.apache.spark.ml.util.MLReadable
Returns an MLReader instance for this class.
read(ByteBuffer) - Method in class org.apache.spark.security.CryptoStreamUtils.ErrorHandlingReadableChannel
 
read(Kryo, Input, Class<Iterable<?>>) - Method in class org.apache.spark.serializer.JavaIterableWrapperSerializer
 
read() - Method in class org.apache.spark.sql.SparkSession
Returns a DataFrameReader that can be used to read non-streaming data in as a DataFrame.
read() - Method in class org.apache.spark.sql.SQLContext
 
read() - Method in class org.apache.spark.storage.BufferReleasingInputStream
 
read(byte[]) - Method in class org.apache.spark.storage.BufferReleasingInputStream
 
read(byte[], int, int) - Method in class org.apache.spark.storage.BufferReleasingInputStream
 
read(String) - Static method in class org.apache.spark.streaming.CheckpointReader
Read checkpoint files present in the given checkpoint directory.
read(String, SparkConf, Configuration, boolean) - Static method in class org.apache.spark.streaming.CheckpointReader
Read checkpoint files present in the given checkpoint directory.
read(WriteAheadLogRecordHandle) - Method in class org.apache.spark.streaming.util.WriteAheadLog
Read a written record based on the given record handle.
ReadableChannelFileRegion - Class in org.apache.spark.storage
 
ReadableChannelFileRegion(ReadableByteChannel, long) - Constructor for class org.apache.spark.storage.ReadableChannelFileRegion
 
ReadAheadInputStream - Class in org.apache.spark.io
InputStream implementation which asynchronously reads ahead from the underlying input stream when specified amount of data has been read from the current buffer.
ReadAheadInputStream(InputStream, int) - Constructor for class org.apache.spark.io.ReadAheadInputStream
Creates a ReadAheadInputStream with the specified buffer size and read-ahead threshold
readAll() - Method in class org.apache.spark.streaming.util.WriteAheadLog
Read and return an iterator of all the records that have been written but not yet cleaned up.
readArray(DataInputStream, JVMObjectTracker) - Static method in class org.apache.spark.api.r.SerDe
 
readBoolean(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
 
readBooleanArr(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
 
readBytes(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
 
readBytes() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
 
readBytesArr(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
 
readDate(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
 
readDouble(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
 
readDoubleArr(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
 
readExternal(ObjectInput) - Method in class org.apache.spark.serializer.JavaSerializer
 
readExternal(ObjectInput) - Method in class org.apache.spark.storage.BlockManagerId
 
readExternal(ObjectInput) - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
 
readExternal(ObjectInput) - Method in class org.apache.spark.storage.StorageLevel
 
readFrom(ConfigReader) - Method in class org.apache.spark.internal.config.ConfigEntryWithDefault
 
readFrom(ConfigReader) - Method in class org.apache.spark.internal.config.ConfigEntryWithDefaultFunction
 
readFrom(ConfigReader) - Method in class org.apache.spark.internal.config.ConfigEntryWithDefaultString
 
readFrom(InputStream) - Static method in class org.apache.spark.util.sketch.BloomFilter
Reads in a BloomFilter from an input stream.
readFrom(InputStream) - Static method in class org.apache.spark.util.sketch.CountMinSketch
Reads in a CountMinSketch from an input stream.
readFrom(byte[]) - Static method in class org.apache.spark.util.sketch.CountMinSketch
Reads in a CountMinSketch from a byte array.
readImages(String) - Static method in class org.apache.spark.ml.image.ImageSchema
Deprecated.
use `spark.read.format("image").load(path)` and this `readImages` will be removed in 3.0.0. Since 2.4.0.
readImages(String, SparkSession, boolean, int, boolean, double, long) - Static method in class org.apache.spark.ml.image.ImageSchema
Deprecated.
use `spark.read.format("image").load(path)` and this `readImages` will be removed in 3.0.0. Since 2.4.0.
readInt(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
 
readIntArr(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
 
readKey(ClassTag<T>) - Method in class org.apache.spark.serializer.DeserializationStream
Reads the object representing the key of a key-value pair.
readList(DataInputStream, JVMObjectTracker) - Static method in class org.apache.spark.api.r.SerDe
 
readMap(DataInputStream, JVMObjectTracker) - Static method in class org.apache.spark.api.r.SerDe
 
readObject(DataInputStream, JVMObjectTracker) - Static method in class org.apache.spark.api.r.SerDe
 
readObject(ClassTag<T>) - Method in class org.apache.spark.serializer.DeserializationStream
The most general-purpose method to read an object.
readObjectType(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
 
readRecords() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
 
readSchema(Seq<String>, Option<Configuration>, boolean) - Static method in class org.apache.spark.sql.hive.orc.OrcFileOperator
 
readSchema() - Method in interface org.apache.spark.sql.sources.v2.reader.DataSourceReader
Returns the actual schema of this data source reader, which may be different from the physical schema of the underlying storage, as column pruning or other optimizations may happen.
readSqlObject(DataInputStream, char) - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
readStream() - Method in class org.apache.spark.sql.SparkSession
Returns a DataStreamReader that can be used to read streaming data in as a DataFrame.
readStream() - Method in class org.apache.spark.sql.SQLContext
 
readString(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
 
readStringArr(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
 
readStringBytes(DataInputStream, int) - Static method in class org.apache.spark.api.r.SerDe
 
ReadSupport - Interface in org.apache.spark.sql.sources.v2
A mix-in interface for DataSourceV2.
readTime(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
 
readTypedObject(DataInputStream, char, JVMObjectTracker) - Static method in class org.apache.spark.api.r.SerDe
 
readValue(ClassTag<T>) - Method in class org.apache.spark.serializer.DeserializationStream
Reads the object representing the value of a key-value pair.
ready(Duration, CanAwait) - Method in class org.apache.spark.ComplexFutureAction
 
ready(Duration, CanAwait) - Method in interface org.apache.spark.FutureAction
Blocks until this action completes.
ready(Duration, CanAwait) - Method in class org.apache.spark.SimpleFutureAction
 
reason() - Method in class org.apache.spark.ExecutorLostFailure
 
reason() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask
 
reason() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor
 
reason() - Method in class org.apache.spark.scheduler.local.KillTask
 
reason() - Method in class org.apache.spark.scheduler.SparkListenerExecutorRemoved
 
reason() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
 
reason() - Method in class org.apache.spark.TaskKilled
 
reason() - Method in exception org.apache.spark.TaskKilledException
 
Recall - Class in org.apache.spark.mllib.evaluation.binary
Recall.
Recall() - Constructor for class org.apache.spark.mllib.evaluation.binary.Recall
 
recall(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns recall for a given label (category)
recall() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Deprecated.
Use accuracy. Since 2.0.0.
recall() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
Returns document-based recall averaged by the number of documents
recall(double) - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
Returns recall for a given label (category)
recallByLabel() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns recall for each label (category).
recallByThreshold() - Method in interface org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
Returns a dataframe with two fields (threshold, recall) curve.
recallByThreshold() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
Returns the (threshold, recall) curve.
receive() - Method in interface org.apache.spark.rpc.RpcEndpoint
Process messages from RpcEndpointRef.send or RpcCallContext.reply.
receiveAndReply(RpcCallContext) - Method in interface org.apache.spark.rpc.RpcEndpoint
Process messages from RpcEndpointRef.ask.
ReceivedBlock - Interface in org.apache.spark.streaming.receiver
Trait representing a received block
ReceivedBlockHandler - Interface in org.apache.spark.streaming.receiver
Trait that represents a class that handles the storage of blocks received by receiver
ReceivedBlockStoreResult - Interface in org.apache.spark.streaming.receiver
Trait that represents the metadata related to storage of blocks
ReceivedBlockTrackerLogEvent - Interface in org.apache.spark.streaming.scheduler
Trait representing any event in the ReceivedBlockTracker that updates its state.
Receiver<T> - Class in org.apache.spark.streaming.receiver
:: DeveloperApi :: Abstract class of a receiver that can be run on worker nodes to receive external data.
Receiver(StorageLevel) - Constructor for class org.apache.spark.streaming.receiver.Receiver
 
RECEIVER_WAL_CLASS_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
RECEIVER_WAL_CLOSE_AFTER_WRITE_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
RECEIVER_WAL_ENABLE_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
RECEIVER_WAL_MAX_FAILURES_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
RECEIVER_WAL_ROLLING_INTERVAL_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
ReceiverInfo - Class in org.apache.spark.status.api.v1.streaming
 
ReceiverInfo - Class in org.apache.spark.streaming.scheduler
:: DeveloperApi :: Class having information about a receiver
ReceiverInfo(int, String, boolean, String, String, String, String, long) - Constructor for class org.apache.spark.streaming.scheduler.ReceiverInfo
 
receiverInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverError
 
receiverInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted
 
receiverInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStopped
 
receiverInputDStream() - Method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
 
receiverInputDStream() - Method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
 
ReceiverInputDStream<T> - Class in org.apache.spark.streaming.dstream
Abstract class for defining any InputDStream that has to start a receiver on worker nodes to receive external data.
ReceiverInputDStream(StreamingContext, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.ReceiverInputDStream
 
ReceiverMessage - Interface in org.apache.spark.streaming.receiver
Messages sent to the Receiver.
ReceiverState - Class in org.apache.spark.streaming.scheduler
Enumeration to identify current state of a Receiver
ReceiverState() - Constructor for class org.apache.spark.streaming.scheduler.ReceiverState
 
receiverStream(Receiver<T>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream with any arbitrary user implemented receiver.
receiverStream(Receiver<T>, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
Create an input stream with any arbitrary user implemented receiver.
ReceiverTrackerLocalMessage - Interface in org.apache.spark.streaming.scheduler
Messages used by the driver and ReceiverTrackerEndpoint to communicate locally.
ReceiverTrackerMessage - Interface in org.apache.spark.streaming.scheduler
Messages used by the NetworkReceiver and the ReceiverTracker to communicate with each other.
recentProgress() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Returns an array of the most recent StreamingQueryProgress updates for this query.
recommendForAllItems(int) - Method in class org.apache.spark.ml.recommendation.ALSModel
Returns top numUsers users recommended for each item, for all items.
recommendForAllUsers(int) - Method in class org.apache.spark.ml.recommendation.ALSModel
Returns top numItems items recommended for each user, for all users.
recommendForItemSubset(Dataset<?>, int) - Method in class org.apache.spark.ml.recommendation.ALSModel
Returns top numUsers users recommended for each item id in the input data set.
recommendForUserSubset(Dataset<?>, int) - Method in class org.apache.spark.ml.recommendation.ALSModel
Returns top numItems items recommended for each user id in the input data set.
recommendProducts(int, int) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
Recommends products to a user.
recommendProductsForUsers(int) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
Recommends top products for all users.
recommendUsers(int, int) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
Recommends users to a product.
recommendUsersForProducts(int) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
Recommends top users for all products.
recordReader(InputStream, Configuration) - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
recordReaderClass() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
RECORDS_BETWEEN_BYTES_READ_METRIC_UPDATES() - Static method in class org.apache.spark.rdd.HadoopRDD
Update the input bytes read metric each time this number of records has been read
RECORDS_READ() - Method in class org.apache.spark.InternalAccumulator.input$
 
RECORDS_READ() - Method in class org.apache.spark.InternalAccumulator.shuffleRead$
 
RECORDS_WRITTEN() - Method in class org.apache.spark.InternalAccumulator.output$
 
RECORDS_WRITTEN() - Method in class org.apache.spark.InternalAccumulator.shuffleWrite$
 
recordsRead() - Method in class org.apache.spark.status.api.v1.InputMetricDistributions
 
recordsRead() - Method in class org.apache.spark.status.api.v1.InputMetrics
 
recordsRead() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
 
recordsWritten() - Method in class org.apache.spark.status.api.v1.OutputMetricDistributions
 
recordsWritten() - Method in class org.apache.spark.status.api.v1.OutputMetrics
 
recordsWritten() - Method in class org.apache.spark.status.api.v1.ShuffleWriteMetrics
 
recordWriter(OutputStream, Configuration) - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
recordWriterClass() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
recoverPartitions(String) - Method in class org.apache.spark.sql.catalog.Catalog
Recovers all the partitions in the directory of a table and update the catalog.
RecursiveFlag - Class in org.apache.spark.ml.image
 
RecursiveFlag() - Constructor for class org.apache.spark.ml.image.RecursiveFlag
 
recursiveList(File) - Static method in class org.apache.spark.TestUtils
Lists files recursively.
redact(SparkConf, Seq<Tuple2<String, String>>) - Static method in class org.apache.spark.util.Utils
Redact the sensitive values in the given map.
redact(Option<Regex>, Seq<Tuple2<String, String>>) - Static method in class org.apache.spark.util.Utils
Redact the sensitive values in the given map.
redact(Option<Regex>, String) - Static method in class org.apache.spark.util.Utils
Redact the sensitive information in the given string.
redact(Map<String, String>) - Static method in class org.apache.spark.util.Utils
Looks up the redaction regex from within the key value pairs and uses it to redact the rest of the key value pairs.
REDIRECT_CONNECTOR_NAME() - Static method in class org.apache.spark.ui.JettyUtils
 
redirectableStream() - Method in class org.apache.spark.storage.memory.SerializedValuesHolder
 
redirectError() - Method in class org.apache.spark.launcher.SparkLauncher
Specifies that stderr in spark-submit should be redirected to stdout.
redirectError(ProcessBuilder.Redirect) - Method in class org.apache.spark.launcher.SparkLauncher
Redirects error output to the specified Redirect.
redirectError(File) - Method in class org.apache.spark.launcher.SparkLauncher
Redirects error output to the specified File.
redirectOutput(ProcessBuilder.Redirect) - Method in class org.apache.spark.launcher.SparkLauncher
Redirects standard output to the specified Redirect.
redirectOutput(File) - Method in class org.apache.spark.launcher.SparkLauncher
Redirects error output to the specified File.
redirectToLog(String) - Method in class org.apache.spark.launcher.SparkLauncher
Sets all output to be logged and redirected to a logger with the specified name.
reduce(Function2<T, T, T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Reduces the elements of this RDD using the specified commutative and associative binary operator.
reduce(Function2<T, T, T>) - Method in class org.apache.spark.rdd.RDD
Reduces the elements of this RDD using the specified commutative and associative binary operator.
reduce(Function2<T, T, T>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: (Scala-specific) Reduces the elements of this Dataset using the specified binary function.
reduce(ReduceFunction<T>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: (Java-specific) Reduces the elements of this Dataset using the specified binary function.
reduce(BUF, IN) - Method in class org.apache.spark.sql.expressions.Aggregator
Combine two values to produce a new value.
reduce(Function2<T, T, T>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD has a single element generated by reducing each RDD of this DStream.
reduce(Function2<T, T, T>) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD has a single element generated by reducing each RDD of this DStream.
reduceByKey(Partitioner, Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
Merge the values for each key using an associative and commutative reduce function.
reduceByKey(Function2<V, V, V>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
Merge the values for each key using an associative and commutative reduce function.
reduceByKey(Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
Merge the values for each key using an associative and commutative reduce function.
reduceByKey(Partitioner, Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Merge the values for each key using an associative and commutative reduce function.
reduceByKey(Function2<V, V, V>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
Merge the values for each key using an associative and commutative reduce function.
reduceByKey(Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Merge the values for each key using an associative and commutative reduce function.
reduceByKey(Function2<V, V, V>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying reduceByKey to each RDD.
reduceByKey(Function2<V, V, V>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying reduceByKey to each RDD.
reduceByKey(Function2<V, V, V>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying reduceByKey to each RDD.
reduceByKey(Function2<V, V, V>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying reduceByKey to each RDD.
reduceByKey(Function2<V, V, V>, int) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying reduceByKey to each RDD.
reduceByKey(Function2<V, V, V>, Partitioner) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying reduceByKey to each RDD.
reduceByKeyAndWindow(Function2<V, V, V>, Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Create a new DStream by applying reduceByKey over a sliding window on this DStream.
reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying reduceByKey over a sliding window.
reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying reduceByKey over a sliding window.
reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying reduceByKey over a sliding window.
reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by reducing over a using incremental computation.
reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, int, Function<Tuple2<K, V>, Boolean>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying incremental reduceByKey over a sliding window.
reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, Partitioner, Function<Tuple2<K, V>, Boolean>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying incremental reduceByKey over a sliding window.
reduceByKeyAndWindow(Function2<V, V, V>, Duration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying reduceByKey over a sliding window on this DStream.
reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying reduceByKey over a sliding window.
reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, int) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying reduceByKey over a sliding window.
reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, Partitioner) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying reduceByKey over a sliding window.
reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, int, Function1<Tuple2<K, V>, Object>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying incremental reduceByKey over a sliding window.
reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, Partitioner, Function1<Tuple2<K, V>, Object>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying incremental reduceByKey over a sliding window.
reduceByKeyLocally(Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
Merge the values for each key using an associative and commutative reduce function, but return the result immediately to the master as a Map.
reduceByKeyLocally(Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Merge the values for each key using an associative and commutative reduce function, but return the results immediately to the master as a Map.
reduceByWindow(Function2<T, T, T>, Duration, Duration) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD has a single element generated by reducing all elements in a sliding window over this DStream.
reduceByWindow(Function2<T, T, T>, Function2<T, T, T>, Duration, Duration) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD has a single element generated by reducing all elements in a sliding window over this DStream.
reduceByWindow(Function2<T, T, T>, Duration, Duration) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD has a single element generated by reducing all elements in a sliding window over this DStream.
reduceByWindow(Function2<T, T, T>, Function2<T, T, T>, Duration, Duration) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD has a single element generated by reducing all elements in a sliding window over this DStream.
ReduceFunction<T> - Interface in org.apache.spark.api.java.function
Base interface for function used in Dataset's reduce.
reduceGroups(Function2<V, V, V>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
(Scala-specific) Reduces the elements of each group of data using the specified binary function.
reduceGroups(ReduceFunction<V>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
(Java-specific) Reduces the elements of each group of data using the specified binary function.
reduceId() - Method in class org.apache.spark.FetchFailed
 
reduceId() - Method in class org.apache.spark.storage.ShuffleBlockId
 
reduceId() - Method in class org.apache.spark.storage.ShuffleDataBlockId
 
reduceId() - Method in class org.apache.spark.storage.ShuffleIndexBlockId
 
references() - Method in class org.apache.spark.sql.sources.And
 
references() - Method in class org.apache.spark.sql.sources.EqualNullSafe
 
references() - Method in class org.apache.spark.sql.sources.EqualTo
 
references() - Method in class org.apache.spark.sql.sources.Filter
List of columns that are referenced by this filter.
references() - Method in class org.apache.spark.sql.sources.GreaterThan
 
references() - Method in class org.apache.spark.sql.sources.GreaterThanOrEqual
 
references() - Method in class org.apache.spark.sql.sources.In
 
references() - Method in class org.apache.spark.sql.sources.IsNotNull
 
references() - Method in class org.apache.spark.sql.sources.IsNull
 
references() - Method in class org.apache.spark.sql.sources.LessThan
 
references() - Method in class org.apache.spark.sql.sources.LessThanOrEqual
 
references() - Method in class org.apache.spark.sql.sources.Not
 
references() - Method in class org.apache.spark.sql.sources.Or
 
references() - Method in class org.apache.spark.sql.sources.StringContains
 
references() - Method in class org.apache.spark.sql.sources.StringEndsWith
 
references() - Method in class org.apache.spark.sql.sources.StringStartsWith
 
refreshByPath(String) - Method in class org.apache.spark.sql.catalog.Catalog
Invalidates and refreshes all the cached data (and the associated metadata) for any Dataset that contains the given data source path.
refreshTable(String) - Method in class org.apache.spark.sql.catalog.Catalog
Invalidates and refreshes all the cached data and metadata of the given table.
refreshTable(String) - Method in class org.apache.spark.sql.hive.HiveContext
Deprecated.
Invalidate and refresh all the cached the metadata of the given table.
regex(Regex) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
regexFromString(String, String) - Static method in class org.apache.spark.internal.config.ConfigHelpers
 
regexp_extract(Column, String, int) - Static method in class org.apache.spark.sql.functions
Extract a specific group matched by a Java regex, from the specified string column.
regexp_replace(Column, String, String) - Static method in class org.apache.spark.sql.functions
Replace all substrings of the specified string value that match regexp with rep.
regexp_replace(Column, Column, Column) - Static method in class org.apache.spark.sql.functions
Replace all substrings of the specified string value that match regexp with rep.
RegexTokenizer - Class in org.apache.spark.ml.feature
A regex based tokenizer that extracts tokens either by using the provided regex pattern to split the text (default) or repeatedly matching the regex (if gaps is false).
RegexTokenizer(String) - Constructor for class org.apache.spark.ml.feature.RegexTokenizer
 
RegexTokenizer() - Constructor for class org.apache.spark.ml.feature.RegexTokenizer
 
register(AccumulatorV2<?, ?>) - Method in class org.apache.spark.SparkContext
Register the given accumulator.
register(AccumulatorV2<?, ?>, String) - Method in class org.apache.spark.SparkContext
Register the given accumulator with given name.
register(String, String) - Static method in class org.apache.spark.sql.types.UDTRegistration
Registers an UserDefinedType to an user class.
register(String, UserDefinedAggregateFunction) - Method in class org.apache.spark.sql.UDFRegistration
Registers a user-defined aggregate function (UDAF).
register(String, UserDefinedFunction) - Method in class org.apache.spark.sql.UDFRegistration
Registers a user-defined function (UDF), for a UDF that's already defined using the Dataset API (i.e.
register(String, Function0<RT>, TypeTags.TypeTag<RT>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 0 arguments as user-defined function (UDF).
register(String, Function1<A1, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 1 arguments as user-defined function (UDF).
register(String, Function2<A1, A2, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 2 arguments as user-defined function (UDF).
register(String, Function3<A1, A2, A3, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 3 arguments as user-defined function (UDF).
register(String, Function4<A1, A2, A3, A4, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 4 arguments as user-defined function (UDF).
register(String, Function5<A1, A2, A3, A4, A5, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 5 arguments as user-defined function (UDF).
register(String, Function6<A1, A2, A3, A4, A5, A6, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 6 arguments as user-defined function (UDF).
register(String, Function7<A1, A2, A3, A4, A5, A6, A7, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 7 arguments as user-defined function (UDF).
register(String, Function8<A1, A2, A3, A4, A5, A6, A7, A8, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 8 arguments as user-defined function (UDF).
register(String, Function9<A1, A2, A3, A4, A5, A6, A7, A8, A9, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 9 arguments as user-defined function (UDF).
register(String, Function10<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 10 arguments as user-defined function (UDF).
register(String, Function11<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 11 arguments as user-defined function (UDF).
register(String, Function12<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 12 arguments as user-defined function (UDF).
register(String, Function13<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 13 arguments as user-defined function (UDF).
register(String, Function14<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 14 arguments as user-defined function (UDF).
register(String, Function15<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 15 arguments as user-defined function (UDF).
register(String, Function16<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 16 arguments as user-defined function (UDF).
register(String, Function17<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>, TypeTags.TypeTag<A17>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 17 arguments as user-defined function (UDF).
register(String, Function18<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>, TypeTags.TypeTag<A17>, TypeTags.TypeTag<A18>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 18 arguments as user-defined function (UDF).
register(String, Function19<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>, TypeTags.TypeTag<A17>, TypeTags.TypeTag<A18>, TypeTags.TypeTag<A19>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 19 arguments as user-defined function (UDF).
register(String, Function20<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, A20, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>, TypeTags.TypeTag<A17>, TypeTags.TypeTag<A18>, TypeTags.TypeTag<A19>, TypeTags.TypeTag<A20>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 20 arguments as user-defined function (UDF).
register(String, Function21<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, A20, A21, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>, TypeTags.TypeTag<A17>, TypeTags.TypeTag<A18>, TypeTags.TypeTag<A19>, TypeTags.TypeTag<A20>, TypeTags.TypeTag<A21>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 21 arguments as user-defined function (UDF).
register(String, Function22<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, A20, A21, A22, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>, TypeTags.TypeTag<A17>, TypeTags.TypeTag<A18>, TypeTags.TypeTag<A19>, TypeTags.TypeTag<A20>, TypeTags.TypeTag<A21>, TypeTags.TypeTag<A22>) - Method in class org.apache.spark.sql.UDFRegistration
Registers a deterministic Scala closure of 22 arguments as user-defined function (UDF).
register(String, UDF0<?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF0 instance as user-defined function (UDF).
register(String, UDF1<?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF1 instance as user-defined function (UDF).
register(String, UDF2<?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF2 instance as user-defined function (UDF).
register(String, UDF3<?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF3 instance as user-defined function (UDF).
register(String, UDF4<?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF4 instance as user-defined function (UDF).
register(String, UDF5<?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF5 instance as user-defined function (UDF).
register(String, UDF6<?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF6 instance as user-defined function (UDF).
register(String, UDF7<?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF7 instance as user-defined function (UDF).
register(String, UDF8<?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF8 instance as user-defined function (UDF).
register(String, UDF9<?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF9 instance as user-defined function (UDF).
register(String, UDF10<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF10 instance as user-defined function (UDF).
register(String, UDF11<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF11 instance as user-defined function (UDF).
register(String, UDF12<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF12 instance as user-defined function (UDF).
register(String, UDF13<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF13 instance as user-defined function (UDF).
register(String, UDF14<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF14 instance as user-defined function (UDF).
register(String, UDF15<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF15 instance as user-defined function (UDF).
register(String, UDF16<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF16 instance as user-defined function (UDF).
register(String, UDF17<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF17 instance as user-defined function (UDF).
register(String, UDF18<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF18 instance as user-defined function (UDF).
register(String, UDF19<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF19 instance as user-defined function (UDF).
register(String, UDF20<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF20 instance as user-defined function (UDF).
register(String, UDF21<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF21 instance as user-defined function (UDF).
register(String, UDF22<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
Register a deterministic Java UDF22 instance as user-defined function (UDF).
register(QueryExecutionListener) - Method in class org.apache.spark.sql.util.ExecutionListenerManager
Registers the specified QueryExecutionListener.
register(AccumulatorV2<?, ?>) - Static method in class org.apache.spark.util.AccumulatorContext
Registers an AccumulatorV2 created on the driver such that it can be used on the executors.
register(String, Function0<Object>) - Static method in class org.apache.spark.util.SignalUtils
Adds an action to be run when a given signal is received by this process.
registerAvroSchemas(Seq<Schema>) - Method in class org.apache.spark.SparkConf
Use Kryo serialization and register the given set of Avro schemas so that the generic record serializer can decrease network IO
RegisterBlockManager(BlockManagerId, long, long, org.apache.spark.rpc.RpcEndpointRef) - Constructor for class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager
 
RegisterBlockManager$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager$
 
registerClasses(Kryo) - Method in interface org.apache.spark.serializer.KryoRegistrator
 
RegisterClusterManager(org.apache.spark.rpc.RpcEndpointRef) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterClusterManager
 
RegisterClusterManager$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterClusterManager$
 
registerDialect(JdbcDialect) - Static method in class org.apache.spark.sql.jdbc.JdbcDialects
Register a dialect for use on all new matching jdbc org.apache.spark.sql.DataFrame.
RegisteredExecutor$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisteredExecutor$
 
RegisterExecutor(String, org.apache.spark.rpc.RpcEndpointRef, String, int, Map<String, String>) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor
 
RegisterExecutor$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor$
 
RegisterExecutorFailed(String) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutorFailed
 
RegisterExecutorFailed$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutorFailed$
 
registerKryoClasses(SparkConf) - Static method in class org.apache.spark.graphx.GraphXUtils
Registers classes that GraphX uses with Kryo.
registerKryoClasses(SparkContext) - Static method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette
This method registers the class SquaredEuclideanSilhouette.ClusterStats for kryo serialization.
registerKryoClasses(Class<?>[]) - Method in class org.apache.spark.SparkConf
Use Kryo serialization and register the given set of classes with Kryo.
registerLogger(Logger) - Static method in class org.apache.spark.util.SignalUtils
Register a signal handler to log signals on UNIX-like systems.
registerShutdownDeleteDir(File) - Static method in class org.apache.spark.util.ShutdownHookManager
 
registerStream(DStream<BinarySample>) - Method in class org.apache.spark.mllib.stat.test.StreamingTest
Register a DStream of values for significance testing.
registerStream(JavaDStream<BinarySample>) - Method in class org.apache.spark.mllib.stat.test.StreamingTest
Register a JavaDStream of values for significance testing.
registerTempTable(String) - Method in class org.apache.spark.sql.Dataset
Deprecated.
Use createOrReplaceTempView(viewName) instead. Since 2.0.0.
regParam() - Method in interface org.apache.spark.ml.optim.loss.DifferentiableRegularization
Magnitude of the regularization penalty.
regParam() - Method in interface org.apache.spark.ml.param.shared.HasRegParam
Param for regularization parameter (&gt;= 0).
Regression() - Static method in class org.apache.spark.mllib.tree.configuration.Algo
 
RegressionEvaluator - Class in org.apache.spark.ml.evaluation
:: Experimental :: Evaluator for regression, which expects two input columns: prediction and label.
RegressionEvaluator(String) - Constructor for class org.apache.spark.ml.evaluation.RegressionEvaluator
 
RegressionEvaluator() - Constructor for class org.apache.spark.ml.evaluation.RegressionEvaluator
 
RegressionMetrics - Class in org.apache.spark.mllib.evaluation
Evaluator for regression.
RegressionMetrics(RDD<Tuple2<Object, Object>>, boolean) - Constructor for class org.apache.spark.mllib.evaluation.RegressionMetrics
 
RegressionMetrics(RDD<Tuple2<Object, Object>>) - Constructor for class org.apache.spark.mllib.evaluation.RegressionMetrics
 
RegressionModel<FeaturesType,M extends RegressionModel<FeaturesType,M>> - Class in org.apache.spark.ml.regression
:: DeveloperApi ::
RegressionModel() - Constructor for class org.apache.spark.ml.regression.RegressionModel
 
RegressionModel - Interface in org.apache.spark.mllib.regression
 
reindex() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
reindex() - Method in class org.apache.spark.graphx.VertexRDD
Construct a new VertexRDD that is indexed by only the visible vertices.
RelationalGroupedDataset - Class in org.apache.spark.sql
A set of methods for aggregations on a DataFrame, created by groupBy, cube or rollup (and also pivot).
RelationalGroupedDataset.CubeType$ - Class in org.apache.spark.sql
To indicate it's the CUBE
RelationalGroupedDataset.GroupByType$ - Class in org.apache.spark.sql
To indicate it's the GroupBy
RelationalGroupedDataset.GroupType - Interface in org.apache.spark.sql
The Grouping Type
RelationalGroupedDataset.PivotType$ - Class in org.apache.spark.sql
 
RelationalGroupedDataset.RollupType$ - Class in org.apache.spark.sql
To indicate it's the ROLLUP
RelationConversions - Class in org.apache.spark.sql.hive
Relation conversion from metastore relations to data source relations for better performance
RelationConversions(SQLConf, HiveSessionCatalog) - Constructor for class org.apache.spark.sql.hive.RelationConversions
 
RelationProvider - Interface in org.apache.spark.sql.sources
Implemented by objects that produce relations for a specific kind of data source.
relativeDirection(long) - Method in class org.apache.spark.graphx.Edge
Return the relative direction of the edge to the corresponding vertex.
relativeError() - Method in interface org.apache.spark.ml.feature.QuantileDiscretizerBase
Relative error (see documentation for org.apache.spark.sql.DataFrameStatFunctions.approxQuantile for description) Must be in the range [0, 1].
relativeError() - Method in class org.apache.spark.util.sketch.CountMinSketch
Returns the relative error (or eps) of this CountMinSketch.
rem(Decimal, Decimal) - Method in class org.apache.spark.sql.types.Decimal.DecimalAsIfIntegral$
 
remainder(Decimal) - Method in class org.apache.spark.sql.types.Decimal
 
remember(Duration) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Sets each DStreams in this context to remember RDDs it generated in the last given duration.
remember(Duration) - Method in class org.apache.spark.streaming.StreamingContext
Set each DStream in this context to remember RDDs it generated in the last given duration.
REMOTE_BLOCKS_FETCHED() - Method in class org.apache.spark.InternalAccumulator.shuffleRead$
 
REMOTE_BYTES_READ() - Method in class org.apache.spark.InternalAccumulator.shuffleRead$
 
REMOTE_BYTES_READ_TO_DISK() - Method in class org.apache.spark.InternalAccumulator.shuffleRead$
 
remoteBlocksFetched() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
 
remoteBlocksFetched() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
 
remoteBytesRead() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
 
remoteBytesRead() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
 
remoteBytesReadToDisk() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
 
remoteBytesReadToDisk() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
 
remove(Param<T>) - Method in class org.apache.spark.ml.param.ParamMap
Removes a key from this map and returns its value associated previously as an option.
remove(String) - Method in class org.apache.spark.SparkConf
Remove a parameter from the configuration
remove() - Method in interface org.apache.spark.sql.streaming.GroupState
Remove this state.
remove(String) - Method in class org.apache.spark.sql.types.MetadataBuilder
 
remove() - Method in class org.apache.spark.streaming.State
Remove the state if it exists.
remove(long) - Static method in class org.apache.spark.util.AccumulatorContext
Unregisters the AccumulatorV2 with the given ID, if any.
RemoveBlock(BlockId) - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveBlock
 
RemoveBlock$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveBlock$
 
RemoveBroadcast(long, boolean) - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveBroadcast
 
RemoveBroadcast$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveBroadcast$
 
removeDistribution(LiveExecutor) - Method in class org.apache.spark.status.LiveRDD
 
RemoveExecutor(String, org.apache.spark.scheduler.ExecutorLossReason) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor
 
RemoveExecutor(String) - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveExecutor
 
RemoveExecutor$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor$
 
RemoveExecutor$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveExecutor$
 
removeFromDriver() - Method in class org.apache.spark.storage.BlockManagerMessages.RemoveBroadcast
 
removeListener(StreamingQueryListener) - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
removeListener(L) - Method in interface org.apache.spark.util.ListenerBus
Remove a listener and it won't receive any events.
removeListenerOnError(SparkListenerInterface) - Method in class org.apache.spark.scheduler.AsyncEventQueue
 
removeListenerOnError(L) - Method in interface org.apache.spark.util.ListenerBus
This can be overridden by subclasses if there is any extra cleanup to do when removing a listener.
removeMapOutput(int, BlockManagerId) - Method in class org.apache.spark.ShuffleStatus
Remove the map output which was served by the specified block manager.
removeOutputsByFilter(Function1<BlockManagerId, Object>) - Method in class org.apache.spark.ShuffleStatus
Removes all shuffle outputs which satisfies the filter.
removeOutputsOnExecutor(String) - Method in class org.apache.spark.ShuffleStatus
Removes all map outputs associated with the specified executor.
removeOutputsOnHost(String) - Method in class org.apache.spark.ShuffleStatus
Removes all shuffle outputs associated with this host.
removePartition(String) - Method in class org.apache.spark.status.LiveRDD
 
removePartition(LiveRDDPartition) - Method in class org.apache.spark.status.RDDPartitionSeq
 
RemoveRdd(int) - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveRdd
 
RemoveRdd$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveRdd$
 
removeReason() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
removeReason() - Method in class org.apache.spark.status.LiveExecutor
 
removeSchedulable(Schedulable) - Method in interface org.apache.spark.scheduler.Schedulable
 
removeSelfEdges() - Method in class org.apache.spark.graphx.GraphOps
Remove self edges.
RemoveShuffle(int) - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveShuffle
 
RemoveShuffle$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveShuffle$
 
removeShutdownDeleteDir(File) - Static method in class org.apache.spark.util.ShutdownHookManager
 
removeShutdownHook(Object) - Static method in class org.apache.spark.util.ShutdownHookManager
Remove a previously installed shutdown hook.
removeSparkListener(SparkListenerInterface) - Method in class org.apache.spark.SparkContext
:: DeveloperApi :: Deregister the listener from Spark's listener bus.
removeStreamingListener(StreamingListener) - Method in class org.apache.spark.streaming.StreamingContext
 
removeTime() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
removeTime() - Method in class org.apache.spark.status.LiveExecutor
 
RemoveWorker(String, String, String) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveWorker
 
RemoveWorker$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveWorker$
 
renameFunction(String, String, String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Rename an existing function in the database.
renamePartitions(String, String, Seq<Map<String, String>>, Seq<Map<String, String>>) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Rename one or many existing table partitions, assuming they exist.
rep(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
rep1(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
rep1(Function0<Parsers.Parser<T>>, Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
rep1sep(Function0<Parsers.Parser<T>>, Function0<Parsers.Parser<Object>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
repartition(int) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return a new RDD that has exactly numPartitions partitions.
repartition(int) - Method in class org.apache.spark.api.java.JavaPairRDD
Return a new RDD that has exactly numPartitions partitions.
repartition(int) - Method in class org.apache.spark.api.java.JavaRDD
Return a new RDD that has exactly numPartitions partitions.
repartition(int, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
Return a new RDD that has exactly numPartitions partitions.
repartition(int, Column...) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset partitioned by the given partitioning expressions into numPartitions.
repartition(Column...) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset partitioned by the given partitioning expressions, using spark.sql.shuffle.partitions as number of partitions.
repartition(int) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset that has exactly numPartitions partitions.
repartition(int, Seq<Column>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset partitioned by the given partitioning expressions into numPartitions.
repartition(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset partitioned by the given partitioning expressions, using spark.sql.shuffle.partitions as number of partitions.
repartition(int) - Method in class org.apache.spark.streaming.api.java.JavaDStream
Return a new DStream with an increased or decreased level of parallelism.
repartition(int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream with an increased or decreased level of parallelism.
repartition(int) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream with an increased or decreased level of parallelism.
repartitionAndSortWithinPartitions(Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
Repartition the RDD according to the given partitioner and, within each resulting partition, sort records by their keys.
repartitionAndSortWithinPartitions(Partitioner, Comparator<K>) - Method in class org.apache.spark.api.java.JavaPairRDD
Repartition the RDD according to the given partitioner and, within each resulting partition, sort records by their keys.
repartitionAndSortWithinPartitions(Partitioner) - Method in class org.apache.spark.rdd.OrderedRDDFunctions
Repartition the RDD according to the given partitioner and, within each resulting partition, sort records by their keys.
repartitionByRange(int, Column...) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset partitioned by the given partitioning expressions into numPartitions.
repartitionByRange(Column...) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset partitioned by the given partitioning expressions, using spark.sql.shuffle.partitions as number of partitions.
repartitionByRange(int, Seq<Column>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset partitioned by the given partitioning expressions into numPartitions.
repartitionByRange(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset partitioned by the given partitioning expressions, using spark.sql.shuffle.partitions as number of partitions.
repeat(Column, int) - Static method in class org.apache.spark.sql.functions
Repeats a string column n times, and returns it as a new string column.
replace(String, Map<T, T>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Replaces values matching keys in replacement map with the corresponding values.
replace(String[], Map<T, T>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
Replaces values matching keys in replacement map with the corresponding values.
replace(String, Map<T, T>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
(Scala-specific) Replaces values matching keys in replacement map.
replace(Seq<String>, Map<T, T>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
(Scala-specific) Replaces values matching keys in replacement map.
replaceCharType(DataType) - Static method in class org.apache.spark.sql.types.HiveStringType
 
replicas() - Method in class org.apache.spark.storage.BlockManagerMessages.ReplicateBlock
 
ReplicateBlock(BlockId, Seq<BlockManagerId>, int) - Constructor for class org.apache.spark.storage.BlockManagerMessages.ReplicateBlock
 
ReplicateBlock$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.ReplicateBlock$
 
replicatedVertexView() - Method in class org.apache.spark.graphx.impl.GraphImpl
 
replication() - Method in class org.apache.spark.storage.StorageLevel
 
reply(Object) - Method in interface org.apache.spark.rpc.RpcCallContext
Reply a message to the sender.
repN(int, Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
report() - Method in interface org.apache.spark.metrics.sink.Sink
 
reportError(String, Throwable) - Method in class org.apache.spark.streaming.receiver.Receiver
Report exceptions in receiving data.
repsep(Function0<Parsers.Parser<T>>, Function0<Parsers.Parser<Object>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
requestedTotal() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors
 
requestExecutors(int) - Method in interface org.apache.spark.ExecutorAllocationClient
Request an additional number of executors from the cluster manager.
RequestExecutors(int, int, Map<String, Object>, Set<String>) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors
 
requestExecutors(int) - Method in class org.apache.spark.SparkContext
:: DeveloperApi :: Request an additional number of executors from the cluster manager.
RequestExecutors$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors$
 
requestTotalExecutors(int, int, Map<String, Object>) - Method in interface org.apache.spark.ExecutorAllocationClient
Update the cluster manager on our scheduling needs.
requestTotalExecutors(int, int, Map<String, Object>) - Method in class org.apache.spark.SparkContext
Update the cluster manager on our scheduling needs.
res() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
 
reservoirSampleAndCount(Iterator<T>, int, long, ClassTag<T>) - Static method in class org.apache.spark.util.random.SamplingUtils
Reservoir sampling implementation that also returns the input size.
reset() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
Resets the values of all metrics to zero.
reset() - Method in interface org.apache.spark.sql.hive.client.HiveClient
Used for testing only.
reset() - Method in class org.apache.spark.storage.BufferReleasingInputStream
 
reset() - Method in class org.apache.spark.util.AccumulatorV2
Resets this accumulator, which is zero value.
reset() - Method in class org.apache.spark.util.CollectionAccumulator
 
reset() - Method in class org.apache.spark.util.DoubleAccumulator
 
reset() - Method in class org.apache.spark.util.LegacyAccumulatorWrapper
 
reset() - Method in class org.apache.spark.util.LongAccumulator
 
resetTerminated() - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
Forget about past terminated queries so that awaitAnyTermination() can be used again to wait for new terminations.
residualDegreeOfFreedom() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
The residual degrees of freedom.
residualDegreeOfFreedomNull() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
The residual degrees of freedom for the null model.
residuals() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
Get the default residuals (deviance residuals) of the fitted model.
residuals(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
Get the residuals of the fitted model by type.
residuals() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
Residuals (label - predicted value)
ResolveHiveSerdeTable - Class in org.apache.spark.sql.hive
Determine the database, serde/format and schema of the Hive serde table, according to the storage properties.
ResolveHiveSerdeTable(SparkSession) - Constructor for class org.apache.spark.sql.hive.ResolveHiveSerdeTable
 
resolveURI(String) - Static method in class org.apache.spark.util.Utils
Return a well-formed URI for the file described by a user input string.
resolveURIs(String) - Static method in class org.apache.spark.util.Utils
Resolve a comma-separated list of paths.
responder() - Method in class org.apache.spark.ui.JettyUtils.ServletParams
 
responseFromBackup(String) - Static method in class org.apache.spark.util.Utils
Return true if the response message is sent from a backup Master on standby.
restart(String) - Method in class org.apache.spark.streaming.receiver.Receiver
Restart the receiver.
restart(String, Throwable) - Method in class org.apache.spark.streaming.receiver.Receiver
Restart the receiver.
restart(String, Throwable, int) - Method in class org.apache.spark.streaming.receiver.Receiver
Restart the receiver.
ResubmitFailedStages - Class in org.apache.spark.scheduler
 
ResubmitFailedStages() - Constructor for class org.apache.spark.scheduler.ResubmitFailedStages
 
Resubmitted - Class in org.apache.spark
:: DeveloperApi :: A org.apache.spark.scheduler.ShuffleMapTask that completed successfully earlier, but we lost the executor before the stage completed.
Resubmitted() - Constructor for class org.apache.spark.Resubmitted
 
result(Duration, CanAwait) - Method in class org.apache.spark.ComplexFutureAction
 
result(Duration, CanAwait) - Method in interface org.apache.spark.FutureAction
Awaits and returns the result (of type T) of this action.
result(Duration, CanAwait) - Method in class org.apache.spark.SimpleFutureAction
 
RESULT_SERIALIZATION_TIME() - Static method in class org.apache.spark.InternalAccumulator
 
RESULT_SERIALIZATION_TIME() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
 
RESULT_SERIALIZATION_TIME() - Static method in class org.apache.spark.ui.ToolTips
 
RESULT_SIZE() - Static method in class org.apache.spark.InternalAccumulator
 
RESULT_SIZE() - Static method in class org.apache.spark.status.TaskIndexNames
 
resultFetchStart() - Method in class org.apache.spark.status.api.v1.TaskData
 
resultSerializationTime() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
resultSerializationTime() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 
resultSetToObjectArray(ResultSet) - Static method in class org.apache.spark.rdd.JdbcRDD
 
resultSize() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
resultSize() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 
RetrieveLastAllocatedExecutorId$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RetrieveLastAllocatedExecutorId$
 
RetrieveSparkAppConfig$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RetrieveSparkAppConfig$
 
retryWaitMs(SparkConf) - Static method in class org.apache.spark.util.RpcUtils
Returns the configured number of milliseconds to wait on each retry
ReturnStatementFinder - Class in org.apache.spark.util
 
ReturnStatementFinder(Option<String>) - Constructor for class org.apache.spark.util.ReturnStatementFinder
 
reverse() - Method in class org.apache.spark.graphx.EdgeDirection
Reverse the direction of an edge.
reverse() - Method in class org.apache.spark.graphx.EdgeRDD
Reverse all the edges in this RDD.
reverse() - Method in class org.apache.spark.graphx.Graph
Reverses all edges in the graph.
reverse() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
reverse() - Method in class org.apache.spark.graphx.impl.GraphImpl
 
reverse(Column) - Static method in class org.apache.spark.sql.functions
Returns a reversed string or an array with reverse order of elements.
reverseRoutingTables() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
reverseRoutingTables() - Method in class org.apache.spark.graphx.VertexRDD
Returns a new VertexRDD reflecting a reversal of all edge directions in the corresponding EdgeRDD.
ReviveOffers - Class in org.apache.spark.scheduler.local
 
ReviveOffers() - Constructor for class org.apache.spark.scheduler.local.ReviveOffers
 
reviveOffers() - Method in interface org.apache.spark.scheduler.SchedulerBackend
 
ReviveOffers$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.ReviveOffers$
 
RFormula - Class in org.apache.spark.ml.feature
:: Experimental :: Implements the transforms required for fitting a dataset against an R model formula.
RFormula(String) - Constructor for class org.apache.spark.ml.feature.RFormula
 
RFormula() - Constructor for class org.apache.spark.ml.feature.RFormula
 
RFormulaBase - Interface in org.apache.spark.ml.feature
Base trait for RFormula and RFormulaModel.
RFormulaModel - Class in org.apache.spark.ml.feature
:: Experimental :: Model fitted by RFormula.
RFormulaParser - Class in org.apache.spark.ml.feature
Limited implementation of R formula parsing.
RFormulaParser() - Constructor for class org.apache.spark.ml.feature.RFormulaParser
 
RidgeRegressionModel - Class in org.apache.spark.mllib.regression
Regression model trained using RidgeRegression.
RidgeRegressionModel(Vector, double) - Constructor for class org.apache.spark.mllib.regression.RidgeRegressionModel
 
RidgeRegressionWithSGD - Class in org.apache.spark.mllib.regression
Train a regression model with L2-regularization using Stochastic Gradient Descent.
RidgeRegressionWithSGD() - Constructor for class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
Deprecated.
Use ml.regression.LinearRegression with elasticNetParam = 0.0. Note the default regParam is 0.01 for RidgeRegressionWithSGD, but is 0.0 for LinearRegression. Since 2.0.0.
right() - Method in class org.apache.spark.sql.sources.And
 
right() - Method in class org.apache.spark.sql.sources.Or
 
rightCategories() - Method in class org.apache.spark.ml.tree.CategoricalSplit
Get sorted categories which split to the right
rightChild() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
 
rightChild() - Method in class org.apache.spark.ml.tree.InternalNode
 
rightChildIndex(int) - Static method in class org.apache.spark.mllib.tree.model.Node
Return the index of the right child of this node.
rightImpurity() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
 
rightNode() - Method in class org.apache.spark.mllib.tree.model.Node
 
rightNodeId() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
 
rightOuterJoin(JavaPairRDD<K, W>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
Perform a right outer join of this and other.
rightOuterJoin(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
Perform a right outer join of this and other.
rightOuterJoin(JavaPairRDD<K, W>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
Perform a right outer join of this and other.
rightOuterJoin(RDD<Tuple2<K, W>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
Perform a right outer join of this and other.
rightOuterJoin(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Perform a right outer join of this and other.
rightOuterJoin(RDD<Tuple2<K, W>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
Perform a right outer join of this and other.
rightOuterJoin(JavaPairDStream<K, W>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'right outer join' between RDDs of this DStream and other DStream.
rightOuterJoin(JavaPairDStream<K, W>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'right outer join' between RDDs of this DStream and other DStream.
rightOuterJoin(JavaPairDStream<K, W>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by applying 'right outer join' between RDDs of this DStream and other DStream.
rightOuterJoin(DStream<Tuple2<K, W>>, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'right outer join' between RDDs of this DStream and other DStream.
rightOuterJoin(DStream<Tuple2<K, W>>, int, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'right outer join' between RDDs of this DStream and other DStream.
rightOuterJoin(DStream<Tuple2<K, W>>, Partitioner, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new DStream by applying 'right outer join' between RDDs of this DStream and other DStream.
rightPredict() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
 
rint(Column) - Static method in class org.apache.spark.sql.functions
Returns the double value that is closest in value to the argument and is equal to a mathematical integer.
rint(String) - Static method in class org.apache.spark.sql.functions
Returns the double value that is closest in value to the argument and is equal to a mathematical integer.
rlike(String) - Method in class org.apache.spark.sql.Column
SQL RLIKE expression (LIKE with Regex).
RMATa() - Static method in class org.apache.spark.graphx.util.GraphGenerators
 
RMATb() - Static method in class org.apache.spark.graphx.util.GraphGenerators
 
RMATc() - Static method in class org.apache.spark.graphx.util.GraphGenerators
 
RMATd() - Static method in class org.apache.spark.graphx.util.GraphGenerators
 
rmatGraph(SparkContext, int, int) - Static method in class org.apache.spark.graphx.util.GraphGenerators
A random graph generator using the R-MAT model, proposed in "R-MAT: A Recursive Model for Graph Mining" by Chakrabarti et al.
rnd() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
 
roc() - Method in interface org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
Returns the receiver operating characteristic (ROC) curve, which is a Dataframe having two fields (FPR, TPR) with (0.0, 0.0) prepended and (1.0, 1.0) appended to it.
roc() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
Returns the receiver operating characteristic (ROC) curve, which is an RDD of (false positive rate, true positive rate) with (0.0, 0.0) prepended and (1.0, 1.0) appended to it.
rolledOver() - Method in interface org.apache.spark.util.logging.RollingPolicy
Notify that rollover has occurred
RollingPolicy - Interface in org.apache.spark.util.logging
Defines the policy based on which RollingFileAppender will generate rolling files.
rollup(Column...) - Method in class org.apache.spark.sql.Dataset
Create a multi-dimensional rollup for the current Dataset using the specified columns, so we can run aggregation on them.
rollup(String, String...) - Method in class org.apache.spark.sql.Dataset
Create a multi-dimensional rollup for the current Dataset using the specified columns, so we can run aggregation on them.
rollup(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
Create a multi-dimensional rollup for the current Dataset using the specified columns, so we can run aggregation on them.
rollup(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
Create a multi-dimensional rollup for the current Dataset using the specified columns, so we can run aggregation on them.
RollupType$() - Constructor for class org.apache.spark.sql.RelationalGroupedDataset.RollupType$
 
rootMeanSquaredError() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
Returns the root mean squared error, which is defined as the square root of the mean squared error.
rootMeanSquaredError() - Method in class org.apache.spark.mllib.evaluation.RegressionMetrics
Returns the root mean squared error, which is defined as the square root of the mean squared error.
rootNode() - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
 
rootNode() - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
 
rootNode() - Method in interface org.apache.spark.ml.tree.DecisionTreeModel
Root of the decision tree
rootPool() - Method in interface org.apache.spark.scheduler.SchedulableBuilder
 
rootPool() - Method in interface org.apache.spark.scheduler.TaskScheduler
 
round(Column) - Static method in class org.apache.spark.sql.functions
Returns the value of the column e rounded to 0 decimal places with HALF_UP round mode.
round(Column, int) - Static method in class org.apache.spark.sql.functions
Round the value of e to scale decimal places with HALF_UP round mode if scale is greater than or equal to 0 or at integral part when scale is less than 0.
ROUND_CEILING() - Static method in class org.apache.spark.sql.types.Decimal
 
ROUND_FLOOR() - Static method in class org.apache.spark.sql.types.Decimal
 
ROUND_HALF_EVEN() - Static method in class org.apache.spark.sql.types.Decimal
 
ROUND_HALF_UP() - Static method in class org.apache.spark.sql.types.Decimal
 
ROW() - Static method in class org.apache.spark.api.r.SerializationFormats
 
Row - Interface in org.apache.spark.sql
Represents one row of output from a relational operator.
row(T) - Method in interface org.apache.spark.ui.PagedTable
 
row_number() - Static method in class org.apache.spark.sql.functions
Window function: returns a sequential number starting at 1 within a window partition.
RowFactory - Class in org.apache.spark.sql
A factory class used to construct Row objects.
RowFactory() - Constructor for class org.apache.spark.sql.RowFactory
 
rowIndices() - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
rowIndices() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
rowIter() - Method in interface org.apache.spark.ml.linalg.Matrix
Returns an iterator of row vectors.
rowIter() - Method in interface org.apache.spark.mllib.linalg.Matrix
Returns an iterator of row vectors.
rowIterator() - Method in class org.apache.spark.sql.vectorized.ColumnarBatch
Returns an iterator over the rows in this batch.
RowMatrix - Class in org.apache.spark.mllib.linalg.distributed
Represents a row-oriented distributed Matrix with no meaningful row indices.
RowMatrix(RDD<Vector>, long, int) - Constructor for class org.apache.spark.mllib.linalg.distributed.RowMatrix
 
RowMatrix(RDD<Vector>) - Constructor for class org.apache.spark.mllib.linalg.distributed.RowMatrix
Alternative constructor leaving matrix dimensions to be determined automatically.
rows() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
 
rows() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
 
rowsBetween(long, long) - Static method in class org.apache.spark.sql.expressions.Window
Creates a WindowSpec with the frame boundaries defined, from start (inclusive) to end (inclusive).
rowsBetween(long, long) - Method in class org.apache.spark.sql.expressions.WindowSpec
Defines the frame boundaries, from start (inclusive) to end (inclusive).
rowsPerBlock() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
 
rPackages() - Static method in class org.apache.spark.api.r.RUtils
 
rpad(Column, int, String) - Static method in class org.apache.spark.sql.functions
Right-pad the string column with pad to a length of len.
RpcCallContext - Interface in org.apache.spark.rpc
A callback that RpcEndpoint can use to send back a message or failure.
RpcEndpoint - Interface in org.apache.spark.rpc
An end point for the RPC that defines what functions to trigger given a message.
rpcEnv() - Method in interface org.apache.spark.rpc.RpcEndpoint
The RpcEnv that this RpcEndpoint is registered to.
RpcEnvFactory - Interface in org.apache.spark.rpc
A factory class to create the RpcEnv.
RpcEnvFileServer - Interface in org.apache.spark.rpc
A server used by the RpcEnv to server files to other processes owned by the application.
RpcUtils - Class in org.apache.spark.util
 
RpcUtils() - Constructor for class org.apache.spark.util.RpcUtils
 
RRDD<T> - Class in org.apache.spark.api.r
An RDD that stores serialized R objects as Array[Byte].
RRDD(RDD<T>, byte[], String, String, byte[], Object[], ClassTag<T>) - Constructor for class org.apache.spark.api.r.RRDD
 
RRunnerModes - Class in org.apache.spark.api.r
 
RRunnerModes() - Constructor for class org.apache.spark.api.r.RRunnerModes
 
rtrim(Column) - Static method in class org.apache.spark.sql.functions
Trim the spaces from right end for the specified string value.
rtrim(Column, String) - Static method in class org.apache.spark.sql.functions
Trim the specified character string from right end for the specified string column.
ruleName() - Static method in class org.apache.spark.sql.hive.HiveAnalysis
 
run(Graph<VD, ED>, int, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.ConnectedComponents
Compute the connected component membership of each vertex and return a graph with the vertex value containing the lowest vertex id in the connected component containing that vertex.
run(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.ConnectedComponents
Compute the connected component membership of each vertex and return a graph with the vertex value containing the lowest vertex id in the connected component containing that vertex.
run(Graph<VD, ED>, int, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.LabelPropagation
Run static Label Propagation for detecting communities in networks.
run(Graph<VD, ED>, int, double, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.PageRank
Run PageRank for a fixed number of iterations returning a graph with vertex attributes containing the PageRank and edge attributes the normalized edge weight.
run(Graph<VD, ED>, Seq<Object>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.ShortestPaths
Computes shortest paths to the given set of landmark vertices.
run(Graph<VD, ED>, int, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.StronglyConnectedComponents
Compute the strongly connected component (SCC) of each vertex and return a graph with the vertex value containing the lowest vertex id in the SCC containing that vertex.
run(RDD<Edge<Object>>, SVDPlusPlus.Conf) - Static method in class org.apache.spark.graphx.lib.SVDPlusPlus
Implement SVD++ based on "Factorization Meets the Neighborhood: a Multifaceted Collaborative Filtering Model", available at here.
run(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.TriangleCount
 
run(RDD<LabeledPoint>, BoostingStrategy, long, String) - Static method in class org.apache.spark.ml.tree.impl.GradientBoostedTrees
Method to train a gradient boosting model
run(RDD<LabeledPoint>, Strategy, int, String, long, Option<org.apache.spark.ml.util.Instrumentation>, boolean, Option<String>) - Static method in class org.apache.spark.ml.tree.impl.RandomForest
Train a random forest.
run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
Run Logistic Regression with the configured parameters on an input RDD of LabeledPoint entries.
run(RDD<LabeledPoint>, Vector) - Method in class org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
Run Logistic Regression with the configured parameters on an input RDD of LabeledPoint entries starting from the initial weights provided.
run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.classification.NaiveBayes
Run the algorithm with the configured parameters on an input RDD of LabeledPoint entries.
run(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
Runs the bisecting k-means algorithm.
run(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
Java-friendly version of run().
run(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
Perform expectation maximization
run(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
Java-friendly version of run()
run(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.KMeans
Train a K-means model on the given set of points; data should be cached for high performance, because this is an iterative algorithm.
run(RDD<Tuple2<Object, Vector>>) - Method in class org.apache.spark.mllib.clustering.LDA
Learn an LDA model using the given dataset.
run(JavaPairRDD<Long, Vector>) - Method in class org.apache.spark.mllib.clustering.LDA
Java-friendly version of run()
run(Graph<Object, Object>) - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering
Run the PIC algorithm on Graph.
run(RDD<Tuple3<Object, Object, Object>>) - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering
Run the PIC algorithm.
run(JavaRDD<Tuple3<Long, Long, Double>>) - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering
A Java-friendly version of PowerIterationClustering.run.
run(RDD<FPGrowth.FreqItemset<Item>>, ClassTag<Item>) - Method in class org.apache.spark.mllib.fpm.AssociationRules
Computes the association rules with confidence above minConfidence.
run(RDD<FPGrowth.FreqItemset<Item>>, Map<Item, Object>, ClassTag<Item>) - Method in class org.apache.spark.mllib.fpm.AssociationRules
Computes the association rules with confidence above minConfidence.
run(JavaRDD<FPGrowth.FreqItemset<Item>>) - Method in class org.apache.spark.mllib.fpm.AssociationRules
Java-friendly version of run.
run(RDD<Object>, ClassTag<Item>) - Method in class org.apache.spark.mllib.fpm.FPGrowth
Computes an FP-Growth model that contains frequent itemsets.
run(JavaRDD<Basket>) - Method in class org.apache.spark.mllib.fpm.FPGrowth
Java-friendly version of run.
run(RDD<Object[]>, ClassTag<Item>) - Method in class org.apache.spark.mllib.fpm.PrefixSpan
Finds the complete set of frequent sequential patterns in the input sequences of itemsets.
run(JavaRDD<Sequence>) - Method in class org.apache.spark.mllib.fpm.PrefixSpan
A Java-friendly version of run() that reads sequences from a JavaRDD and returns frequent sequences in a PrefixSpanModel.
run(RDD<Rating>) - Method in class org.apache.spark.mllib.recommendation.ALS
Run ALS with the configured parameters on an input RDD of Rating objects.
run(JavaRDD<Rating>) - Method in class org.apache.spark.mllib.recommendation.ALS
Java-friendly version of ALS.run.
run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
Run the algorithm with the configured parameters on an input RDD of LabeledPoint entries.
run(RDD<LabeledPoint>, Vector) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
Run the algorithm with the configured parameters on an input RDD of LabeledPoint entries starting from the initial weights provided.
run(RDD<Tuple3<Object, Object, Object>>) - Method in class org.apache.spark.mllib.regression.IsotonicRegression
Run IsotonicRegression algorithm to obtain isotonic regression model.
run(JavaRDD<Tuple3<Double, Double, Double>>) - Method in class org.apache.spark.mllib.regression.IsotonicRegression
Run pool adjacent violators algorithm to obtain isotonic regression model.
run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.DecisionTree
Method to train a decision tree model over an RDD
run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.GradientBoostedTrees
Method to train a gradient boosting model
run(JavaRDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.GradientBoostedTrees
Java-friendly API for org.apache.spark.mllib.tree.GradientBoostedTrees.run.
run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.RandomForest
Method to train a decision tree model over an RDD
run(SparkSession, SparkPlan) - Method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
 
run(SparkSession, SparkPlan) - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
 
run(SparkSession, SparkPlan) - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
Inserts all the rows in the table into Hive.
run() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationWriterThread
 
run() - Method in class org.apache.spark.util.SparkShutdownHook
 
runApproximateJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, ApproximateEvaluator<U, R>, long) - Method in class org.apache.spark.SparkContext
:: DeveloperApi :: Run a job that can return approximate results.
runId() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Returns the unique id of this run of the query.
runId() - Method in class org.apache.spark.sql.streaming.StreamingQueryListener.QueryStartedEvent
 
runId() - Method in class org.apache.spark.sql.streaming.StreamingQueryListener.QueryTerminatedEvent
 
runId() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
 
runInNewThread(String, boolean, Function0<T>) - Static method in class org.apache.spark.util.ThreadUtils
Run a piece of code in a new thread and return the result.
runJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, Seq<Object>, Function2<Object, U, BoxedUnit>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
Run a function on a given set of partitions in an RDD and pass the results to the given handler function.
runJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, Seq<Object>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
Run a function on a given set of partitions in an RDD and return the results as an array.
runJob(RDD<T>, Function1<Iterator<T>, U>, Seq<Object>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
Run a function on a given set of partitions in an RDD and return the results as an array.
runJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
Run a job on all partitions in an RDD and return the results in an array.
runJob(RDD<T>, Function1<Iterator<T>, U>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
Run a job on all partitions in an RDD and return the results in an array.
runJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, Function2<Object, U, BoxedUnit>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
Run a job on all partitions in an RDD and pass the results to a handler function.
runJob(RDD<T>, Function1<Iterator<T>, U>, Function2<Object, U, BoxedUnit>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
Run a job on all partitions in an RDD and pass the results to a handler function.
runLBFGS(RDD<Tuple2<Object, Vector>>, Gradient, Updater, int, double, int, double, Vector) - Static method in class org.apache.spark.mllib.optimization.LBFGS
Run Limited-memory BFGS (L-BFGS) in parallel.
runMiniBatchSGD(RDD<Tuple2<Object, Vector>>, Gradient, Updater, double, int, double, double, Vector, double) - Static method in class org.apache.spark.mllib.optimization.GradientDescent
Run stochastic gradient descent (SGD) in parallel using mini batches.
runMiniBatchSGD(RDD<Tuple2<Object, Vector>>, Gradient, Updater, double, int, double, double, Vector) - Static method in class org.apache.spark.mllib.optimization.GradientDescent
Alias of runMiniBatchSGD with convergenceTol set to default value of 0.001.
running() - Method in class org.apache.spark.scheduler.TaskInfo
 
RUNNING() - Static method in class org.apache.spark.TaskState
 
runningTasks() - Method in interface org.apache.spark.scheduler.Schedulable
 
runParallelPersonalizedPageRank(Graph<VD, ED>, int, double, long[], ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.PageRank
Run Personalized PageRank for a fixed number of iterations, for a set of starting nodes in parallel.
runPreCanonicalized(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.TriangleCount
 
runSqlHive(String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Runs a HiveQL command using Hive, returning the results as a list of strings.
runtime() - Method in class org.apache.spark.status.api.v1.ApplicationEnvironmentInfo
 
RuntimeConfig - Class in org.apache.spark.sql
Runtime configuration interface for Spark.
RuntimeInfo - Class in org.apache.spark.status.api.v1
 
RuntimePercentage - Class in org.apache.spark.scheduler
 
RuntimePercentage(double, Option<Object>, double) - Constructor for class org.apache.spark.scheduler.RuntimePercentage
 
runUntilConvergence(Graph<VD, ED>, double, double, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.PageRank
Run a dynamic version of PageRank returning a graph with vertex attributes containing the PageRank and edge attributes containing the normalized edge weight.
runUntilConvergenceWithOptions(Graph<VD, ED>, double, double, Option<Object>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.PageRank
Run a dynamic version of PageRank returning a graph with vertex attributes containing the PageRank and edge attributes containing the normalized edge weight.
runWithOptions(Graph<VD, ED>, int, double, Option<Object>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.PageRank
Run PageRank for a fixed number of iterations returning a graph with vertex attributes containing the PageRank and edge attributes the normalized edge weight.
runWithValidation(RDD<LabeledPoint>, RDD<LabeledPoint>, BoostingStrategy, long, String) - Static method in class org.apache.spark.ml.tree.impl.GradientBoostedTrees
Method to validate a gradient boosting model
runWithValidation(RDD<LabeledPoint>, RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.GradientBoostedTrees
Method to validate a gradient boosting model
runWithValidation(JavaRDD<LabeledPoint>, JavaRDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.GradientBoostedTrees
Java-friendly API for org.apache.spark.mllib.tree.GradientBoostedTrees.runWithValidation.
RUtils - Class in org.apache.spark.api.r
 
RUtils() - Constructor for class org.apache.spark.api.r.RUtils
 
RWrappers - Class in org.apache.spark.ml.r
This is the Scala stub of SparkR read.ml.
RWrappers() - Constructor for class org.apache.spark.ml.r.RWrappers
 
RWrapperUtils - Class in org.apache.spark.ml.r
 
RWrapperUtils() - Constructor for class org.apache.spark.ml.r.RWrapperUtils
 

S

s() - Method in class org.apache.spark.mllib.linalg.SingularValueDecomposition
 
safeCall(Function0<T>) - Method in interface org.apache.spark.security.CryptoStreamUtils.BaseErrorHandler
 
sameThread() - Static method in class org.apache.spark.util.ThreadUtils
An ExecutionContextExecutor that runs each task in the thread that invokes execute/submit.
sample(boolean, Double) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return a sampled subset of this RDD.
sample(boolean, Double, long) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return a sampled subset of this RDD.
sample(boolean, double) - Method in class org.apache.spark.api.java.JavaPairRDD
Return a sampled subset of this RDD.
sample(boolean, double, long) - Method in class org.apache.spark.api.java.JavaPairRDD
Return a sampled subset of this RDD.
sample(boolean, double) - Method in class org.apache.spark.api.java.JavaRDD
Return a sampled subset of this RDD with a random seed.
sample(boolean, double, long) - Method in class org.apache.spark.api.java.JavaRDD
Return a sampled subset of this RDD, with a user-supplied seed.
sample(boolean, double, long) - Method in class org.apache.spark.rdd.RDD
Return a sampled subset of this RDD.
sample(double, long) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset by sampling a fraction of rows (without replacement), using a user-supplied seed.
sample(double) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset by sampling a fraction of rows (without replacement), using a random seed.
sample(boolean, double, long) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset by sampling a fraction of rows, using a user-supplied seed.
sample(boolean, double) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset by sampling a fraction of rows, using a random seed.
sample() - Method in class org.apache.spark.util.random.BernoulliCellSampler
 
sample() - Method in class org.apache.spark.util.random.BernoulliSampler
 
sample() - Method in class org.apache.spark.util.random.PoissonSampler
 
sample(Iterator<T>) - Method in class org.apache.spark.util.random.PoissonSampler
 
sample(Iterator<T>) - Method in interface org.apache.spark.util.random.RandomSampler
take a random sample
sample() - Method in interface org.apache.spark.util.random.RandomSampler
Whether to sample the next item or not.
sampleBy(String, Map<T, Object>, long) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Returns a stratified sample without replacement based on the fraction given on each stratum.
sampleBy(String, Map<T, Double>, long) - Method in class org.apache.spark.sql.DataFrameStatFunctions
Returns a stratified sample without replacement based on the fraction given on each stratum.
sampleByKey(boolean, Map<K, Double>, long) - Method in class org.apache.spark.api.java.JavaPairRDD
Return a subset of this RDD sampled by key (via stratified sampling).
sampleByKey(boolean, Map<K, Double>) - Method in class org.apache.spark.api.java.JavaPairRDD
Return a subset of this RDD sampled by key (via stratified sampling).
sampleByKey(boolean, Map<K, Object>, long) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return a subset of this RDD sampled by key (via stratified sampling).
sampleByKeyExact(boolean, Map<K, Double>, long) - Method in class org.apache.spark.api.java.JavaPairRDD
Return a subset of this RDD sampled by key (via stratified sampling) containing exactly math.ceil(numItems * samplingRate) for each stratum (group of pairs with the same key).
sampleByKeyExact(boolean, Map<K, Double>) - Method in class org.apache.spark.api.java.JavaPairRDD
Return a subset of this RDD sampled by key (via stratified sampling) containing exactly math.ceil(numItems * samplingRate) for each stratum (group of pairs with the same key).
sampleByKeyExact(boolean, Map<K, Object>, long) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return a subset of this RDD sampled by key (via stratified sampling) containing exactly math.ceil(numItems * samplingRate) for each stratum (group of pairs with the same key).
SamplePathFilter - Class in org.apache.spark.ml.image
Filter that allows loading a fraction of HDFS files.
SamplePathFilter() - Constructor for class org.apache.spark.ml.image.SamplePathFilter
 
samplePointsPerPartitionHint() - Method in class org.apache.spark.RangePartitioner
 
sampleRatio() - Method in class org.apache.spark.ml.image.SamplePathFilter
 
sampleStdev() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Compute the sample standard deviation of this RDD's elements (which corrects for bias in estimating the standard deviation by dividing by N-1 instead of N).
sampleStdev() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
Compute the sample standard deviation of this RDD's elements (which corrects for bias in estimating the standard deviation by dividing by N-1 instead of N).
sampleStdev() - Method in class org.apache.spark.util.StatCounter
Return the sample standard deviation of the values, which corrects for bias in estimating the variance by dividing by N-1 instead of N.
sampleVariance() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Compute the sample variance of this RDD's elements (which corrects for bias in estimating the standard variance by dividing by N-1 instead of N).
sampleVariance() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
Compute the sample variance of this RDD's elements (which corrects for bias in estimating the variance by dividing by N-1 instead of N).
sampleVariance() - Method in class org.apache.spark.util.StatCounter
Return the sample variance, which corrects for bias in estimating the variance by dividing by N-1 instead of N.
SamplingUtils - Class in org.apache.spark.util.random
 
SamplingUtils() - Constructor for class org.apache.spark.util.random.SamplingUtils
 
satisfy(Distribution) - Method in interface org.apache.spark.sql.sources.v2.reader.partitioning.Partitioning
Returns true if this partitioning can satisfy the given distribution, which means Spark does not need to shuffle the output data of this data source for some certain operations.
save(String) - Method in interface org.apache.spark.ml.util.MLWritable
Saves this ML instance to the input path, a shortcut of write.save(path).
save(String) - Method in class org.apache.spark.ml.util.MLWriter
Saves the ML instances to the input path.
save(SparkContext, String, String, int, int, Vector, double, Option<Object>) - Method in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$
Helper method for saving GLM classification model metadata and data.
save(SparkContext, String) - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
 
save(SparkContext, String, org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0.Data) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$
 
save(SparkContext, String, org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0.Data) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.classification.SVMModel
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
 
save(SparkContext, BisectingKMeansModel, String) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel.SaveLoadV1_0$
 
save(SparkContext, BisectingKMeansModel, String) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel.SaveLoadV2_0$
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.KMeansModel
 
save(SparkContext, KMeansModel, String) - Method in class org.apache.spark.mllib.clustering.KMeansModel.SaveLoadV1_0$
 
save(SparkContext, KMeansModel, String) - Method in class org.apache.spark.mllib.clustering.KMeansModel.SaveLoadV2_0$
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel
 
save(SparkContext, PowerIterationClusteringModel, String) - Method in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel.SaveLoadV1_0$
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.feature.ChiSqSelectorModel
 
save(SparkContext, ChiSqSelectorModel, String) - Method in class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.feature.Word2VecModel
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.fpm.FPGrowthModel
Save this model to the given path.
save(FPGrowthModel<?>, String) - Method in class org.apache.spark.mllib.fpm.FPGrowthModel.SaveLoadV1_0$
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.fpm.PrefixSpanModel
Save this model to the given path.
save(PrefixSpanModel<?>, String) - Method in class org.apache.spark.mllib.fpm.PrefixSpanModel.SaveLoadV1_0$
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
Save this model to the given path.
save(MatrixFactorizationModel, String) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel.SaveLoadV1_0$
Saves a MatrixFactorizationModel, where user features are saved under data/users and product features are saved under data/products.
save(SparkContext, String, String, Vector, double) - Method in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$
Helper method for saving GLM regression model metadata and data.
save(SparkContext, String) - Method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.regression.LassoModel
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.regression.LinearRegressionModel
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.regression.RidgeRegressionModel
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
 
save(SparkContext, String, DecisionTreeModel) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
 
save(SparkContext, String) - Method in class org.apache.spark.mllib.tree.model.RandomForestModel
 
save(SparkContext, String) - Method in interface org.apache.spark.mllib.util.Saveable
Save this model to the given path.
save(String) - Method in class org.apache.spark.sql.DataFrameWriter
Saves the content of the DataFrame at the specified path.
save() - Method in class org.apache.spark.sql.DataFrameWriter
Saves the content of the DataFrame as the specified table.
Saveable - Interface in org.apache.spark.mllib.util
:: DeveloperApi ::
saveAsHadoopDataset(JobConf) - Method in class org.apache.spark.api.java.JavaPairRDD
Output the RDD to any Hadoop-supported storage system, using a Hadoop JobConf object for that storage system.
saveAsHadoopDataset(JobConf) - Method in class org.apache.spark.rdd.PairRDDFunctions
Output the RDD to any Hadoop-supported storage system, using a Hadoop JobConf object for that storage system.
saveAsHadoopFile(String, Class<?>, Class<?>, Class<F>, JobConf) - Method in class org.apache.spark.api.java.JavaPairRDD
Output the RDD to any Hadoop-supported file system.
saveAsHadoopFile(String, Class<?>, Class<?>, Class<F>) - Method in class org.apache.spark.api.java.JavaPairRDD
Output the RDD to any Hadoop-supported file system.
saveAsHadoopFile(String, Class<?>, Class<?>, Class<F>, Class<? extends CompressionCodec>) - Method in class org.apache.spark.api.java.JavaPairRDD
Output the RDD to any Hadoop-supported file system, compressing with the supplied codec.
saveAsHadoopFile(String, ClassTag<F>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Output the RDD to any Hadoop-supported file system, using a Hadoop OutputFormat class supporting the key and value types K and V in this RDD.
saveAsHadoopFile(String, Class<? extends CompressionCodec>, ClassTag<F>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Output the RDD to any Hadoop-supported file system, using a Hadoop OutputFormat class supporting the key and value types K and V in this RDD.
saveAsHadoopFile(String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, Class<? extends CompressionCodec>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Output the RDD to any Hadoop-supported file system, using a Hadoop OutputFormat class supporting the key and value types K and V in this RDD.
saveAsHadoopFile(String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, JobConf, Option<Class<? extends CompressionCodec>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Output the RDD to any Hadoop-supported file system, using a Hadoop OutputFormat class supporting the key and value types K and V in this RDD.
saveAsHadoopFiles(String, String) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Save each RDD in this DStream as a Hadoop file.
saveAsHadoopFiles(String, String, Class<?>, Class<?>, Class<F>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Save each RDD in this DStream as a Hadoop file.
saveAsHadoopFiles(String, String, Class<?>, Class<?>, Class<F>, JobConf) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Save each RDD in this DStream as a Hadoop file.
saveAsHadoopFiles(String, String, ClassTag<F>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Save each RDD in this DStream as a Hadoop file.
saveAsHadoopFiles(String, String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, JobConf) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Save each RDD in this DStream as a Hadoop file.
SaveAsHiveFile - Interface in org.apache.spark.sql.hive.execution
 
saveAsHiveFile(SparkSession, SparkPlan, Configuration, org.apache.spark.sql.hive.HiveShim.ShimFileSinkDesc, String, Map<Map<String, String>, String>, Seq<Attribute>) - Method in interface org.apache.spark.sql.hive.execution.SaveAsHiveFile
 
saveAsLibSVMFile(RDD<LabeledPoint>, String) - Static method in class org.apache.spark.mllib.util.MLUtils
Save labeled data in LIBSVM format.
saveAsNewAPIHadoopDataset(Configuration) - Method in class org.apache.spark.api.java.JavaPairRDD
Output the RDD to any Hadoop-supported storage system, using a Configuration object for that storage system.
saveAsNewAPIHadoopDataset(Configuration) - Method in class org.apache.spark.rdd.PairRDDFunctions
Output the RDD to any Hadoop-supported storage system with new Hadoop API, using a Hadoop Configuration object for that storage system.
saveAsNewAPIHadoopFile(String, Class<?>, Class<?>, Class<F>, Configuration) - Method in class org.apache.spark.api.java.JavaPairRDD
Output the RDD to any Hadoop-supported file system.
saveAsNewAPIHadoopFile(String, Class<?>, Class<?>, Class<F>) - Method in class org.apache.spark.api.java.JavaPairRDD
Output the RDD to any Hadoop-supported file system.
saveAsNewAPIHadoopFile(String, ClassTag<F>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Output the RDD to any Hadoop-supported file system, using a new Hadoop API OutputFormat (mapreduce.OutputFormat) object supporting the key and value types K and V in this RDD.
saveAsNewAPIHadoopFile(String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, Configuration) - Method in class org.apache.spark.rdd.PairRDDFunctions
Output the RDD to any Hadoop-supported file system, using a new Hadoop API OutputFormat (mapreduce.OutputFormat) object supporting the key and value types K and V in this RDD.
saveAsNewAPIHadoopFiles(String, String) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Save each RDD in this DStream as a Hadoop file.
saveAsNewAPIHadoopFiles(String, String, Class<?>, Class<?>, Class<F>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Save each RDD in this DStream as a Hadoop file.
saveAsNewAPIHadoopFiles(String, String, Class<?>, Class<?>, Class<F>, Configuration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Save each RDD in this DStream as a Hadoop file.
saveAsNewAPIHadoopFiles(String, String, ClassTag<F>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Save each RDD in this DStream as a Hadoop file.
saveAsNewAPIHadoopFiles(String, String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, Configuration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Save each RDD in this DStream as a Hadoop file.
saveAsObjectFile(String) - Method in interface org.apache.spark.api.java.JavaRDDLike
Save this RDD as a SequenceFile of serialized objects.
saveAsObjectFile(String) - Method in class org.apache.spark.rdd.RDD
Save this RDD as a SequenceFile of serialized objects.
saveAsObjectFiles(String, String) - Method in class org.apache.spark.streaming.dstream.DStream
Save each RDD in this DStream as a Sequence file of serialized objects.
saveAsSequenceFile(String, Option<Class<? extends CompressionCodec>>) - Method in class org.apache.spark.rdd.SequenceFileRDDFunctions
Output the RDD as a Hadoop SequenceFile using the Writable types we infer from the RDD's key and value types.
saveAsTable(String) - Method in class org.apache.spark.sql.DataFrameWriter
Saves the content of the DataFrame as the specified table.
saveAsTextFile(String) - Method in interface org.apache.spark.api.java.JavaRDDLike
Save this RDD as a text file, using string representations of elements.
saveAsTextFile(String, Class<? extends CompressionCodec>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Save this RDD as a compressed text file, using string representations of elements.
saveAsTextFile(String) - Method in class org.apache.spark.rdd.RDD
Save this RDD as a text file, using string representations of elements.
saveAsTextFile(String, Class<? extends CompressionCodec>) - Method in class org.apache.spark.rdd.RDD
Save this RDD as a compressed text file, using string representations of elements.
saveAsTextFiles(String, String) - Method in class org.apache.spark.streaming.dstream.DStream
Save each RDD in this DStream as at text file, using string representation of elements.
savedTasks() - Method in class org.apache.spark.status.LiveStage
 
saveImpl(Params, PipelineStage[], SparkContext, String) - Method in class org.apache.spark.ml.Pipeline.SharedReadWrite$
Save metadata and stages for a Pipeline or PipelineModel - save metadata to path/metadata - save stages to stages/IDX_UID
saveImpl(M, String, SparkSession, JsonAST.JObject) - Static method in class org.apache.spark.ml.tree.EnsembleModelReadWrite
Helper method for saving a tree ensemble to disk.
SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$
 
SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$
 
SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.clustering.BisectingKMeansModel.SaveLoadV1_0$
 
SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.clustering.KMeansModel.SaveLoadV1_0$
 
SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.clustering.PowerIterationClusteringModel.SaveLoadV1_0$
 
SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$
 
SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.fpm.FPGrowthModel.SaveLoadV1_0$
 
SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.fpm.PrefixSpanModel.SaveLoadV1_0$
 
SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.recommendation.MatrixFactorizationModel.SaveLoadV1_0$
 
SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$
 
SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
 
SaveLoadV2_0$() - Constructor for class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$
 
SaveLoadV2_0$() - Constructor for class org.apache.spark.mllib.clustering.BisectingKMeansModel.SaveLoadV2_0$
 
SaveLoadV2_0$() - Constructor for class org.apache.spark.mllib.clustering.KMeansModel.SaveLoadV2_0$
 
SaveMode - Enum in org.apache.spark.sql
SaveMode is used to specify the expected behavior of saving a DataFrame to a data source.
sc() - Method in class org.apache.spark.api.java.JavaSparkContext
 
sc() - Method in interface org.apache.spark.ml.util.BaseReadWrite
Returns the underlying `SparkContext`.
sc() - Method in class org.apache.spark.sql.SQLImplicits.StringToColumn
 
scal(double, Vector) - Static method in class org.apache.spark.ml.linalg.BLAS
x = a * x
scal(double, Vector) - Static method in class org.apache.spark.mllib.linalg.BLAS
x = a * x
scalaBoolean() - Static method in class org.apache.spark.sql.Encoders
An encoder for Scala's primitive boolean type.
scalaByte() - Static method in class org.apache.spark.sql.Encoders
An encoder for Scala's primitive byte type.
scalaDouble() - Static method in class org.apache.spark.sql.Encoders
An encoder for Scala's primitive double type.
scalaFloat() - Static method in class org.apache.spark.sql.Encoders
An encoder for Scala's primitive float type.
scalaInt() - Static method in class org.apache.spark.sql.Encoders
An encoder for Scala's primitive int type.
scalaIntToJavaLong(DStream<Object>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
 
scalaLong() - Static method in class org.apache.spark.sql.Encoders
An encoder for Scala's primitive long type.
scalaShort() - Static method in class org.apache.spark.sql.Encoders
An encoder for Scala's primitive short type.
scalaToJavaLong(JavaPairDStream<K, Object>, ClassTag<K>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
 
scalaVersion() - Method in class org.apache.spark.status.api.v1.RuntimeInfo
 
scale() - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
scale() - Method in class org.apache.spark.ml.regression.LinearRegressionModel
 
scale() - Method in class org.apache.spark.mllib.random.GammaGenerator
 
scale() - Method in class org.apache.spark.sql.types.Decimal
 
scale() - Method in class org.apache.spark.sql.types.DecimalType
 
scalingVec() - Method in class org.apache.spark.ml.feature.ElementwiseProduct
the vector to multiply with input vectors
scalingVec() - Method in class org.apache.spark.mllib.feature.ElementwiseProduct
 
Schedulable - Interface in org.apache.spark.scheduler
An interface for schedulable entities.
SchedulableBuilder - Interface in org.apache.spark.scheduler
An interface to build Schedulable tree buildPools: build the tree nodes(pools) addTaskSetManager: build the leaf nodes(TaskSetManagers)
schedulableQueue() - Method in interface org.apache.spark.scheduler.Schedulable
 
SCHEDULED() - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
 
SCHEDULER_DELAY() - Static method in class org.apache.spark.status.TaskIndexNames
 
SCHEDULER_DELAY() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
 
SCHEDULER_DELAY() - Static method in class org.apache.spark.ui.ToolTips
 
SchedulerBackend - Interface in org.apache.spark.scheduler
A backend interface for scheduling systems that allows plugging in different ones under TaskSchedulerImpl.
SchedulerBackendUtils - Class in org.apache.spark.scheduler.cluster
 
SchedulerBackendUtils() - Constructor for class org.apache.spark.scheduler.cluster.SchedulerBackendUtils
 
schedulerDelay() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
schedulerDelay(TaskData) - Static method in class org.apache.spark.status.AppStatusUtils
 
schedulerDelay(long, long, long, long, long, long) - Static method in class org.apache.spark.status.AppStatusUtils
 
SchedulerPool - Class in org.apache.spark.status
 
SchedulerPool(String) - Constructor for class org.apache.spark.status.SchedulerPool
 
SchedulingAlgorithm - Interface in org.apache.spark.scheduler
An interface for sort algorithm FIFO: FIFO algorithm between TaskSetManagers FS: FS algorithm between Pools, and FIFO or FS within Pools
schedulingDelay() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
 
schedulingDelay() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
Time taken for the first job of this batch to start processing from the time this batch was submitted to the streaming scheduler.
schedulingMode() - Method in interface org.apache.spark.scheduler.Schedulable
 
SchedulingMode - Class in org.apache.spark.scheduler
"FAIR" and "FIFO" determines which policy is used to order tasks amongst a Schedulable's sub-queues "NONE" is used when the a Schedulable has no sub-queues.
SchedulingMode() - Constructor for class org.apache.spark.scheduler.SchedulingMode
 
schedulingMode() - Method in interface org.apache.spark.scheduler.TaskScheduler
 
schedulingPool() - Method in class org.apache.spark.status.api.v1.StageData
 
schedulingPool() - Method in class org.apache.spark.status.LiveStage
 
schema(StructType) - Method in class org.apache.spark.sql.DataFrameReader
Specifies the input schema.
schema(String) - Method in class org.apache.spark.sql.DataFrameReader
Specifies the schema by using the input DDL-formatted string.
schema() - Method in class org.apache.spark.sql.Dataset
Returns the schema of this Dataset.
schema() - Method in interface org.apache.spark.sql.Encoder
Returns the schema of encoding this type of object as a Row.
schema() - Method in interface org.apache.spark.sql.Row
Schema for the row.
schema() - Method in class org.apache.spark.sql.sources.BaseRelation
 
schema(StructType) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Specifies the input schema.
schema(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Specifies the schema by using the input DDL-formatted string.
schema_of_json(String) - Static method in class org.apache.spark.sql.functions
Parses a JSON string and infers its schema in DDL format.
schema_of_json(Column) - Static method in class org.apache.spark.sql.functions
Parses a JSON string and infers its schema in DDL format.
schemaLess() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
 
SchemaRelationProvider - Interface in org.apache.spark.sql.sources
Implemented by objects that produce relations for a specific kind of data source with a given schema.
SchemaUtils - Class in org.apache.spark.ml.util
Utils for handling schemas.
SchemaUtils() - Constructor for class org.apache.spark.ml.util.SchemaUtils
 
SchemaUtils - Class in org.apache.spark.sql.util
Utils for handling schemas.
SchemaUtils() - Constructor for class org.apache.spark.sql.util.SchemaUtils
 
scope() - Method in class org.apache.spark.storage.RDDInfo
 
scoreAndLabels() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
 
scratch() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
 
script() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
 
Scripts() - Method in interface org.apache.spark.sql.hive.HiveStrategies
 
Scripts() - Constructor for class org.apache.spark.sql.hive.HiveStrategies.Scripts
 
Scripts$() - Constructor for class org.apache.spark.sql.hive.HiveStrategies.Scripts$
 
ScriptTransformationExec - Class in org.apache.spark.sql.hive.execution
Transforms the input by forking and running the specified script.
ScriptTransformationExec(Seq<Expression>, String, Seq<Attribute>, SparkPlan, HiveScriptIOSchema) - Constructor for class org.apache.spark.sql.hive.execution.ScriptTransformationExec
 
ScriptTransformationWriterThread - Class in org.apache.spark.sql.hive.execution
 
ScriptTransformationWriterThread(Iterator<InternalRow>, Seq<DataType>, org.apache.spark.sql.catalyst.expressions.Projection, AbstractSerDe, ObjectInspector, HiveScriptIOSchema, OutputStream, Process, org.apache.spark.util.CircularBuffer, TaskContext, Configuration) - Constructor for class org.apache.spark.sql.hive.execution.ScriptTransformationWriterThread
 
second(Column) - Static method in class org.apache.spark.sql.functions
Extracts the seconds as an integer from a given date/timestamp/string.
seconds() - Static method in class org.apache.spark.scheduler.StatsReportListener
 
seconds(long) - Static method in class org.apache.spark.streaming.Durations
 
Seconds - Class in org.apache.spark.streaming
Helper object that creates instance of Duration representing a given number of seconds.
Seconds() - Constructor for class org.apache.spark.streaming.Seconds
 
securityManager() - Method in class org.apache.spark.SparkEnv
 
securityManager() - Method in interface org.apache.spark.status.api.v1.UIRoot
 
seed() - Method in interface org.apache.spark.ml.param.shared.HasSeed
Param for random seed.
seedParam() - Static method in class org.apache.spark.ml.image.SamplePathFilter
 
select(Column...) - Method in class org.apache.spark.sql.Dataset
Selects a set of column based expressions.
select(String, String...) - Method in class org.apache.spark.sql.Dataset
Selects a set of columns.
select(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
Selects a set of column based expressions.
select(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
Selects a set of columns.
select(TypedColumn<T, U1>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: Returns a new Dataset by computing the given Column expression for each element.
select(TypedColumn<T, U1>, TypedColumn<T, U2>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: Returns a new Dataset by computing the given Column expressions for each element.
select(TypedColumn<T, U1>, TypedColumn<T, U2>, TypedColumn<T, U3>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: Returns a new Dataset by computing the given Column expressions for each element.
select(TypedColumn<T, U1>, TypedColumn<T, U2>, TypedColumn<T, U3>, TypedColumn<T, U4>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: Returns a new Dataset by computing the given Column expressions for each element.
select(TypedColumn<T, U1>, TypedColumn<T, U2>, TypedColumn<T, U3>, TypedColumn<T, U4>, TypedColumn<T, U5>) - Method in class org.apache.spark.sql.Dataset
:: Experimental :: Returns a new Dataset by computing the given Column expressions for each element.
selectedFeatures() - Method in class org.apache.spark.ml.feature.ChiSqSelectorModel
list of indices to select (filter).
selectedFeatures() - Method in class org.apache.spark.mllib.feature.ChiSqSelectorModel
 
selectExpr(String...) - Method in class org.apache.spark.sql.Dataset
Selects a set of SQL expressions.
selectExpr(Seq<String>) - Method in class org.apache.spark.sql.Dataset
Selects a set of SQL expressions.
selectorType() - Method in interface org.apache.spark.ml.feature.ChiSqSelectorParams
The selector type of the ChisqSelector.
selectorType() - Method in class org.apache.spark.mllib.feature.ChiSqSelector
 
self() - Method in interface org.apache.spark.rpc.RpcEndpoint
The RpcEndpointRef of this RpcEndpoint.
sendData(String, Seq<Object>) - Method in interface org.apache.spark.streaming.kinesis.KinesisDataGenerator
Sends the data to Kinesis and returns the metadata for everything that has been sent.
sender() - Method in class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager
 
senderAddress() - Method in interface org.apache.spark.rpc.RpcCallContext
The sender of this message.
sendFailure(Throwable) - Method in interface org.apache.spark.rpc.RpcCallContext
Report a failure to the sender.
sendToDst(A) - Method in class org.apache.spark.graphx.EdgeContext
Sends a message to the destination vertex.
sendToDst(A) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
 
sendToSrc(A) - Method in class org.apache.spark.graphx.EdgeContext
Sends a message to the source vertex.
sendToSrc(A) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
 
sendWith(TransportClient) - Method in interface org.apache.spark.rpc.netty.OutboxMessage
 
seqToString(Seq<T>, Function1<T, String>) - Static method in class org.apache.spark.internal.config.ConfigHelpers
 
sequence() - Method in class org.apache.spark.mllib.fpm.PrefixSpan.FreqSequence
 
sequence(Column, Column, Column) - Static method in class org.apache.spark.sql.functions
Generate a sequence of integers from start to stop, incrementing by step.
sequence(Column, Column) - Static method in class org.apache.spark.sql.functions
Generate a sequence of integers from start to stop, incrementing by 1 if start is less than or equal to stop, otherwise -1.
sequenceCol() - Method in class org.apache.spark.ml.fpm.PrefixSpan
Param for the name of the sequence column in dataset (default "sequence"), rows with nulls in this column are ignored.
sequenceFile(String, Class<K>, Class<V>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
Get an RDD for a Hadoop SequenceFile with given key and value types.
sequenceFile(String, Class<K>, Class<V>) - Method in class org.apache.spark.api.java.JavaSparkContext
Get an RDD for a Hadoop SequenceFile.
sequenceFile(String, Class<K>, Class<V>, int) - Method in class org.apache.spark.SparkContext
Get an RDD for a Hadoop SequenceFile with given key and value types.
sequenceFile(String, Class<K>, Class<V>) - Method in class org.apache.spark.SparkContext
Get an RDD for a Hadoop SequenceFile with given key and value types.
sequenceFile(String, int, ClassTag<K>, ClassTag<V>, Function0<WritableConverter<K>>, Function0<WritableConverter<V>>) - Method in class org.apache.spark.SparkContext
Version of sequenceFile() for types implicitly convertible to Writables through a WritableConverter.
SequenceFileRDDFunctions<K,V> - Class in org.apache.spark.rdd
Extra functions available on RDDs of (key, value) pairs to create a Hadoop SequenceFile, through an implicit conversion.
SequenceFileRDDFunctions(RDD<Tuple2<K, V>>, Class<? extends Writable>, Class<? extends Writable>, Function1<K, Writable>, ClassTag<K>, Function1<V, Writable>, ClassTag<V>) - Constructor for class org.apache.spark.rdd.SequenceFileRDDFunctions
 
SER_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
 
SerDe - Class in org.apache.spark.api.r
Utility functions to serialize, deserialize objects to / from R
SerDe() - Constructor for class org.apache.spark.api.r.SerDe
 
SERDE() - Static method in class org.apache.spark.sql.hive.execution.HiveOptions
 
serde() - Method in class org.apache.spark.sql.hive.execution.HiveOptions
 
serdeProperties() - Method in class org.apache.spark.sql.hive.execution.HiveOptions
 
SerializableMapWrapper(Map<A, B>) - Constructor for class org.apache.spark.api.java.JavaUtils.SerializableMapWrapper
 
SerializableWritable<T extends org.apache.hadoop.io.Writable> - Class in org.apache.spark
 
SerializableWritable(T) - Constructor for class org.apache.spark.SerializableWritable
 
SerializationDebugger - Class in org.apache.spark.serializer
 
SerializationDebugger() - Constructor for class org.apache.spark.serializer.SerializationDebugger
 
SerializationDebugger.ObjectStreamClassMethods - Class in org.apache.spark.serializer
An implicit class that allows us to call private methods of ObjectStreamClass.
SerializationDebugger.ObjectStreamClassMethods$ - Class in org.apache.spark.serializer
 
SerializationFormats - Class in org.apache.spark.api.r
 
SerializationFormats() - Constructor for class org.apache.spark.api.r.SerializationFormats
 
SerializationStream - Class in org.apache.spark.serializer
:: DeveloperApi :: A stream for writing serialized objects.
SerializationStream() - Constructor for class org.apache.spark.serializer.SerializationStream
 
serializationStream() - Method in class org.apache.spark.storage.memory.SerializedValuesHolder
 
serialize(Vector) - Method in class org.apache.spark.mllib.linalg.VectorUDT
 
serialize(T, ClassTag<T>) - Method in class org.apache.spark.serializer.DummySerializerInstance
 
serialize(T, ClassTag<T>) - Method in class org.apache.spark.serializer.SerializerInstance
 
serialize(T) - Static method in class org.apache.spark.util.Utils
Serialize an object using Java serialization
SERIALIZED_R_DATA_SCHEMA() - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
serializedData() - Method in class org.apache.spark.scheduler.local.StatusUpdate
 
serializedMapStatus(org.apache.spark.broadcast.BroadcastManager, boolean, int) - Method in class org.apache.spark.ShuffleStatus
Serializes the mapStatuses array into an efficient compressed format.
SerializedMemoryEntry<T> - Class in org.apache.spark.storage.memory
 
SerializedMemoryEntry(org.apache.spark.util.io.ChunkedByteBuffer, MemoryMode, ClassTag<T>) - Constructor for class org.apache.spark.storage.memory.SerializedMemoryEntry
 
SerializedValuesHolder<T> - Class in org.apache.spark.storage.memory
A holder for storing the serialized values.
SerializedValuesHolder(BlockId, int, ClassTag<T>, MemoryMode, org.apache.spark.serializer.SerializerManager) - Constructor for class org.apache.spark.storage.memory.SerializedValuesHolder
 
Serializer - Class in org.apache.spark.serializer
:: DeveloperApi :: A serializer.
Serializer() - Constructor for class org.apache.spark.serializer.Serializer
 
serializer() - Method in class org.apache.spark.ShuffleDependency
 
serializer() - Method in class org.apache.spark.SparkEnv
 
SerializerInstance - Class in org.apache.spark.serializer
:: DeveloperApi :: An instance of a serializer, for use by one thread at a time.
SerializerInstance() - Constructor for class org.apache.spark.serializer.SerializerInstance
 
serializerManager() - Method in class org.apache.spark.SparkEnv
 
serializeStream(OutputStream) - Method in class org.apache.spark.serializer.DummySerializerInstance
 
serializeStream(OutputStream) - Method in class org.apache.spark.serializer.SerializerInstance
 
serializeViaNestedStream(OutputStream, SerializerInstance, Function1<SerializationStream, BoxedUnit>) - Static method in class org.apache.spark.util.Utils
Serialize via nested stream using specific serializer
servletContext() - Method in interface org.apache.spark.status.api.v1.ApiRequestContext
 
ServletParams(Function1<HttpServletRequest, T>, String, Function1<T, String>) - Constructor for class org.apache.spark.ui.JettyUtils.ServletParams
 
ServletParams$() - Constructor for class org.apache.spark.ui.JettyUtils.ServletParams$
 
session(SparkSession) - Static method in class org.apache.spark.ml.r.RWrappers
 
session(SparkSession) - Method in interface org.apache.spark.ml.util.BaseReadWrite
Sets the Spark Session to use for saving/loading.
session(SparkSession) - Method in class org.apache.spark.ml.util.GeneralMLWriter
 
session(SparkSession) - Method in class org.apache.spark.ml.util.MLReader
 
session(SparkSession) - Method in class org.apache.spark.ml.util.MLWriter
 
sessionCatalog() - Method in class org.apache.spark.sql.hive.RelationConversions
 
SessionConfigSupport - Interface in org.apache.spark.sql.sources.v2
A mix-in interface for DataSourceV2.
sessionState() - Method in class org.apache.spark.sql.SparkSession
State isolated across sessions, including SQL configurations, temporary tables, registered functions, and everything else that accepts a SQLConf.
set(long, long, int, int, VD, VD, ED) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
 
Set() - Static method in class org.apache.spark.metrics.sink.StatsdMetricType
 
set(Param<T>, T) - Method in interface org.apache.spark.ml.param.Params
Sets a parameter in the embedded param map.
set(String, Object) - Method in interface org.apache.spark.ml.param.Params
Sets a parameter (by name) in the embedded param map.
set(ParamPair<?>) - Method in interface org.apache.spark.ml.param.Params
Sets a parameter in the embedded param map.
set(String, long, long) - Static method in class org.apache.spark.rdd.InputFileBlockHolder
Sets the thread-local input block.
set(String, String) - Method in class org.apache.spark.SparkConf
Set a configuration variable.
set(SparkEnv) - Static method in class org.apache.spark.SparkEnv
 
set(String, String) - Method in class org.apache.spark.sql.RuntimeConfig
Sets the given Spark runtime configuration property.
set(String, boolean) - Method in class org.apache.spark.sql.RuntimeConfig
Sets the given Spark runtime configuration property.
set(String, long) - Method in class org.apache.spark.sql.RuntimeConfig
Sets the given Spark runtime configuration property.
set(long) - Method in class org.apache.spark.sql.types.Decimal
Set this Decimal to the given Long.
set(int) - Method in class org.apache.spark.sql.types.Decimal
Set this Decimal to the given Int.
set(long, int, int) - Method in class org.apache.spark.sql.types.Decimal
Set this Decimal to the given unscaled Long, with a given precision and scale.
set(BigDecimal, int, int) - Method in class org.apache.spark.sql.types.Decimal
Set this Decimal to the given BigDecimal value, with a given precision and scale.
set(BigDecimal) - Method in class org.apache.spark.sql.types.Decimal
Set this Decimal to the given BigDecimal value, inheriting its precision and scale.
set(BigInteger) - Method in class org.apache.spark.sql.types.Decimal
If the value is not in the range of long, convert it to BigDecimal and the precision and scale are based on the converted value.
set(Decimal) - Method in class org.apache.spark.sql.types.Decimal
Set this Decimal to the given Decimal value.
setActive(SQLContext) - Static method in class org.apache.spark.sql.SQLContext
Deprecated.
Use SparkSession.setActiveSession instead. Since 2.0.0.
setActiveSession(SparkSession) - Static method in class org.apache.spark.sql.SparkSession
Changes the SparkSession that will be returned in this thread and its children when SparkSession.getOrCreate() is called.
setAggregationDepth(int) - Method in class org.apache.spark.ml.classification.LinearSVC
Suggested depth for treeAggregate (greater than or equal to 2).
setAggregationDepth(int) - Method in class org.apache.spark.ml.classification.LogisticRegression
Suggested depth for treeAggregate (greater than or equal to 2).
setAggregationDepth(int) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
Suggested depth for treeAggregate (greater than or equal to 2).
setAggregationDepth(int) - Method in class org.apache.spark.ml.regression.LinearRegression
Suggested depth for treeAggregate (greater than or equal to 2).
setAggregator(Aggregator<K, V, C>) - Method in class org.apache.spark.rdd.ShuffledRDD
Set aggregator for RDD's shuffle.
setAlgo(String) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
Sets Algorithm using a String.
setAll(Traversable<Tuple2<String, String>>) - Method in class org.apache.spark.SparkConf
Set multiple parameters together
setAlpha(double) - Method in class org.apache.spark.ml.recommendation.ALS
 
setAlpha(Vector) - Method in class org.apache.spark.mllib.clustering.LDA
Alias for setDocConcentration()
setAlpha(double) - Method in class org.apache.spark.mllib.clustering.LDA
Alias for setDocConcentration()
setAlpha(double) - Method in class org.apache.spark.mllib.recommendation.ALS
Sets the constant used in computing confidence in implicit ALS.
setAppName(String) - Method in class org.apache.spark.launcher.AbstractLauncher
Set the application name.
setAppName(String) - Method in class org.apache.spark.launcher.SparkLauncher
 
setAppName(String) - Method in class org.apache.spark.SparkConf
Set a name for your application.
setAppResource(String) - Method in class org.apache.spark.launcher.AbstractLauncher
Set the main application resource.
setAppResource(String) - Method in class org.apache.spark.launcher.SparkLauncher
 
setBandwidth(double) - Method in class org.apache.spark.mllib.stat.KernelDensity
Sets the bandwidth (standard deviation) of the Gaussian kernel (default: 1.0).
setBeta(double) - Method in class org.apache.spark.mllib.clustering.LDA
Alias for setTopicConcentration()
setBinary(boolean) - Method in class org.apache.spark.ml.feature.CountVectorizer
 
setBinary(boolean) - Method in class org.apache.spark.ml.feature.CountVectorizerModel
 
setBinary(boolean) - Method in class org.apache.spark.ml.feature.HashingTF
 
setBinary(boolean) - Method in class org.apache.spark.mllib.feature.HashingTF
If true, term frequency vector will be binary such that non-zero term counts will be set to 1 (default: false)
setBlocks(int) - Method in class org.apache.spark.mllib.recommendation.ALS
Set the number of blocks for both user blocks and product blocks to parallelize the computation into; pass -1 for an auto-configured number of blocks.
setBlockSize(int) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
Sets the value of param blockSize.
setBucketLength(double) - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
 
setCacheNodeIds(boolean) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
 
setCacheNodeIds(boolean) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
setCacheNodeIds(boolean) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
 
setCacheNodeIds(boolean) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
 
setCacheNodeIds(boolean) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
setCacheNodeIds(boolean) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
 
setCacheNodeIds(boolean) - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setCallSite(String) - Method in class org.apache.spark.api.java.JavaSparkContext
Pass-through to SparkContext.setCallSite.
setCallSite(String) - Method in class org.apache.spark.SparkContext
Set the thread-local property for overriding the call sites of actions and RDDs.
setCaseSensitive(boolean) - Method in class org.apache.spark.ml.feature.StopWordsRemover
 
setCategoricalCols(String[]) - Method in class org.apache.spark.ml.feature.FeatureHasher
 
setCategoricalFeaturesInfo(Map<Integer, Integer>) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
Sets categoricalFeaturesInfo using a Java Map.
setCensorCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
 
setCheckpointDir(String) - Method in class org.apache.spark.api.java.JavaSparkContext
Set the directory under which RDDs are going to be checkpointed.
setCheckpointDir(String) - Method in class org.apache.spark.SparkContext
Set the directory under which RDDs are going to be checkpointed.
setCheckpointInterval(int) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
Specifies how often to checkpoint the cached node IDs.
setCheckpointInterval(int) - Method in class org.apache.spark.ml.classification.GBTClassifier
Specifies how often to checkpoint the cached node IDs.
setCheckpointInterval(int) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
Specifies how often to checkpoint the cached node IDs.
setCheckpointInterval(int) - Method in class org.apache.spark.ml.clustering.LDA
 
setCheckpointInterval(int) - Method in class org.apache.spark.ml.recommendation.ALS
 
setCheckpointInterval(int) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
Specifies how often to checkpoint the cached node IDs.
setCheckpointInterval(int) - Method in class org.apache.spark.ml.regression.GBTRegressor
Specifies how often to checkpoint the cached node IDs.
setCheckpointInterval(int) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
Specifies how often to checkpoint the cached node IDs.
setCheckpointInterval(int) - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setCheckpointInterval(int) - Method in class org.apache.spark.mllib.clustering.LDA
Parameter for set checkpoint interval (greater than or equal to 1) or disable checkpoint (-1).
setCheckpointInterval(int) - Method in class org.apache.spark.mllib.recommendation.ALS
:: DeveloperApi :: Set period (in iterations) between checkpoints (default = 10).
setCheckpointInterval(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
setClassifier(Classifier<?, ?, ?>) - Method in class org.apache.spark.ml.classification.OneVsRest
 
setColdStartStrategy(String) - Method in class org.apache.spark.ml.recommendation.ALS
 
setColdStartStrategy(String) - Method in class org.apache.spark.ml.recommendation.ALSModel
 
setCollectSubModels(boolean) - Method in class org.apache.spark.ml.tuning.CrossValidator
Whether to collect submodels when fitting.
setCollectSubModels(boolean) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
Whether to collect submodels when fitting.
setConf(Configuration) - Method in interface org.apache.spark.input.Configurable
 
setConf(String, String) - Method in class org.apache.spark.launcher.AbstractLauncher
Set a single configuration value for the application.
setConf(String, String) - Method in class org.apache.spark.launcher.SparkLauncher
 
setConf(Configuration) - Method in class org.apache.spark.ml.image.SamplePathFilter
 
setConf(Properties) - Method in class org.apache.spark.sql.SQLContext
Set Spark SQL configuration properties.
setConf(String, String) - Method in class org.apache.spark.sql.SQLContext
Set the given Spark SQL configuration property.
setConfig(String, String) - Static method in class org.apache.spark.launcher.SparkLauncher
Set a configuration value for the launcher library.
setConvergenceTol(double) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
Set the largest change in log-likelihood at which convergence is considered to have occurred.
setConvergenceTol(double) - Method in class org.apache.spark.mllib.optimization.GradientDescent
Set the convergence tolerance.
setConvergenceTol(double) - Method in class org.apache.spark.mllib.optimization.LBFGS
Set the convergence tolerance of iterations for L-BFGS.
setConvergenceTol(double) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
Set the convergence tolerance.
setCurrentDatabase(String) - Method in class org.apache.spark.sql.catalog.Catalog
Sets the current default database in this session.
setCurrentDatabase(String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Sets the name of current database.
setCustomHostname(String) - Static method in class org.apache.spark.util.Utils
Allow setting a custom host name because when we run on Mesos we need to use the same hostname it reports to the master.
setDAGScheduler(DAGScheduler) - Method in interface org.apache.spark.scheduler.TaskScheduler
 
setDecayFactor(double) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
Set the forgetfulness of the previous centroids.
setDefault(Param<T>, T) - Method in interface org.apache.spark.ml.param.Params
Sets a default value for a param.
setDefault(Seq<ParamPair<?>>) - Method in interface org.apache.spark.ml.param.Params
Sets default values for a list of params.
setDefaultClassLoader(ClassLoader) - Method in class org.apache.spark.serializer.Serializer
Sets a class loader for the serializer to use in deserialization.
setDefaultSession(SparkSession) - Static method in class org.apache.spark.sql.SparkSession
Sets the default SparkSession that is returned by the builder.
setDegree(int) - Method in class org.apache.spark.ml.feature.PolynomialExpansion
 
setDeployMode(String) - Method in class org.apache.spark.launcher.AbstractLauncher
Set the deploy mode for the application.
setDeployMode(String) - Method in class org.apache.spark.launcher.SparkLauncher
 
setDistanceMeasure(String) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
 
setDistanceMeasure(String) - Method in class org.apache.spark.ml.clustering.KMeans
 
setDistanceMeasure(String) - Method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
setDistanceMeasure(String) - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
Set the distance suite used by the algorithm.
setDistanceMeasure(String) - Method in class org.apache.spark.mllib.clustering.KMeans
Set the distance suite used by the algorithm.
setDocConcentration(double[]) - Method in class org.apache.spark.ml.clustering.LDA
 
setDocConcentration(double) - Method in class org.apache.spark.ml.clustering.LDA
 
setDocConcentration(Vector) - Method in class org.apache.spark.mllib.clustering.LDA
Concentration parameter (commonly named "alpha") for the prior placed on documents' distributions over topics ("theta").
setDocConcentration(double) - Method in class org.apache.spark.mllib.clustering.LDA
Replicates a Double docConcentration to create a symmetric prior.
setDropLast(boolean) - Method in class org.apache.spark.ml.feature.OneHotEncoder
Deprecated.
 
setDropLast(boolean) - Method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
 
setDropLast(boolean) - Method in class org.apache.spark.ml.feature.OneHotEncoderModel
 
setDstCol(String) - Method in class org.apache.spark.ml.clustering.PowerIterationClustering
 
setElasticNetParam(double) - Method in class org.apache.spark.ml.classification.LogisticRegression
Set the ElasticNet mixing parameter.
setElasticNetParam(double) - Method in class org.apache.spark.ml.regression.LinearRegression
Set the ElasticNet mixing parameter.
setEpsilon(double) - Method in class org.apache.spark.ml.regression.LinearRegression
Sets the value of param epsilon.
setEpsilon(double) - Method in class org.apache.spark.mllib.clustering.KMeans
Set the distance threshold within which we've consider centers to have converged.
setError(PrintStream) - Method in interface org.apache.spark.sql.hive.client.HiveClient
 
setEstimator(Estimator<?>) - Method in class org.apache.spark.ml.tuning.CrossValidator
 
setEstimator(Estimator<?>) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
 
setEstimatorParamMaps(ParamMap[]) - Method in class org.apache.spark.ml.tuning.CrossValidator
 
setEstimatorParamMaps(ParamMap[]) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
 
setEvaluator(Evaluator) - Method in class org.apache.spark.ml.tuning.CrossValidator
 
setEvaluator(Evaluator) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
 
setExecutorEnv(String, String) - Method in class org.apache.spark.SparkConf
Set an environment variable to be used when launching executors for this application.
setExecutorEnv(Seq<Tuple2<String, String>>) - Method in class org.apache.spark.SparkConf
Set multiple environment variables to be used when launching executors.
setExecutorEnv(Tuple2<String, String>[]) - Method in class org.apache.spark.SparkConf
Set multiple environment variables to be used when launching executors.
setFamily(String) - Method in class org.apache.spark.ml.classification.LogisticRegression
Sets the value of param family.
setFamily(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
Sets the value of param family.
setFdr(double) - Method in class org.apache.spark.ml.feature.ChiSqSelector
 
setFdr(double) - Method in class org.apache.spark.mllib.feature.ChiSqSelector
 
setFeatureIndex(int) - Method in class org.apache.spark.ml.regression.IsotonicRegression
 
setFeatureIndex(int) - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.classification.OneVsRest
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.classification.OneVsRestModel
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.GaussianMixture
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.KMeans
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.KMeansModel
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.LDA
The features for LDA should be a Vector representing the word counts in a document.
setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.LDAModel
The features for LDA should be a Vector representing the word counts in a document.
setFeaturesCol(String) - Method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.feature.ChiSqSelector
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.feature.ChiSqSelectorModel
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.feature.RFormula
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.PredictionModel
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.Predictor
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.regression.IsotonicRegression
 
setFeaturesCol(String) - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
 
setFeatureSubsetStrategy(String) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
setFeatureSubsetStrategy(String) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
 
setFeatureSubsetStrategy(String) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
setFeatureSubsetStrategy(String) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
 
setFeatureSubsetStrategy(String) - Method in interface org.apache.spark.ml.tree.TreeEnsembleParams
Deprecated.
This method is deprecated and will be removed in 3.0.0
setFinalRDDStorageLevel(StorageLevel) - Method in class org.apache.spark.mllib.recommendation.ALS
:: DeveloperApi :: Sets storage level for final RDDs (user/product used in MatrixFactorizationModel).
setFinalStorageLevel(String) - Method in class org.apache.spark.ml.recommendation.ALS
 
setFitIntercept(boolean) - Method in class org.apache.spark.ml.classification.LinearSVC
Whether to fit an intercept term.
setFitIntercept(boolean) - Method in class org.apache.spark.ml.classification.LogisticRegression
Whether to fit an intercept term.
setFitIntercept(boolean) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
Set if we should fit the intercept Default is true.
setFitIntercept(boolean) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
Sets if we should fit the intercept.
setFitIntercept(boolean) - Method in class org.apache.spark.ml.regression.LinearRegression
Set if we should fit the intercept.
setForceIndexLabel(boolean) - Method in class org.apache.spark.ml.feature.RFormula
 
setFormula(String) - Method in class org.apache.spark.ml.feature.RFormula
Sets the formula to use for this transformer.
setFpr(double) - Method in class org.apache.spark.ml.feature.ChiSqSelector
 
setFpr(double) - Method in class org.apache.spark.mllib.feature.ChiSqSelector
 
setFwe(double) - Method in class org.apache.spark.ml.feature.ChiSqSelector
 
setFwe(double) - Method in class org.apache.spark.mllib.feature.ChiSqSelector
 
setGaps(boolean) - Method in class org.apache.spark.ml.feature.RegexTokenizer
 
setGradient(Gradient) - Method in class org.apache.spark.mllib.optimization.GradientDescent
Set the gradient function (of the loss function of one single data example) to be used for SGD.
setGradient(Gradient) - Method in class org.apache.spark.mllib.optimization.LBFGS
Set the gradient function (of the loss function of one single data example) to be used for L-BFGS.
setHalfLife(double, String) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
Set the half life and time unit ("batches" or "points").
setHandleInvalid(String) - Method in class org.apache.spark.ml.feature.Bucketizer
 
setHandleInvalid(String) - Method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
 
setHandleInvalid(String) - Method in class org.apache.spark.ml.feature.OneHotEncoderModel
 
setHandleInvalid(String) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
setHandleInvalid(String) - Method in class org.apache.spark.ml.feature.RFormula
 
setHandleInvalid(String) - Method in class org.apache.spark.ml.feature.StringIndexer
 
setHandleInvalid(String) - Method in class org.apache.spark.ml.feature.StringIndexerModel
 
setHandleInvalid(String) - Method in class org.apache.spark.ml.feature.VectorAssembler
 
setHandleInvalid(String) - Method in class org.apache.spark.ml.feature.VectorIndexer
 
setHandleInvalid(String) - Method in class org.apache.spark.ml.feature.VectorSizeHint
 
setHashAlgorithm(String) - Method in class org.apache.spark.mllib.feature.HashingTF
Set the hash algorithm used when mapping term to integer.
setIfMissing(String, String) - Method in class org.apache.spark.SparkConf
Set a parameter if it isn't already configured
setImplicitPrefs(boolean) - Method in class org.apache.spark.ml.recommendation.ALS
 
setImplicitPrefs(boolean) - Method in class org.apache.spark.mllib.recommendation.ALS
Sets whether to use implicit preference.
setImpurity(String) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
 
setImpurity(String) - Method in class org.apache.spark.ml.classification.GBTClassifier
The impurity setting is ignored for GBT models.
setImpurity(String) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
 
setImpurity(String) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
 
setImpurity(String) - Method in class org.apache.spark.ml.regression.GBTRegressor
The impurity setting is ignored for GBT models.
setImpurity(String) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
 
setImpurity(String) - Method in interface org.apache.spark.ml.tree.TreeClassifierParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setImpurity(String) - Method in interface org.apache.spark.ml.tree.TreeRegressorParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setImpurity(Impurity) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
setIndices(int[]) - Method in class org.apache.spark.ml.feature.VectorSlicer
 
setInfo(PrintStream) - Method in interface org.apache.spark.sql.hive.client.HiveClient
 
setInitialCenters(Vector[], double[]) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
Specify initial centers directly.
setInitializationMode(String) - Method in class org.apache.spark.mllib.clustering.KMeans
Set the initialization algorithm.
setInitializationMode(String) - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering
Set the initialization mode.
setInitializationSteps(int) - Method in class org.apache.spark.mllib.clustering.KMeans
Set the number of steps for the k-means|| initialization mode.
setInitialModel(GaussianMixtureModel) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
Set the initial GMM starting point, bypassing the random initialization.
setInitialModel(KMeansModel) - Method in class org.apache.spark.mllib.clustering.KMeans
Set the initial starting point, bypassing the random initialization or k-means|| The condition model.k == this.k must be met, failure results in an IllegalArgumentException.
setInitialWeights(Vector) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
Sets the value of param initialWeights.
setInitialWeights(Vector) - Method in class org.apache.spark.mllib.classification.StreamingLogisticRegressionWithSGD
Set the initial weights.
setInitialWeights(Vector) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
Set the initial weights.
setInitMode(String) - Method in class org.apache.spark.ml.clustering.KMeans
 
setInitMode(String) - Method in class org.apache.spark.ml.clustering.PowerIterationClustering
 
setInitSteps(int) - Method in class org.apache.spark.ml.clustering.KMeans
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.Binarizer
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.Bucketizer
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.CountVectorizer
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.CountVectorizerModel
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.HashingTF
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.IDF
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.IDFModel
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.IndexToString
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.MaxAbsScaler
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.MaxAbsScalerModel
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.MinHashLSH
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.MinHashLSHModel
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.MinMaxScaler
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.OneHotEncoder
Deprecated.
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.PCA
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.PCAModel
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.StandardScaler
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.StandardScalerModel
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.StopWordsRemover
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.StringIndexer
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.StringIndexerModel
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.VectorIndexer
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.VectorIndexerModel
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.VectorSizeHint
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.VectorSlicer
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.Word2Vec
 
setInputCol(String) - Method in class org.apache.spark.ml.feature.Word2VecModel
 
setInputCol(String) - Method in class org.apache.spark.ml.UnaryTransformer
 
setInputCols(String[]) - Method in class org.apache.spark.ml.feature.Bucketizer
 
setInputCols(Seq<String>) - Method in class org.apache.spark.ml.feature.FeatureHasher
 
setInputCols(String[]) - Method in class org.apache.spark.ml.feature.FeatureHasher
 
setInputCols(String[]) - Method in class org.apache.spark.ml.feature.Imputer
 
setInputCols(String[]) - Method in class org.apache.spark.ml.feature.ImputerModel
 
setInputCols(String[]) - Method in class org.apache.spark.ml.feature.Interaction
 
setInputCols(String[]) - Method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
 
setInputCols(String[]) - Method in class org.apache.spark.ml.feature.OneHotEncoderModel
 
setInputCols(String[]) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
setInputCols(String[]) - Method in class org.apache.spark.ml.feature.VectorAssembler
 
setIntercept(boolean) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
Set if the algorithm should add an intercept.
setIntermediateRDDStorageLevel(StorageLevel) - Method in class org.apache.spark.mllib.recommendation.ALS
:: DeveloperApi :: Sets storage level for intermediate RDDs (user/product in/out links).
setIntermediateStorageLevel(String) - Method in class org.apache.spark.ml.recommendation.ALS
 
setInverse(boolean) - Method in class org.apache.spark.ml.feature.DCT
 
setIsotonic(boolean) - Method in class org.apache.spark.ml.regression.IsotonicRegression
 
setIsotonic(boolean) - Method in class org.apache.spark.mllib.regression.IsotonicRegression
Sets the isotonic parameter.
setItemCol(String) - Method in class org.apache.spark.ml.recommendation.ALS
 
setItemCol(String) - Method in class org.apache.spark.ml.recommendation.ALSModel
 
setItemsCol(String) - Method in class org.apache.spark.ml.fpm.FPGrowth
 
setItemsCol(String) - Method in class org.apache.spark.ml.fpm.FPGrowthModel
 
setIterations(int) - Method in class org.apache.spark.mllib.recommendation.ALS
Set the number of iterations to run.
setJars(Seq<String>) - Method in class org.apache.spark.SparkConf
Set JAR files to distribute to the cluster.
setJars(String[]) - Method in class org.apache.spark.SparkConf
Set JAR files to distribute to the cluster.
setJavaHome(String) - Method in class org.apache.spark.launcher.SparkLauncher
Set a custom JAVA_HOME for launching the Spark application.
setJobDescription(String) - Method in class org.apache.spark.api.java.JavaSparkContext
Set a human readable description of the current job.
setJobDescription(String) - Method in class org.apache.spark.SparkContext
Set a human readable description of the current job.
setJobGroup(String, String, boolean) - Method in class org.apache.spark.api.java.JavaSparkContext
Assigns a group ID to all the jobs started by this thread until the group ID is set to a different value or cleared.
setJobGroup(String, String) - Method in class org.apache.spark.api.java.JavaSparkContext
Assigns a group ID to all the jobs started by this thread until the group ID is set to a different value or cleared.
setJobGroup(String, String, boolean) - Method in class org.apache.spark.SparkContext
Assigns a group ID to all the jobs started by this thread until the group ID is set to a different value or cleared.
setK(int) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
 
setK(int) - Method in class org.apache.spark.ml.clustering.GaussianMixture
 
setK(int) - Method in class org.apache.spark.ml.clustering.KMeans
 
setK(int) - Method in class org.apache.spark.ml.clustering.LDA
 
setK(int) - Method in class org.apache.spark.ml.clustering.PowerIterationClustering
 
setK(int) - Method in class org.apache.spark.ml.feature.PCA
 
setK(int) - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
Sets the desired number of leaf clusters (default: 4).
setK(int) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
Set the number of Gaussians in the mixture model.
setK(int) - Method in class org.apache.spark.mllib.clustering.KMeans
Set the number of clusters to create (k).
setK(int) - Method in class org.apache.spark.mllib.clustering.LDA
Set the number of topics to infer, i.e., the number of soft cluster centers.
setK(int) - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering
Set the number of clusters.
setK(int) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
Set the number of clusters.
setKappa(double) - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
Learning rate: exponential decay rate---should be between (0.5, 1.0] to guarantee asymptotic convergence.
setKeepLastCheckpoint(boolean) - Method in class org.apache.spark.ml.clustering.LDA
 
setKeepLastCheckpoint(boolean) - Method in class org.apache.spark.mllib.clustering.EMLDAOptimizer
If using checkpointing, this indicates whether to keep the last checkpoint (vs clean up).
setKeyOrdering(Ordering<K>) - Method in class org.apache.spark.rdd.ShuffledRDD
Set key ordering for RDD's shuffle.
setLabelCol(String) - Method in class org.apache.spark.ml.classification.OneVsRest
 
setLabelCol(String) - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
 
setLabelCol(String) - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
 
setLabelCol(String) - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
 
setLabelCol(String) - Method in class org.apache.spark.ml.feature.ChiSqSelector
 
setLabelCol(String) - Method in class org.apache.spark.ml.feature.RFormula
 
setLabelCol(String) - Method in class org.apache.spark.ml.Predictor
 
setLabelCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
 
setLabelCol(String) - Method in class org.apache.spark.ml.regression.IsotonicRegression
 
setLabels(String[]) - Method in class org.apache.spark.ml.feature.IndexToString
 
setLambda(double) - Method in class org.apache.spark.mllib.classification.NaiveBayes
Set the smoothing parameter.
setLambda(double) - Method in class org.apache.spark.mllib.recommendation.ALS
Set the regularization parameter, lambda.
setLayers(int[]) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
Sets the value of param layers.
setLearningDecay(double) - Method in class org.apache.spark.ml.clustering.LDA
 
setLearningOffset(double) - Method in class org.apache.spark.ml.clustering.LDA
 
setLearningRate(double) - Method in class org.apache.spark.mllib.feature.Word2Vec
Sets initial learning rate (default: 0.025).
setLearningRate(double) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
setLink(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
Sets the value of param link.
setLinkPower(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
Sets the value of param linkPower.
setLinkPredictionCol(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
Sets the link prediction (linear predictor) column name.
setLinkPredictionCol(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
Sets the link prediction (linear predictor) column name.
setLocale(String) - Method in class org.apache.spark.ml.feature.StopWordsRemover
 
setLocalProperty(String, String) - Method in class org.apache.spark.api.java.JavaSparkContext
Set a local property that affects jobs submitted from this thread, and all child threads, such as the Spark fair scheduler pool.
setLocalProperty(String, String) - Method in class org.apache.spark.SparkContext
Set a local property that affects jobs submitted from this thread, such as the Spark fair scheduler pool.
setLogLevel(String) - Method in class org.apache.spark.api.java.JavaSparkContext
Control our logLevel.
setLogLevel(String) - Method in class org.apache.spark.SparkContext
Control our logLevel.
setLogLevel(Level) - Static method in class org.apache.spark.util.Utils
configure a new log4j level
setLoss(String) - Method in class org.apache.spark.ml.regression.LinearRegression
Sets the value of param loss.
setLoss(Loss) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
setLossType(String) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
setLossType(String) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
setLowerBoundsOnCoefficients(Matrix) - Method in class org.apache.spark.ml.classification.LogisticRegression
Set the lower bounds on coefficients if fitting under bound constrained optimization.
setLowerBoundsOnIntercepts(Vector) - Method in class org.apache.spark.ml.classification.LogisticRegression
Set the lower bounds on intercepts if fitting under bound constrained optimization.
setMainClass(String) - Method in class org.apache.spark.launcher.AbstractLauncher
Sets the application class name for Java/Scala applications.
setMainClass(String) - Method in class org.apache.spark.launcher.SparkLauncher
 
setMapSideCombine(boolean) - Method in class org.apache.spark.rdd.ShuffledRDD
Set mapSideCombine flag for RDD's shuffle.
setMaster(String) - Method in class org.apache.spark.launcher.AbstractLauncher
Set the Spark master for the application.
setMaster(String) - Method in class org.apache.spark.launcher.SparkLauncher
 
setMaster(String) - Method in class org.apache.spark.SparkConf
The master URL to connect to, such as "local" to run locally with one thread, "local[4]" to run locally with 4 cores, or "spark://master:7077" to run on a Spark standalone cluster.
setMax(double) - Method in class org.apache.spark.ml.feature.MinMaxScaler
 
setMax(double) - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
 
setMaxBins(int) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
 
setMaxBins(int) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
setMaxBins(int) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
 
setMaxBins(int) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
 
setMaxBins(int) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
setMaxBins(int) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
 
setMaxBins(int) - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setMaxBins(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
setMaxCategories(int) - Method in class org.apache.spark.ml.feature.VectorIndexer
 
setMaxDepth(int) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
 
setMaxDepth(int) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
setMaxDepth(int) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
 
setMaxDepth(int) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
 
setMaxDepth(int) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
setMaxDepth(int) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
 
setMaxDepth(int) - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setMaxDepth(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
setMaxDF(double) - Method in class org.apache.spark.ml.feature.CountVectorizer
 
setMaxIter(int) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
setMaxIter(int) - Method in class org.apache.spark.ml.classification.LinearSVC
Set the maximum number of iterations.
setMaxIter(int) - Method in class org.apache.spark.ml.classification.LogisticRegression
Set the maximum number of iterations.
setMaxIter(int) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
Set the maximum number of iterations.
setMaxIter(int) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
 
setMaxIter(int) - Method in class org.apache.spark.ml.clustering.GaussianMixture
 
setMaxIter(int) - Method in class org.apache.spark.ml.clustering.KMeans
 
setMaxIter(int) - Method in class org.apache.spark.ml.clustering.LDA
 
setMaxIter(int) - Method in class org.apache.spark.ml.clustering.PowerIterationClustering
 
setMaxIter(int) - Method in class org.apache.spark.ml.feature.Word2Vec
 
setMaxIter(int) - Method in class org.apache.spark.ml.recommendation.ALS
 
setMaxIter(int) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
Set the maximum number of iterations.
setMaxIter(int) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
setMaxIter(int) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
Sets the maximum number of iterations (applicable for solver "irls").
setMaxIter(int) - Method in class org.apache.spark.ml.regression.LinearRegression
Set the maximum number of iterations.
setMaxIter(int) - Method in interface org.apache.spark.ml.tree.GBTParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setMaxIterations(int) - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
Sets the max number of k-means iterations to split clusters (default: 20).
setMaxIterations(int) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
Set the maximum number of iterations allowed.
setMaxIterations(int) - Method in class org.apache.spark.mllib.clustering.KMeans
Set maximum number of iterations allowed.
setMaxIterations(int) - Method in class org.apache.spark.mllib.clustering.LDA
Set the maximum number of iterations allowed.
setMaxIterations(int) - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering
Set maximum number of iterations of the power iteration loop
setMaxLocalProjDBSize(long) - Method in class org.apache.spark.ml.fpm.PrefixSpan
 
setMaxLocalProjDBSize(long) - Method in class org.apache.spark.mllib.fpm.PrefixSpan
Sets the maximum number of items (including delimiters used in the internal storage format) allowed in a projected database before local processing (default: 32000000L).
setMaxMemoryInMB(int) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
 
setMaxMemoryInMB(int) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
setMaxMemoryInMB(int) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
 
setMaxMemoryInMB(int) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
 
setMaxMemoryInMB(int) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
setMaxMemoryInMB(int) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
 
setMaxMemoryInMB(int) - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setMaxMemoryInMB(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
setMaxPatternLength(int) - Method in class org.apache.spark.ml.fpm.PrefixSpan
 
setMaxPatternLength(int) - Method in class org.apache.spark.mllib.fpm.PrefixSpan
Sets maximal pattern length (default: 10).
setMaxSentenceLength(int) - Method in class org.apache.spark.ml.feature.Word2Vec
 
setMaxSentenceLength(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
Sets the maximum length (in words) of each sentence in the input data.
setMetricName(String) - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
 
setMetricName(String) - Method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
setMetricName(String) - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
 
setMetricName(String) - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
 
setMin(double) - Method in class org.apache.spark.ml.feature.MinMaxScaler
 
setMin(double) - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
 
setMinConfidence(double) - Method in class org.apache.spark.ml.fpm.FPGrowth
 
setMinConfidence(double) - Method in class org.apache.spark.ml.fpm.FPGrowthModel
 
setMinConfidence(double) - Method in class org.apache.spark.mllib.fpm.AssociationRules
Sets the minimal confidence (default: 0.8).
setMinCount(int) - Method in class org.apache.spark.ml.feature.Word2Vec
 
setMinCount(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
Sets minCount, the minimum number of times a token must appear to be included in the word2vec model's vocabulary (default: 5).
setMinDF(double) - Method in class org.apache.spark.ml.feature.CountVectorizer
 
setMinDivisibleClusterSize(double) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
 
setMinDivisibleClusterSize(double) - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
Sets the minimum number of points (if greater than or equal to 1.0) or the minimum proportion of points (if less than 1.0) of a divisible cluster (default: 1).
setMinDocFreq(int) - Method in class org.apache.spark.ml.feature.IDF
 
setMiniBatchFraction(double) - Method in class org.apache.spark.mllib.classification.StreamingLogisticRegressionWithSGD
Set the fraction of each batch to use for updates.
setMiniBatchFraction(double) - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
Mini-batch fraction in (0, 1], which sets the fraction of document sampled and used in each iteration.
setMiniBatchFraction(double) - Method in class org.apache.spark.mllib.optimization.GradientDescent
Set fraction of data to be used for each SGD iteration.
setMiniBatchFraction(double) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
Set the fraction of each batch to use for updates.
setMinInfoGain(double) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
 
setMinInfoGain(double) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
setMinInfoGain(double) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
 
setMinInfoGain(double) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
 
setMinInfoGain(double) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
setMinInfoGain(double) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
 
setMinInfoGain(double) - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setMinInfoGain(double) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
setMinInstancesPerNode(int) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
 
setMinInstancesPerNode(int) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
setMinInstancesPerNode(int) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
 
setMinInstancesPerNode(int) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
 
setMinInstancesPerNode(int) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
setMinInstancesPerNode(int) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
 
setMinInstancesPerNode(int) - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setMinInstancesPerNode(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
setMinSupport(double) - Method in class org.apache.spark.ml.fpm.FPGrowth
 
setMinSupport(double) - Method in class org.apache.spark.ml.fpm.PrefixSpan
 
setMinSupport(double) - Method in class org.apache.spark.mllib.fpm.FPGrowth
Sets the minimal support level (default: 0.3).
setMinSupport(double) - Method in class org.apache.spark.mllib.fpm.PrefixSpan
Sets the minimal support level (default: 0.1).
setMinTF(double) - Method in class org.apache.spark.ml.feature.CountVectorizer
 
setMinTF(double) - Method in class org.apache.spark.ml.feature.CountVectorizerModel
 
setMinTokenLength(int) - Method in class org.apache.spark.ml.feature.RegexTokenizer
 
setMissingValue(double) - Method in class org.apache.spark.ml.feature.Imputer
 
setModelType(String) - Method in class org.apache.spark.ml.classification.NaiveBayes
Set the model type using a string (case-sensitive).
setModelType(String) - Method in class org.apache.spark.mllib.classification.NaiveBayes
Set the model type using a string (case-sensitive).
setN(int) - Method in class org.apache.spark.ml.feature.NGram
 
setName(String) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Assign a name to this RDD
setName(String) - Method in class org.apache.spark.api.java.JavaPairRDD
Assign a name to this RDD
setName(String) - Method in class org.apache.spark.api.java.JavaRDD
Assign a name to this RDD
setName(String) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
setName(String) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
setName(String) - Method in class org.apache.spark.rdd.RDD
Assign a name to this RDD
setNames(String[]) - Method in class org.apache.spark.ml.feature.VectorSlicer
 
setNonnegative(boolean) - Method in class org.apache.spark.ml.recommendation.ALS
 
setNonnegative(boolean) - Method in class org.apache.spark.mllib.recommendation.ALS
Set whether the least-squares problems solved at each iteration should have nonnegativity constraints.
setNullAt(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
setNullAt(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
setNumBlocks(int) - Method in class org.apache.spark.ml.recommendation.ALS
Sets both numUserBlocks and numItemBlocks to the specific value.
setNumBuckets(int) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
setNumBucketsArray(int[]) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
setNumClasses(int) - Method in class org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
Set the number of possible outcomes for k classes classification problem in Multinomial Logistic Regression.
setNumClasses(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
setNumCorrections(int) - Method in class org.apache.spark.mllib.optimization.LBFGS
Set the number of corrections used in the LBFGS update.
setNumFeatures(int) - Method in class org.apache.spark.ml.feature.FeatureHasher
 
setNumFeatures(int) - Method in class org.apache.spark.ml.feature.HashingTF
 
setNumFolds(int) - Method in class org.apache.spark.ml.tuning.CrossValidator
 
setNumHashTables(int) - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
 
setNumHashTables(int) - Method in class org.apache.spark.ml.feature.MinHashLSH
 
setNumItemBlocks(int) - Method in class org.apache.spark.ml.recommendation.ALS
 
setNumIterations(int) - Method in class org.apache.spark.mllib.classification.StreamingLogisticRegressionWithSGD
Set the number of iterations of gradient descent to run per update.
setNumIterations(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
Sets number of iterations (default: 1), which should be smaller than or equal to number of partitions.
setNumIterations(int) - Method in class org.apache.spark.mllib.optimization.GradientDescent
Set the number of iterations for SGD.
setNumIterations(int) - Method in class org.apache.spark.mllib.optimization.LBFGS
Set the maximal number of iterations for L-BFGS.
setNumIterations(int) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
Set the number of iterations of gradient descent to run per update.
setNumIterations(int) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
setNumPartitions(int) - Method in class org.apache.spark.ml.feature.Word2Vec
 
setNumPartitions(int) - Method in class org.apache.spark.ml.fpm.FPGrowth
 
setNumPartitions(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
Sets number of partitions (default: 1).
setNumPartitions(int) - Method in class org.apache.spark.mllib.fpm.FPGrowth
Sets the number of partitions used by parallel FP-growth (default: same as input data).
setNumRows(int) - Method in class org.apache.spark.sql.vectorized.ColumnarBatch
Sets the number of rows in this batch.
setNumTopFeatures(int) - Method in class org.apache.spark.ml.feature.ChiSqSelector
 
setNumTopFeatures(int) - Method in class org.apache.spark.mllib.feature.ChiSqSelector
 
setNumTrees(int) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
 
setNumTrees(int) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
 
setNumTrees(int) - Method in interface org.apache.spark.ml.tree.RandomForestParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setNumUserBlocks(int) - Method in class org.apache.spark.ml.recommendation.ALS
 
setOffsetCol(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
Sets the value of param offsetCol.
setOffsetRange(Optional<Offset>, Optional<Offset>) - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.MicroBatchReader
Set the desired offset range for input partitions created from this reader.
setOptimizeDocConcentration(boolean) - Method in class org.apache.spark.ml.clustering.LDA
 
setOptimizeDocConcentration(boolean) - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
Sets whether to optimize docConcentration parameter during training.
setOptimizer(String) - Method in class org.apache.spark.ml.clustering.LDA
 
setOptimizer(LDAOptimizer) - Method in class org.apache.spark.mllib.clustering.LDA
:: DeveloperApi ::
setOptimizer(String) - Method in class org.apache.spark.mllib.clustering.LDA
Set the LDAOptimizer used to perform the actual calculation by algorithm name.
setOrNull(long, int, int) - Method in class org.apache.spark.sql.types.Decimal
Set this Decimal to the given unscaled Long, with a given precision and scale, and return it, or return null if it cannot be set due to overflow.
setOut(PrintStream) - Method in interface org.apache.spark.sql.hive.client.HiveClient
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.Binarizer
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.Bucketizer
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.ChiSqSelector
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.ChiSqSelectorModel
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.CountVectorizer
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.CountVectorizerModel
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.FeatureHasher
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.HashingTF
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.IDF
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.IDFModel
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.IndexToString
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.Interaction
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.MaxAbsScaler
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.MaxAbsScalerModel
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.MinHashLSH
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.MinHashLSHModel
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.MinMaxScaler
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.OneHotEncoder
Deprecated.
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.PCA
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.PCAModel
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.StandardScaler
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.StandardScalerModel
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.StopWordsRemover
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.StringIndexer
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.StringIndexerModel
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.VectorAssembler
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.VectorIndexer
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.VectorIndexerModel
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.VectorSlicer
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.Word2Vec
 
setOutputCol(String) - Method in class org.apache.spark.ml.feature.Word2VecModel
 
setOutputCol(String) - Method in class org.apache.spark.ml.UnaryTransformer
 
setOutputCols(String[]) - Method in class org.apache.spark.ml.feature.Bucketizer
 
setOutputCols(String[]) - Method in class org.apache.spark.ml.feature.Imputer
 
setOutputCols(String[]) - Method in class org.apache.spark.ml.feature.ImputerModel
 
setOutputCols(String[]) - Method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
 
setOutputCols(String[]) - Method in class org.apache.spark.ml.feature.OneHotEncoderModel
 
setOutputCols(String[]) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
setP(double) - Method in class org.apache.spark.ml.feature.Normalizer
 
setParallelism(int) - Method in class org.apache.spark.ml.classification.OneVsRest
The implementation of parallel one vs.
setParallelism(int) - Method in class org.apache.spark.ml.tuning.CrossValidator
Set the maximum level of parallelism to evaluate models in parallel.
setParallelism(int) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
Set the maximum level of parallelism to evaluate models in parallel.
setParent(Estimator<M>) - Method in class org.apache.spark.ml.Model
Sets the parent of this model (Java API).
setPattern(String) - Method in class org.apache.spark.ml.feature.RegexTokenizer
 
setPeacePeriod(int) - Method in class org.apache.spark.mllib.stat.test.StreamingTest
Set the number of initial batches to ignore.
setPercentile(double) - Method in class org.apache.spark.ml.feature.ChiSqSelector
 
setPercentile(double) - Method in class org.apache.spark.mllib.feature.ChiSqSelector
 
setPredictionCol(String) - Method in class org.apache.spark.ml.classification.OneVsRest
 
setPredictionCol(String) - Method in class org.apache.spark.ml.classification.OneVsRestModel
 
setPredictionCol(String) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
 
setPredictionCol(String) - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
 
setPredictionCol(String) - Method in class org.apache.spark.ml.clustering.GaussianMixture
 
setPredictionCol(String) - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
 
setPredictionCol(String) - Method in class org.apache.spark.ml.clustering.KMeans
 
setPredictionCol(String) - Method in class org.apache.spark.ml.clustering.KMeansModel
 
setPredictionCol(String) - Method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
setPredictionCol(String) - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
 
setPredictionCol(String) - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
 
setPredictionCol(String) - Method in class org.apache.spark.ml.fpm.FPGrowth
 
setPredictionCol(String) - Method in class org.apache.spark.ml.fpm.FPGrowthModel
 
setPredictionCol(String) - Method in class org.apache.spark.ml.PredictionModel
 
setPredictionCol(String) - Method in class org.apache.spark.ml.Predictor
 
setPredictionCol(String) - Method in class org.apache.spark.ml.recommendation.ALS
 
setPredictionCol(String) - Method in class org.apache.spark.ml.recommendation.ALSModel
 
setPredictionCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
 
setPredictionCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
setPredictionCol(String) - Method in class org.apache.spark.ml.regression.IsotonicRegression
 
setPredictionCol(String) - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
 
setProbabilityCol(String) - Method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
 
setProbabilityCol(String) - Method in class org.apache.spark.ml.classification.ProbabilisticClassifier
 
setProbabilityCol(String) - Method in class org.apache.spark.ml.clustering.GaussianMixture
 
setProbabilityCol(String) - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
 
setProductBlocks(int) - Method in class org.apache.spark.mllib.recommendation.ALS
Set the number of product blocks to parallelize the computation.
setPropertiesFile(String) - Method in class org.apache.spark.launcher.AbstractLauncher
Set a custom properties file with Spark configuration for the application.
setPropertiesFile(String) - Method in class org.apache.spark.launcher.SparkLauncher
 
setQuantileCalculationStrategy(Enumeration.Value) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
setQuantileProbabilities(double[]) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
 
setQuantileProbabilities(double[]) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
setQuantilesCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
 
setQuantilesCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
setRandomCenters(int, double, long) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
Initialize random centers, requiring only the number of dimensions.
setRank(int) - Method in class org.apache.spark.ml.recommendation.ALS
 
setRank(int) - Method in class org.apache.spark.mllib.recommendation.ALS
Set the rank of the feature matrices computed (number of features).
setRatingCol(String) - Method in class org.apache.spark.ml.recommendation.ALS
 
setRawPredictionCol(String) - Method in class org.apache.spark.ml.classification.ClassificationModel
 
setRawPredictionCol(String) - Method in class org.apache.spark.ml.classification.Classifier
 
setRawPredictionCol(String) - Method in class org.apache.spark.ml.classification.OneVsRest
 
setRawPredictionCol(String) - Method in class org.apache.spark.ml.classification.OneVsRestModel
 
setRawPredictionCol(String) - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
 
setRegParam(double) - Method in class org.apache.spark.ml.classification.LinearSVC
Set the regularization parameter.
setRegParam(double) - Method in class org.apache.spark.ml.classification.LogisticRegression
Set the regularization parameter.
setRegParam(double) - Method in class org.apache.spark.ml.recommendation.ALS
 
setRegParam(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
Sets the regularization parameter for L2 regularization.
setRegParam(double) - Method in class org.apache.spark.ml.regression.LinearRegression
Set the regularization parameter.
setRegParam(double) - Method in class org.apache.spark.mllib.classification.StreamingLogisticRegressionWithSGD
Set the regularization parameter.
setRegParam(double) - Method in class org.apache.spark.mllib.optimization.GradientDescent
Set the regularization parameter.
setRegParam(double) - Method in class org.apache.spark.mllib.optimization.LBFGS
Set the regularization parameter.
setRegParam(double) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
Set the regularization parameter.
setRelativeError(double) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
setRequiredColumns(Configuration, StructType, StructType) - Static method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
setRest(long, int, VD, ED) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
 
setRuns(int) - Method in class org.apache.spark.mllib.clustering.KMeans
Deprecated.
This has no effect. Since 2.1.0.
setSample(RDD<Object>) - Method in class org.apache.spark.mllib.stat.KernelDensity
Sets the sample to use for density estimation.
setSample(JavaRDD<Double>) - Method in class org.apache.spark.mllib.stat.KernelDensity
Sets the sample to use for density estimation (for Java users).
setScalingVec(Vector) - Method in class org.apache.spark.ml.feature.ElementwiseProduct
 
setSeed(long) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
 
setSeed(long) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
setSeed(long) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
Set the seed for weights initialization if weights are not set
setSeed(long) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
 
setSeed(long) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
 
setSeed(long) - Method in class org.apache.spark.ml.clustering.GaussianMixture
 
setSeed(long) - Method in class org.apache.spark.ml.clustering.KMeans
 
setSeed(long) - Method in class org.apache.spark.ml.clustering.LDA
 
setSeed(long) - Method in class org.apache.spark.ml.clustering.LDAModel
 
setSeed(long) - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
 
setSeed(long) - Method in class org.apache.spark.ml.feature.MinHashLSH
 
setSeed(long) - Method in class org.apache.spark.ml.feature.Word2Vec
 
setSeed(long) - Method in class org.apache.spark.ml.recommendation.ALS
 
setSeed(long) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
 
setSeed(long) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
setSeed(long) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
 
setSeed(long) - Method in interface org.apache.spark.ml.tree.DecisionTreeParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setSeed(long) - Method in class org.apache.spark.ml.tuning.CrossValidator
 
setSeed(long) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
 
setSeed(long) - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
Sets the random seed (default: hash value of the class name).
setSeed(long) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
Set the random seed
setSeed(long) - Method in class org.apache.spark.mllib.clustering.KMeans
Set the random seed for cluster initialization.
setSeed(long) - Method in class org.apache.spark.mllib.clustering.LDA
Set the random seed for cluster initialization.
setSeed(long) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
Set the random seed for cluster initialization.
setSeed(long) - Method in class org.apache.spark.mllib.feature.Word2Vec
Sets random seed (default: a random long integer).
setSeed(long) - Method in class org.apache.spark.mllib.random.ExponentialGenerator
 
setSeed(long) - Method in class org.apache.spark.mllib.random.GammaGenerator
 
setSeed(long) - Method in class org.apache.spark.mllib.random.LogNormalGenerator
 
setSeed(long) - Method in class org.apache.spark.mllib.random.PoissonGenerator
 
setSeed(long) - Method in class org.apache.spark.mllib.random.StandardNormalGenerator
 
setSeed(long) - Method in class org.apache.spark.mllib.random.UniformGenerator
 
setSeed(long) - Method in class org.apache.spark.mllib.random.WeibullGenerator
 
setSeed(long) - Method in class org.apache.spark.mllib.recommendation.ALS
Sets a random seed to have deterministic results.
setSeed(long) - Method in class org.apache.spark.util.random.BernoulliCellSampler
 
setSeed(long) - Method in class org.apache.spark.util.random.BernoulliSampler
 
setSeed(long) - Method in class org.apache.spark.util.random.PoissonSampler
 
setSeed(long) - Method in interface org.apache.spark.util.random.Pseudorandom
Set random seed.
setSelectorType(String) - Method in class org.apache.spark.ml.feature.ChiSqSelector
 
setSelectorType(String) - Method in class org.apache.spark.mllib.feature.ChiSqSelector
 
setSequenceCol(String) - Method in class org.apache.spark.ml.fpm.PrefixSpan
 
setSerializer(Serializer) - Method in class org.apache.spark.rdd.CoGroupedRDD
Set a serializer for this RDD's shuffle, or null to use the default (spark.serializer)
setSerializer(Serializer) - Method in class org.apache.spark.rdd.ShuffledRDD
Set a serializer for this RDD's shuffle, or null to use the default (spark.serializer)
setSize(int) - Method in class org.apache.spark.ml.feature.VectorSizeHint
 
setSmoothing(double) - Method in class org.apache.spark.ml.classification.NaiveBayes
Set the smoothing parameter.
setSolver(String) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
Sets the value of param solver.
setSolver(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
Sets the solver algorithm used for optimization.
setSolver(String) - Method in class org.apache.spark.ml.regression.LinearRegression
Set the solver algorithm used for optimization.
setSparkContextSessionConf(SparkSession, Map<Object, Object>) - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
setSparkHome(String) - Method in class org.apache.spark.launcher.SparkLauncher
Set a custom Spark installation location for the application.
setSparkHome(String) - Method in class org.apache.spark.SparkConf
Set the location where Spark is installed on worker nodes.
setSplits(double[]) - Method in class org.apache.spark.ml.feature.Bucketizer
 
setSplitsArray(double[][]) - Method in class org.apache.spark.ml.feature.Bucketizer
 
setSQLReadObject(Function2<DataInputStream, Object, Object>) - Static method in class org.apache.spark.api.r.SerDe
 
setSQLWriteObject(Function2<DataOutputStream, Object, Object>) - Static method in class org.apache.spark.api.r.SerDe
 
setSrcCol(String) - Method in class org.apache.spark.ml.clustering.PowerIterationClustering
 
setSrcOnly(long, int, VD) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
 
setStages(PipelineStage[]) - Method in class org.apache.spark.ml.Pipeline
 
setStandardization(boolean) - Method in class org.apache.spark.ml.classification.LinearSVC
Whether to standardize the training features before fitting the model.
setStandardization(boolean) - Method in class org.apache.spark.ml.classification.LogisticRegression
Whether to standardize the training features before fitting the model.
setStandardization(boolean) - Method in class org.apache.spark.ml.regression.LinearRegression
Whether to standardize the training features before fitting the model.
setStartOffset(Optional<Offset>) - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.ContinuousReader
Set the desired start offset for partitions created from this reader.
setStatement(String) - Method in class org.apache.spark.ml.feature.SQLTransformer
 
setStepSize(double) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
setStepSize(double) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
Sets the value of param stepSize (applicable only for solver "gd").
setStepSize(double) - Method in class org.apache.spark.ml.feature.Word2Vec
 
setStepSize(double) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
setStepSize(double) - Method in interface org.apache.spark.ml.tree.GBTParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setStepSize(double) - Method in class org.apache.spark.mllib.classification.StreamingLogisticRegressionWithSGD
Set the step size for gradient descent.
setStepSize(double) - Method in class org.apache.spark.mllib.optimization.GradientDescent
Set the initial step size of SGD for the first step.
setStepSize(double) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
Set the step size for gradient descent.
setStopWords(String[]) - Method in class org.apache.spark.ml.feature.StopWordsRemover
 
setStorageLevel(String) - Method in class org.apache.spark.status.LiveRDD
 
setStrategy(String) - Method in class org.apache.spark.ml.feature.Imputer
Imputation strategy.
setStringIndexerOrderType(String) - Method in class org.apache.spark.ml.feature.RFormula
 
setStringOrderType(String) - Method in class org.apache.spark.ml.feature.StringIndexer
 
setSubsamplingRate(double) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
setSubsamplingRate(double) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
 
setSubsamplingRate(double) - Method in class org.apache.spark.ml.clustering.LDA
 
setSubsamplingRate(double) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
setSubsamplingRate(double) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
 
setSubsamplingRate(double) - Method in interface org.apache.spark.ml.tree.TreeEnsembleParams
Deprecated.
This method is deprecated and will be removed in 3.0.0.
setSubsamplingRate(double) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
setTau0(double) - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
A (positive) learning parameter that downweights early iterations.
setTestMethod(String) - Method in class org.apache.spark.mllib.stat.test.StreamingTest
Set the statistical method used for significance testing.
setThreshold(double) - Method in class org.apache.spark.ml.classification.LinearSVC
Set threshold in binary classification.
setThreshold(double) - Method in class org.apache.spark.ml.classification.LinearSVCModel
 
setThreshold(double) - Method in class org.apache.spark.ml.classification.LogisticRegression
 
setThreshold(double) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
 
setThreshold(double) - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
Set threshold in binary classification, in range [0, 1].
setThreshold(double) - Method in class org.apache.spark.ml.feature.Binarizer
 
setThreshold(double) - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
Sets the threshold that separates positive predictions from negative predictions in Binary Logistic Regression.
setThreshold(double) - Method in class org.apache.spark.mllib.classification.SVMModel
Sets the threshold that separates positive predictions from negative predictions.
setThresholds(double[]) - Method in class org.apache.spark.ml.classification.LogisticRegression
 
setThresholds(double[]) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
 
setThresholds(double[]) - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
Set thresholds in multiclass (or binary) classification to adjust the probability of predicting each class.
setThresholds(double[]) - Method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
 
setThresholds(double[]) - Method in class org.apache.spark.ml.classification.ProbabilisticClassifier
 
setTimeoutDuration(long) - Method in interface org.apache.spark.sql.streaming.GroupState
Set the timeout duration in ms for this key.
setTimeoutDuration(String) - Method in interface org.apache.spark.sql.streaming.GroupState
Set the timeout duration for this key as a string.
setTimeoutTimestamp(long) - Method in interface org.apache.spark.sql.streaming.GroupState
Set the timeout timestamp for this key as milliseconds in epoch time.
setTimeoutTimestamp(long, String) - Method in interface org.apache.spark.sql.streaming.GroupState
Set the timeout timestamp for this key as milliseconds in epoch time and an additional duration as a string (e.g.
setTimeoutTimestamp(Date) - Method in interface org.apache.spark.sql.streaming.GroupState
Set the timeout timestamp for this key as a java.sql.Date.
setTimeoutTimestamp(Date, String) - Method in interface org.apache.spark.sql.streaming.GroupState
Set the timeout timestamp for this key as a java.sql.Date and an additional duration as a string (e.g.
setTol(double) - Method in class org.apache.spark.ml.classification.LinearSVC
Set the convergence tolerance of iterations.
setTol(double) - Method in class org.apache.spark.ml.classification.LogisticRegression
Set the convergence tolerance of iterations.
setTol(double) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
Set the convergence tolerance of iterations.
setTol(double) - Method in class org.apache.spark.ml.clustering.GaussianMixture
 
setTol(double) - Method in class org.apache.spark.ml.clustering.KMeans
 
setTol(double) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
Set the convergence tolerance of iterations.
setTol(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
Sets the convergence tolerance of iterations.
setTol(double) - Method in class org.apache.spark.ml.regression.LinearRegression
Set the convergence tolerance of iterations.
setToLowercase(boolean) - Method in class org.apache.spark.ml.feature.RegexTokenizer
 
setTopicConcentration(double) - Method in class org.apache.spark.ml.clustering.LDA
 
setTopicConcentration(double) - Method in class org.apache.spark.mllib.clustering.LDA
Concentration parameter (commonly named "beta" or "eta") for the prior placed on topics' distributions over terms.
setTopicDistributionCol(String) - Method in class org.apache.spark.ml.clustering.LDA
 
setTopicDistributionCol(String) - Method in class org.apache.spark.ml.clustering.LDAModel
 
setTrainRatio(double) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
 
setTreeStrategy(Strategy) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
setUiRoot(ContextHandler, UIRoot) - Static method in class org.apache.spark.status.api.v1.UIRootFromServletContext
 
setupCommitter(TaskAttemptContext) - Method in class org.apache.spark.internal.io.HadoopMapRedCommitProtocol
 
setUpdater(Updater) - Method in class org.apache.spark.mllib.optimization.GradientDescent
Set the updater function to actually perform a gradient step in a given direction.
setUpdater(Updater) - Method in class org.apache.spark.mllib.optimization.LBFGS
Set the updater function to actually perform a gradient step in a given direction.
SetupDriver(org.apache.spark.rpc.RpcEndpointRef) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SetupDriver
 
SetupDriver$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SetupDriver$
 
setupGroups(int, DefaultPartitionCoalescer.PartitionLocations) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
Initializes targetLen partition groups.
setupJob(JobContext) - Method in class org.apache.spark.internal.io.FileCommitProtocol
Setups up a job.
setupJob(JobContext) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
 
setUpperBoundsOnCoefficients(Matrix) - Method in class org.apache.spark.ml.classification.LogisticRegression
Set the upper bounds on coefficients if fitting under bound constrained optimization.
setUpperBoundsOnIntercepts(Vector) - Method in class org.apache.spark.ml.classification.LogisticRegression
Set the upper bounds on intercepts if fitting under bound constrained optimization.
setupTask(TaskAttemptContext) - Method in class org.apache.spark.internal.io.FileCommitProtocol
Sets up a task within a job.
setupTask(TaskAttemptContext) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
 
setupUI(org.apache.spark.ui.SparkUI) - Method in interface org.apache.spark.status.AppHistoryServerPlugin
Sets up UI of this plugin to rebuild the history UI.
setUseNodeIdCache(boolean) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
setUserBlocks(int) - Method in class org.apache.spark.mllib.recommendation.ALS
Set the number of user blocks to parallelize the computation.
setUserCol(String) - Method in class org.apache.spark.ml.recommendation.ALS
 
setUserCol(String) - Method in class org.apache.spark.ml.recommendation.ALSModel
 
setValidateData(boolean) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
Set if the algorithm should validate data before training.
setValidationIndicatorCol(String) - Method in class org.apache.spark.ml.classification.GBTClassifier
 
setValidationIndicatorCol(String) - Method in class org.apache.spark.ml.regression.GBTRegressor
 
setValidationTol(double) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
setValue(R) - Method in class org.apache.spark.Accumulable
Deprecated.
Set the accumulator's value.
setVarianceCol(String) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
 
setVarianceCol(String) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
 
setVariancePower(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
Sets the value of param variancePower.
setVectorSize(int) - Method in class org.apache.spark.ml.feature.Word2Vec
 
setVectorSize(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
Sets vector size (default: 100).
setVerbose(boolean) - Method in class org.apache.spark.launcher.AbstractLauncher
Enables verbose reporting for SparkSubmit.
setVerbose(boolean) - Method in class org.apache.spark.launcher.SparkLauncher
 
setVocabSize(int) - Method in class org.apache.spark.ml.feature.CountVectorizer
 
setWeightCol(String) - Method in class org.apache.spark.ml.classification.LinearSVC
Set the value of param weightCol.
setWeightCol(double) - Method in class org.apache.spark.ml.classification.LinearSVCModel
Deprecated.
This method is deprecated and will be removed in 3.0.0. Since 2.4.4.
setWeightCol(String) - Method in class org.apache.spark.ml.classification.LogisticRegression
Sets the value of param weightCol.
setWeightCol(String) - Method in class org.apache.spark.ml.classification.NaiveBayes
Sets the value of param weightCol.
setWeightCol(String) - Method in class org.apache.spark.ml.classification.OneVsRest
Sets the value of param weightCol.
setWeightCol(String) - Method in class org.apache.spark.ml.clustering.PowerIterationClustering
 
setWeightCol(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
Sets the value of param weightCol.
setWeightCol(String) - Method in class org.apache.spark.ml.regression.IsotonicRegression
 
setWeightCol(String) - Method in class org.apache.spark.ml.regression.LinearRegression
Whether to over-/under-sample training instances according to the given weights in weightCol.
setWindowSize(int) - Method in class org.apache.spark.ml.feature.Word2Vec
 
setWindowSize(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
Sets the window of words (default: 5)
setWindowSize(int) - Method in class org.apache.spark.mllib.stat.test.StreamingTest
Set the number of batches to compute significance tests over.
setWithMean(boolean) - Method in class org.apache.spark.ml.feature.StandardScaler
 
setWithMean(boolean) - Method in class org.apache.spark.mllib.feature.StandardScalerModel
:: DeveloperApi ::
setWithStd(boolean) - Method in class org.apache.spark.ml.feature.StandardScaler
 
setWithStd(boolean) - Method in class org.apache.spark.mllib.feature.StandardScalerModel
:: DeveloperApi ::
sha1(Column) - Static method in class org.apache.spark.sql.functions
Calculates the SHA-1 digest of a binary column and returns the value as a 40 character hex string.
sha2(Column, int) - Static method in class org.apache.spark.sql.functions
Calculates the SHA-2 family of hash functions of a binary column and returns the value as a hex string.
shape() - Method in class org.apache.spark.mllib.random.GammaGenerator
 
SharedParamsCodeGen - Class in org.apache.spark.ml.param.shared
Code generator for shared params (sharedParams.scala).
SharedParamsCodeGen() - Constructor for class org.apache.spark.ml.param.shared.SharedParamsCodeGen
 
SharedReadWrite$() - Constructor for class org.apache.spark.ml.Pipeline.SharedReadWrite$
 
sharedState() - Method in class org.apache.spark.sql.SparkSession
State shared across sessions, including the SparkContext, cached data, listener, and a catalog that interacts with external systems.
shiftLeft(Column, int) - Static method in class org.apache.spark.sql.functions
Shift the given value numBits left.
shiftRight(Column, int) - Static method in class org.apache.spark.sql.functions
(Signed) shift the given value numBits right.
shiftRightUnsigned(Column, int) - Static method in class org.apache.spark.sql.functions
Unsigned shift the given value numBits right.
SHORT() - Static method in class org.apache.spark.sql.Encoders
An encoder for nullable short type.
ShortestPaths - Class in org.apache.spark.graphx.lib
Computes shortest paths to the given set of landmark vertices, returning a graph where each vertex attribute is a map containing the shortest-path distance to each reachable landmark.
ShortestPaths() - Constructor for class org.apache.spark.graphx.lib.ShortestPaths
 
shortName() - Method in interface org.apache.spark.ml.util.MLFormatRegister
 
shortName() - Method in class org.apache.spark.sql.hive.execution.HiveFileFormat
 
shortName() - Method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
shortName() - Method in interface org.apache.spark.sql.sources.DataSourceRegister
The string that represents the format that this data source provider uses.
shortTimeUnitString(TimeUnit) - Static method in class org.apache.spark.streaming.ui.UIUtils
Return the short string for a TimeUnit.
ShortType - Static variable in class org.apache.spark.sql.types.DataTypes
Gets the ShortType object.
ShortType - Class in org.apache.spark.sql.types
The data type representing Short values.
ShortType() - Constructor for class org.apache.spark.sql.types.ShortType
 
shouldCloseFileAfterWrite(SparkConf, boolean) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
 
shouldDistributeGaussians(int, int) - Static method in class org.apache.spark.mllib.clustering.GaussianMixture
Heuristic to distribute the computation of the MultivariateGaussians, approximately when d is greater than 25 except for when k is very small.
shouldGoLeft(Vector) - Method in interface org.apache.spark.ml.tree.Split
Return true (split to left) or false (split to right).
shouldGoLeft(int, Split[]) - Method in interface org.apache.spark.ml.tree.Split
Return true (split to left) or false (split to right).
shouldOwn(Param<?>) - Method in interface org.apache.spark.ml.param.Params
Validates that the input param belongs to this instance.
shouldRollover(long) - Method in interface org.apache.spark.util.logging.RollingPolicy
Whether rollover should be initiated at this moment
show(int) - Method in class org.apache.spark.sql.Dataset
Displays the Dataset in a tabular form.
show() - Method in class org.apache.spark.sql.Dataset
Displays the top 20 rows of Dataset in a tabular form.
show(boolean) - Method in class org.apache.spark.sql.Dataset
Displays the top 20 rows of Dataset in a tabular form.
show(int, boolean) - Method in class org.apache.spark.sql.Dataset
Displays the Dataset in a tabular form.
show(int, int) - Method in class org.apache.spark.sql.Dataset
Displays the Dataset in a tabular form.
show(int, int, boolean) - Method in class org.apache.spark.sql.Dataset
Displays the Dataset in a tabular form.
showBytesDistribution(String, Function2<TaskInfo, TaskMetrics, Object>, Seq<Tuple2<TaskInfo, TaskMetrics>>) - Static method in class org.apache.spark.scheduler.StatsReportListener
 
showBytesDistribution(String, Option<org.apache.spark.util.Distribution>) - Static method in class org.apache.spark.scheduler.StatsReportListener
 
showBytesDistribution(String, org.apache.spark.util.Distribution) - Static method in class org.apache.spark.scheduler.StatsReportListener
 
showDagVizForJob(int, Seq<org.apache.spark.ui.scope.RDDOperationGraph>) - Static method in class org.apache.spark.ui.UIUtils
Return a "DAG visualization" DOM element that expands into a visualization for a job.
showDagVizForStage(int, Option<org.apache.spark.ui.scope.RDDOperationGraph>) - Static method in class org.apache.spark.ui.UIUtils
Return a "DAG visualization" DOM element that expands into a visualization for a stage.
showDistribution(String, org.apache.spark.util.Distribution, Function1<Object, String>) - Static method in class org.apache.spark.scheduler.StatsReportListener
 
showDistribution(String, Option<org.apache.spark.util.Distribution>, Function1<Object, String>) - Static method in class org.apache.spark.scheduler.StatsReportListener
 
showDistribution(String, Option<org.apache.spark.util.Distribution>, String) - Static method in class org.apache.spark.scheduler.StatsReportListener
 
showDistribution(String, String, Function2<TaskInfo, TaskMetrics, Object>, Seq<Tuple2<TaskInfo, TaskMetrics>>) - Static method in class org.apache.spark.scheduler.StatsReportListener
 
showMillisDistribution(String, Option<org.apache.spark.util.Distribution>) - Static method in class org.apache.spark.scheduler.StatsReportListener
 
showMillisDistribution(String, Function2<TaskInfo, TaskMetrics, Object>, Seq<Tuple2<TaskInfo, TaskMetrics>>) - Static method in class org.apache.spark.scheduler.StatsReportListener
 
showMillisDistribution(String, Function1<BatchInfo, Option<Object>>) - Method in class org.apache.spark.streaming.scheduler.StatsReportListener
 
shuffle(Column) - Static method in class org.apache.spark.sql.functions
Returns a random permutation of the given array.
SHUFFLE() - Static method in class org.apache.spark.storage.BlockId
 
SHUFFLE_DATA() - Static method in class org.apache.spark.storage.BlockId
 
SHUFFLE_INDEX() - Static method in class org.apache.spark.storage.BlockId
 
SHUFFLE_LOCAL_BLOCKS() - Static method in class org.apache.spark.status.TaskIndexNames
 
SHUFFLE_READ() - Static method in class org.apache.spark.ui.ToolTips
 
SHUFFLE_READ_BLOCKED_TIME() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
 
SHUFFLE_READ_BLOCKED_TIME() - Static method in class org.apache.spark.ui.ToolTips
 
SHUFFLE_READ_METRICS_PREFIX() - Static method in class org.apache.spark.InternalAccumulator
 
SHUFFLE_READ_RECORDS() - Static method in class org.apache.spark.status.TaskIndexNames
 
SHUFFLE_READ_REMOTE_SIZE() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
 
SHUFFLE_READ_REMOTE_SIZE() - Static method in class org.apache.spark.ui.ToolTips
 
SHUFFLE_READ_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
 
SHUFFLE_REMOTE_BLOCKS() - Static method in class org.apache.spark.status.TaskIndexNames
 
SHUFFLE_REMOTE_READS() - Static method in class org.apache.spark.status.TaskIndexNames
 
SHUFFLE_REMOTE_READS_TO_DISK() - Static method in class org.apache.spark.status.TaskIndexNames
 
SHUFFLE_TOTAL_BLOCKS() - Static method in class org.apache.spark.status.TaskIndexNames
 
SHUFFLE_TOTAL_READS() - Static method in class org.apache.spark.status.TaskIndexNames
 
SHUFFLE_WRITE() - Static method in class org.apache.spark.ui.ToolTips
 
SHUFFLE_WRITE_METRICS_PREFIX() - Static method in class org.apache.spark.InternalAccumulator
 
SHUFFLE_WRITE_RECORDS() - Static method in class org.apache.spark.status.TaskIndexNames
 
SHUFFLE_WRITE_SIZE() - Static method in class org.apache.spark.status.TaskIndexNames
 
SHUFFLE_WRITE_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
 
ShuffleBlockId - Class in org.apache.spark.storage
 
ShuffleBlockId(int, int, int) - Constructor for class org.apache.spark.storage.ShuffleBlockId
 
shuffleCleaned(int) - Method in interface org.apache.spark.CleanerListener
 
ShuffleDataBlockId - Class in org.apache.spark.storage
 
ShuffleDataBlockId(int, int, int) - Constructor for class org.apache.spark.storage.ShuffleDataBlockId
 
ShuffleDependency<K,V,C> - Class in org.apache.spark
:: DeveloperApi :: Represents a dependency on the output of a shuffle stage.
ShuffleDependency(RDD<? extends Product2<K, V>>, Partitioner, Serializer, Option<Ordering<K>>, Option<Aggregator<K, V, C>>, boolean, ClassTag<K>, ClassTag<V>, ClassTag<C>) - Constructor for class org.apache.spark.ShuffleDependency
 
ShuffledRDD<K,V,C> - Class in org.apache.spark.rdd
:: DeveloperApi :: The resulting RDD from a shuffle (e.g.
ShuffledRDD(RDD<? extends Product2<K, V>>, Partitioner, ClassTag<K>, ClassTag<V>, ClassTag<C>) - Constructor for class org.apache.spark.rdd.ShuffledRDD
 
shuffleHandle() - Method in class org.apache.spark.ShuffleDependency
 
shuffleId() - Method in class org.apache.spark.CleanShuffle
 
shuffleId() - Method in class org.apache.spark.FetchFailed
 
shuffleId() - Method in class org.apache.spark.ShuffleDependency
 
shuffleId() - Method in class org.apache.spark.storage.BlockManagerMessages.RemoveShuffle
 
shuffleId() - Method in class org.apache.spark.storage.ShuffleBlockId
 
shuffleId() - Method in class org.apache.spark.storage.ShuffleDataBlockId
 
shuffleId() - Method in class org.apache.spark.storage.ShuffleIndexBlockId
 
ShuffleIndexBlockId - Class in org.apache.spark.storage
 
ShuffleIndexBlockId(int, int, int) - Constructor for class org.apache.spark.storage.ShuffleIndexBlockId
 
shuffleManager() - Method in class org.apache.spark.SparkEnv
 
shuffleRead() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
shuffleRead$() - Constructor for class org.apache.spark.InternalAccumulator.shuffleRead$
 
shuffleReadBytes() - Method in class org.apache.spark.status.api.v1.StageData
 
ShuffleReadMetricDistributions - Class in org.apache.spark.status.api.v1
 
ShuffleReadMetrics - Class in org.apache.spark.status.api.v1
 
shuffleReadMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
shuffleReadMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 
shuffleReadRecords() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
shuffleReadRecords() - Method in class org.apache.spark.status.api.v1.StageData
 
ShuffleStatus - Class in org.apache.spark
Helper class used by the MapOutputTrackerMaster to perform bookkeeping for a single ShuffleMapStage.
ShuffleStatus(int) - Constructor for class org.apache.spark.ShuffleStatus
 
shuffleWrite() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
shuffleWrite$() - Constructor for class org.apache.spark.InternalAccumulator.shuffleWrite$
 
shuffleWriteBytes() - Method in class org.apache.spark.status.api.v1.StageData
 
ShuffleWriteMetricDistributions - Class in org.apache.spark.status.api.v1
 
ShuffleWriteMetrics - Class in org.apache.spark.status.api.v1
 
shuffleWriteMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
 
shuffleWriteMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetrics
 
shuffleWriteRecords() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
shuffleWriteRecords() - Method in class org.apache.spark.status.api.v1.StageData
 
shutdown() - Method in interface org.apache.spark.ExecutorPlugin
Clean up and terminate this plugin.
shutdown(ExecutorService, Duration) - Static method in class org.apache.spark.util.ThreadUtils
 
Shutdown$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.Shutdown$
 
ShutdownHookManager - Class in org.apache.spark.util
Various utility methods used by Spark.
ShutdownHookManager() - Constructor for class org.apache.spark.util.ShutdownHookManager
 
sigma() - Method in class org.apache.spark.mllib.stat.distribution.MultivariateGaussian
 
sigmas() - Method in class org.apache.spark.mllib.clustering.ExpectationSum
 
SignalUtils - Class in org.apache.spark.util
Contains utilities for working with posix signals.
SignalUtils() - Constructor for class org.apache.spark.util.SignalUtils
 
signum(Column) - Static method in class org.apache.spark.sql.functions
Computes the signum of the given value.
signum(String) - Static method in class org.apache.spark.sql.functions
Computes the signum of the given column.
SimpleFutureAction<T> - Class in org.apache.spark
A FutureAction holding the result of an action that triggers a single job.
simpleString() - Method in class org.apache.spark.sql.types.ArrayType
 
simpleString() - Static method in class org.apache.spark.sql.types.BinaryType
 
simpleString() - Static method in class org.apache.spark.sql.types.BooleanType
 
simpleString() - Method in class org.apache.spark.sql.types.ByteType
 
simpleString() - Static method in class org.apache.spark.sql.types.CalendarIntervalType
 
simpleString() - Method in class org.apache.spark.sql.types.CharType
 
simpleString() - Method in class org.apache.spark.sql.types.DataType
Readable string representation for the type.
simpleString() - Static method in class org.apache.spark.sql.types.DateType
 
simpleString() - Method in class org.apache.spark.sql.types.DecimalType
 
simpleString() - Static method in class org.apache.spark.sql.types.DoubleType
 
simpleString() - Static method in class org.apache.spark.sql.types.FloatType
 
simpleString() - Method in class org.apache.spark.sql.types.IntegerType
 
simpleString() - Method in class org.apache.spark.sql.types.LongType
 
simpleString() - Method in class org.apache.spark.sql.types.MapType
 
simpleString() - Static method in class org.apache.spark.sql.types.NullType
 
simpleString() - Method in class org.apache.spark.sql.types.ObjectType
 
simpleString() - Method in class org.apache.spark.sql.types.ShortType
 
simpleString() - Static method in class org.apache.spark.sql.types.StringType
 
simpleString() - Method in class org.apache.spark.sql.types.StructType
 
simpleString() - Static method in class org.apache.spark.sql.types.TimestampType
 
simpleString() - Method in class org.apache.spark.sql.types.VarcharType
 
SimpleUpdater - Class in org.apache.spark.mllib.optimization
:: DeveloperApi :: A simple updater for gradient descent *without* any regularization.
SimpleUpdater() - Constructor for class org.apache.spark.mllib.optimization.SimpleUpdater
 
sin(Column) - Static method in class org.apache.spark.sql.functions
 
sin(String) - Static method in class org.apache.spark.sql.functions
 
SingularValueDecomposition<UType,VType> - Class in org.apache.spark.mllib.linalg
Represents singular value decomposition (SVD) factors.
SingularValueDecomposition(UType, Vector, VType) - Constructor for class org.apache.spark.mllib.linalg.SingularValueDecomposition
 
sinh(Column) - Static method in class org.apache.spark.sql.functions
 
sinh(String) - Static method in class org.apache.spark.sql.functions
 
Sink - Interface in org.apache.spark.metrics.sink
 
sink() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
 
SinkProgress - Class in org.apache.spark.sql.streaming
Information about progress made for a sink in the execution of a StreamingQuery during a trigger.
size() - Method in class org.apache.spark.api.java.JavaUtils.SerializableMapWrapper
 
size() - Method in class org.apache.spark.ml.attribute.AttributeGroup
Size of the attribute group.
size() - Method in class org.apache.spark.ml.feature.VectorSizeHint
The size of Vectors in inputCol.
size() - Method in class org.apache.spark.ml.linalg.DenseVector
 
size() - Method in class org.apache.spark.ml.linalg.SparseVector
 
size() - Method in interface org.apache.spark.ml.linalg.Vector
Size of the vector.
size() - Method in class org.apache.spark.ml.param.ParamMap
Number of param pairs in this map.
size() - Method in class org.apache.spark.mllib.linalg.DenseVector
 
size() - Method in class org.apache.spark.mllib.linalg.SparseVector
 
size() - Method in interface org.apache.spark.mllib.linalg.Vector
Size of the vector.
size(Column) - Static method in class org.apache.spark.sql.functions
Returns length of array or map.
size() - Method in interface org.apache.spark.sql.Row
Number of elements in the Row.
size() - Method in interface org.apache.spark.storage.BlockData
 
size() - Method in class org.apache.spark.storage.DiskBlockData
 
size() - Method in class org.apache.spark.storage.memory.DeserializedMemoryEntry
 
size() - Method in interface org.apache.spark.storage.memory.MemoryEntry
 
size() - Method in class org.apache.spark.storage.memory.SerializedMemoryEntry
 
SizeEstimator - Class in org.apache.spark.util
:: DeveloperApi :: Estimates the sizes of Java objects (number of bytes of memory they occupy), for use in memory-aware caches.
SizeEstimator() - Constructor for class org.apache.spark.util.SizeEstimator
 
sizeInBytes() - Method in class org.apache.spark.sql.sources.BaseRelation
Returns an estimated size of this relation in bytes.
sizeInBytes() - Method in interface org.apache.spark.sql.sources.v2.reader.Statistics
 
sketch(RDD<K>, int, ClassTag<K>) - Static method in class org.apache.spark.RangePartitioner
Sketches the input RDD via reservoir sampling on each partition.
skewness(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the skewness of the values in a group.
skewness(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the skewness of the values in a group.
skip(long) - Method in class org.apache.spark.io.NioBufferedFileInputStream
 
skip(long) - Method in class org.apache.spark.io.ReadAheadInputStream
 
skip(long) - Method in class org.apache.spark.storage.BufferReleasingInputStream
 
skippedStages() - Method in class org.apache.spark.status.LiveJob
 
skippedTasks() - Method in class org.apache.spark.status.LiveJob
 
skipWhitespace() - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
slice(Column, int, int) - Static method in class org.apache.spark.sql.functions
Returns an array containing all the elements in x from index start (or starting from the end if start is negative) with the specified length.
slice(Time, Time) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return all the RDDs between 'fromDuration' to 'toDuration' (both included)
slice(org.apache.spark.streaming.Interval) - Method in class org.apache.spark.streaming.dstream.DStream
Return all the RDDs defined by the Interval object (both end times included)
slice(Time, Time) - Method in class org.apache.spark.streaming.dstream.DStream
Return all the RDDs between 'fromTime' to 'toTime' (both included)
slideDuration() - Method in class org.apache.spark.streaming.dstream.DStream
Time interval after which the DStream generates an RDD
slideDuration() - Method in class org.apache.spark.streaming.dstream.InputDStream
 
sliding(int, int) - Method in class org.apache.spark.mllib.rdd.RDDFunctions
Returns an RDD from grouping items of its parent RDD in fixed size blocks by passing a sliding window over them.
sliding(int) - Method in class org.apache.spark.mllib.rdd.RDDFunctions
sliding(Int, Int)* with step = 1.
smoothing() - Method in interface org.apache.spark.ml.classification.NaiveBayesParams
The smoothing parameter.
SnappyCompressionCodec - Class in org.apache.spark.io
:: DeveloperApi :: Snappy implementation of CompressionCodec.
SnappyCompressionCodec(SparkConf) - Constructor for class org.apache.spark.io.SnappyCompressionCodec
 
SnappyOutputStreamWrapper - Class in org.apache.spark.io
Wrapper over SnappyOutputStream which guards against write-after-close and double-close issues.
SnappyOutputStreamWrapper(SnappyOutputStream) - Constructor for class org.apache.spark.io.SnappyOutputStreamWrapper
 
socketStream(String, int, Function<InputStream, Iterable<T>>, StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream from network source hostname:port.
socketStream(String, int, Function1<InputStream, Iterator<T>>, StorageLevel, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
Creates an input stream from TCP source hostname:port.
socketTextStream(String, int, StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream from network source hostname:port.
socketTextStream(String, int) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream from network source hostname:port.
socketTextStream(String, int, StorageLevel) - Method in class org.apache.spark.streaming.StreamingContext
Creates an input stream from TCP source hostname:port.
solve(double, double, DenseVector, DenseVector, DenseVector) - Method in interface org.apache.spark.ml.optim.NormalEquationSolver
Solve the normal equations from summary statistics.
solve(ALS.NormalEquation, double) - Method in interface org.apache.spark.ml.recommendation.ALS.LeastSquaresNESolver
Solves a least squares problem with regularization (possibly with other constraints).
solve(double[], double[]) - Static method in class org.apache.spark.mllib.linalg.CholeskyDecomposition
Solves a symmetric positive definite linear system via Cholesky factorization.
solve(double[], double[], NNLS.Workspace) - Static method in class org.apache.spark.mllib.optimization.NNLS
Solve a least squares problem, possibly with nonnegativity constraints, by a modified projected gradient method.
solver() - Method in interface org.apache.spark.ml.classification.MultilayerPerceptronParams
The solver algorithm for optimization.
solver() - Method in interface org.apache.spark.ml.param.shared.HasSolver
Param for the solver algorithm for optimization.
solver() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
The solver algorithm for optimization.
solver() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionTrainingSummary
 
solver() - Method in interface org.apache.spark.ml.regression.LinearRegressionParams
The solver algorithm for optimization.
Sort() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
 
sort(String, String...) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset sorted by the specified column, all in ascending order.
sort(Column...) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset sorted by the given expressions.
sort(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset sorted by the specified column, all in ascending order.
sort(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset sorted by the given expressions.
sort_array(Column) - Static method in class org.apache.spark.sql.functions
Sorts the input array for the given column in ascending order, according to the natural ordering of the array elements.
sort_array(Column, boolean) - Static method in class org.apache.spark.sql.functions
Sorts the input array for the given column in ascending or descending order, according to the natural ordering of the array elements.
sortBy(Function<T, S>, boolean, int) - Method in class org.apache.spark.api.java.JavaRDD
Return this RDD sorted by the given key function.
sortBy(Function1<T, K>, boolean, int, Ordering<K>, ClassTag<K>) - Method in class org.apache.spark.rdd.RDD
Return this RDD sorted by the given key function.
sortBy(String, String...) - Method in class org.apache.spark.sql.DataFrameWriter
Sorts the output in each bucket by the given columns.
sortBy(String, Seq<String>) - Method in class org.apache.spark.sql.DataFrameWriter
Sorts the output in each bucket by the given columns.
sortByKey() - Method in class org.apache.spark.api.java.JavaPairRDD
Sort the RDD by key, so that each partition contains a sorted range of the elements in ascending order.
sortByKey(boolean) - Method in class org.apache.spark.api.java.JavaPairRDD
Sort the RDD by key, so that each partition contains a sorted range of the elements.
sortByKey(boolean, int) - Method in class org.apache.spark.api.java.JavaPairRDD
Sort the RDD by key, so that each partition contains a sorted range of the elements.
sortByKey(Comparator<K>) - Method in class org.apache.spark.api.java.JavaPairRDD
Sort the RDD by key, so that each partition contains a sorted range of the elements.
sortByKey(Comparator<K>, boolean) - Method in class org.apache.spark.api.java.JavaPairRDD
Sort the RDD by key, so that each partition contains a sorted range of the elements.
sortByKey(Comparator<K>, boolean, int) - Method in class org.apache.spark.api.java.JavaPairRDD
Sort the RDD by key, so that each partition contains a sorted range of the elements.
sortByKey(boolean, int) - Method in class org.apache.spark.rdd.OrderedRDDFunctions
Sort the RDD by key, so that each partition contains a sorted range of the elements.
sortWithinPartitions(String, String...) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with each partition sorted by the given expressions.
sortWithinPartitions(Column...) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with each partition sorted by the given expressions.
sortWithinPartitions(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with each partition sorted by the given expressions.
sortWithinPartitions(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with each partition sorted by the given expressions.
soundex(Column) - Static method in class org.apache.spark.sql.functions
Returns the soundex code for the specified expression.
Source - Interface in org.apache.spark.metrics.source
 
sourceName() - Static method in class org.apache.spark.metrics.source.CodegenMetrics
 
sourceName() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
 
sourceName() - Method in interface org.apache.spark.metrics.source.Source
 
SourceProgress - Class in org.apache.spark.sql.streaming
Information about progress made for a source in the execution of a StreamingQuery during a trigger.
sources() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
 
sourceSchema(SQLContext, Option<StructType>, String, Map<String, String>) - Method in interface org.apache.spark.sql.sources.StreamSourceProvider
Returns the name and schema of the source that can be used to continually read data.
spark() - Method in class org.apache.spark.status.api.v1.VersionInfo
 
SPARK_CONNECTOR_NAME() - Static method in class org.apache.spark.ui.JettyUtils
 
SPARK_CONTEXT_SHUTDOWN_PRIORITY() - Static method in class org.apache.spark.util.ShutdownHookManager
The shutdown priority of the SparkContext instance.
SPARK_IO_ENCRYPTION_COMMONS_CONFIG_PREFIX() - Static method in class org.apache.spark.security.CryptoStreamUtils
 
SPARK_MASTER - Static variable in class org.apache.spark.launcher.SparkLauncher
The Spark master.
spark_partition_id() - Static method in class org.apache.spark.sql.functions
Partition ID.
SPARK_REGEX() - Static method in class org.apache.spark.SparkMasterRegex
 
SparkAppConfig(Seq<Tuple2<String, String>>, Option<byte[]>, Option<byte[]>) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SparkAppConfig
 
SparkAppConfig$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SparkAppConfig$
 
SparkAppHandle - Interface in org.apache.spark.launcher
A handle to a running Spark application.
SparkAppHandle.Listener - Interface in org.apache.spark.launcher
Listener for updates to a handle's state.
SparkAppHandle.State - Enum in org.apache.spark.launcher
Represents the application's state.
SparkAWSCredentials - Interface in org.apache.spark.streaming.kinesis
Serializable interface providing a method executors can call to obtain an AWSCredentialsProvider instance for authenticating to AWS services.
SparkAWSCredentials.Builder - Class in org.apache.spark.streaming.kinesis
Builder for SparkAWSCredentials instances.
SparkConf - Class in org.apache.spark
Configuration for a Spark application.
SparkConf(boolean) - Constructor for class org.apache.spark.SparkConf
 
SparkConf() - Constructor for class org.apache.spark.SparkConf
Create a SparkConf that loads defaults from system properties and the classpath
sparkContext() - Method in class org.apache.spark.rdd.RDD
The SparkContext that created this RDD.
SparkContext - Class in org.apache.spark
Main entry point for Spark functionality.
SparkContext(SparkConf) - Constructor for class org.apache.spark.SparkContext
 
SparkContext() - Constructor for class org.apache.spark.SparkContext
Create a SparkContext that loads settings from system properties (for instance, when launching with ./bin/spark-submit).
SparkContext(String, String, SparkConf) - Constructor for class org.apache.spark.SparkContext
Alternative constructor that allows setting common Spark properties directly
SparkContext(String, String, String, Seq<String>, Map<String, String>) - Constructor for class org.apache.spark.SparkContext
Alternative constructor that allows setting common Spark properties directly
sparkContext() - Method in class org.apache.spark.sql.SparkSession
 
sparkContext() - Method in class org.apache.spark.sql.SQLContext
 
sparkContext() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
The underlying SparkContext
sparkContext() - Method in class org.apache.spark.streaming.StreamingContext
Return the associated Spark context
SparkEnv - Class in org.apache.spark
:: DeveloperApi :: Holds all the runtime environment objects for a running Spark instance (either master or worker), including the serializer, RpcEnv, block manager, map output tracker, etc.
SparkEnv(String, org.apache.spark.rpc.RpcEnv, Serializer, Serializer, org.apache.spark.serializer.SerializerManager, MapOutputTracker, ShuffleManager, org.apache.spark.broadcast.BroadcastManager, org.apache.spark.storage.BlockManager, SecurityManager, org.apache.spark.metrics.MetricsSystem, MemoryManager, org.apache.spark.scheduler.OutputCommitCoordinator, SparkConf) - Constructor for class org.apache.spark.SparkEnv
 
sparkEventFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
sparkEventToJson(SparkListenerEvent) - Static method in class org.apache.spark.util.JsonProtocol
------------------------------------------------- * JSON serialization methods for SparkListenerEvents |
SparkException - Exception in org.apache.spark
 
SparkException(String, Throwable) - Constructor for exception org.apache.spark.SparkException
 
SparkException(String) - Constructor for exception org.apache.spark.SparkException
 
SparkExecutorInfo - Interface in org.apache.spark
Exposes information about Spark Executors.
SparkExecutorInfoImpl - Class in org.apache.spark
 
SparkExecutorInfoImpl(String, int, long, int, long, long, long, long) - Constructor for class org.apache.spark.SparkExecutorInfoImpl
 
SparkExitCode - Class in org.apache.spark.util
 
SparkExitCode() - Constructor for class org.apache.spark.util.SparkExitCode
 
SparkFiles - Class in org.apache.spark
Resolves paths to files added through SparkContext.addFile().
SparkFiles() - Constructor for class org.apache.spark.SparkFiles
 
SparkFirehoseListener - Class in org.apache.spark
Class that allows users to receive all SparkListener events.
SparkFirehoseListener() - Constructor for class org.apache.spark.SparkFirehoseListener
 
SparkHadoopMapRedUtil - Class in org.apache.spark.mapred
 
SparkHadoopMapRedUtil() - Constructor for class org.apache.spark.mapred.SparkHadoopMapRedUtil
 
SparkHadoopWriter - Class in org.apache.spark.internal.io
A helper object that saves an RDD using a Hadoop OutputFormat.
SparkHadoopWriter() - Constructor for class org.apache.spark.internal.io.SparkHadoopWriter
 
SparkHadoopWriterUtils - Class in org.apache.spark.internal.io
A helper object that provide common utils used during saving an RDD using a Hadoop OutputFormat (both from the old mapred API and the new mapreduce API)
SparkHadoopWriterUtils() - Constructor for class org.apache.spark.internal.io.SparkHadoopWriterUtils
 
sparkJavaOpts(SparkConf, Function1<String, Object>) - Static method in class org.apache.spark.util.Utils
Convert all spark properties set in the given SparkConf to a sequence of java options.
SparkJobInfo - Interface in org.apache.spark
Exposes information about Spark Jobs.
SparkJobInfoImpl - Class in org.apache.spark
 
SparkJobInfoImpl(int, int[], JobExecutionStatus) - Constructor for class org.apache.spark.SparkJobInfoImpl
 
SparkLauncher - Class in org.apache.spark.launcher
Launcher for Spark applications.
SparkLauncher() - Constructor for class org.apache.spark.launcher.SparkLauncher
 
SparkLauncher(Map<String, String>) - Constructor for class org.apache.spark.launcher.SparkLauncher
Creates a launcher that will set the given environment variables in the child.
SparkListener - Class in org.apache.spark.scheduler
:: DeveloperApi :: A default implementation for SparkListenerInterface that has no-op implementations for all callbacks.
SparkListener() - Constructor for class org.apache.spark.scheduler.SparkListener
 
SparkListenerApplicationEnd - Class in org.apache.spark.scheduler
 
SparkListenerApplicationEnd(long) - Constructor for class org.apache.spark.scheduler.SparkListenerApplicationEnd
 
SparkListenerApplicationStart - Class in org.apache.spark.scheduler
 
SparkListenerApplicationStart(String, Option<String>, long, String, Option<String>, Option<Map<String, String>>) - Constructor for class org.apache.spark.scheduler.SparkListenerApplicationStart
 
SparkListenerBlockManagerAdded - Class in org.apache.spark.scheduler
 
SparkListenerBlockManagerAdded(long, BlockManagerId, long, Option<Object>, Option<Object>) - Constructor for class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
 
SparkListenerBlockManagerRemoved - Class in org.apache.spark.scheduler
 
SparkListenerBlockManagerRemoved(long, BlockManagerId) - Constructor for class org.apache.spark.scheduler.SparkListenerBlockManagerRemoved
 
SparkListenerBlockUpdated - Class in org.apache.spark.scheduler
 
SparkListenerBlockUpdated(BlockUpdatedInfo) - Constructor for class org.apache.spark.scheduler.SparkListenerBlockUpdated
 
SparkListenerBus - Interface in org.apache.spark.scheduler
A SparkListenerEvent bus that relays SparkListenerEvents to its listeners
SparkListenerEnvironmentUpdate - Class in org.apache.spark.scheduler
 
SparkListenerEnvironmentUpdate(Map<String, Seq<Tuple2<String, String>>>) - Constructor for class org.apache.spark.scheduler.SparkListenerEnvironmentUpdate
 
SparkListenerEvent - Interface in org.apache.spark.scheduler
 
SparkListenerExecutorAdded - Class in org.apache.spark.scheduler
 
SparkListenerExecutorAdded(long, String, ExecutorInfo) - Constructor for class org.apache.spark.scheduler.SparkListenerExecutorAdded
 
SparkListenerExecutorBlacklisted - Class in org.apache.spark.scheduler
 
SparkListenerExecutorBlacklisted(long, String, int) - Constructor for class org.apache.spark.scheduler.SparkListenerExecutorBlacklisted
 
SparkListenerExecutorBlacklistedForStage - Class in org.apache.spark.scheduler
 
SparkListenerExecutorBlacklistedForStage(long, String, int, int, int) - Constructor for class org.apache.spark.scheduler.SparkListenerExecutorBlacklistedForStage
 
SparkListenerExecutorMetricsUpdate - Class in org.apache.spark.scheduler
Periodic updates from executors.
SparkListenerExecutorMetricsUpdate(String, Seq<Tuple4<Object, Object, Object, Seq<AccumulableInfo>>>) - Constructor for class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
 
SparkListenerExecutorRemoved - Class in org.apache.spark.scheduler
 
SparkListenerExecutorRemoved(long, String, String) - Constructor for class org.apache.spark.scheduler.SparkListenerExecutorRemoved
 
SparkListenerExecutorUnblacklisted - Class in org.apache.spark.scheduler
 
SparkListenerExecutorUnblacklisted(long, String) - Constructor for class org.apache.spark.scheduler.SparkListenerExecutorUnblacklisted
 
SparkListenerInterface - Interface in org.apache.spark.scheduler
Interface for listening to events from the Spark scheduler.
SparkListenerJobEnd - Class in org.apache.spark.scheduler
 
SparkListenerJobEnd(int, long, JobResult) - Constructor for class org.apache.spark.scheduler.SparkListenerJobEnd
 
SparkListenerJobStart - Class in org.apache.spark.scheduler
 
SparkListenerJobStart(int, long, Seq<StageInfo>, Properties) - Constructor for class org.apache.spark.scheduler.SparkListenerJobStart
 
SparkListenerLogStart - Class in org.apache.spark.scheduler
An internal class that describes the metadata of an event log.
SparkListenerLogStart(String) - Constructor for class org.apache.spark.scheduler.SparkListenerLogStart
 
SparkListenerNodeBlacklisted - Class in org.apache.spark.scheduler
 
SparkListenerNodeBlacklisted(long, String, int) - Constructor for class org.apache.spark.scheduler.SparkListenerNodeBlacklisted
 
SparkListenerNodeBlacklistedForStage - Class in org.apache.spark.scheduler
 
SparkListenerNodeBlacklistedForStage(long, String, int, int, int) - Constructor for class org.apache.spark.scheduler.SparkListenerNodeBlacklistedForStage
 
SparkListenerNodeUnblacklisted - Class in org.apache.spark.scheduler
 
SparkListenerNodeUnblacklisted(long, String) - Constructor for class org.apache.spark.scheduler.SparkListenerNodeUnblacklisted
 
SparkListenerSpeculativeTaskSubmitted - Class in org.apache.spark.scheduler
 
SparkListenerSpeculativeTaskSubmitted(int) - Constructor for class org.apache.spark.scheduler.SparkListenerSpeculativeTaskSubmitted
 
SparkListenerStageCompleted - Class in org.apache.spark.scheduler
 
SparkListenerStageCompleted(StageInfo) - Constructor for class org.apache.spark.scheduler.SparkListenerStageCompleted
 
SparkListenerStageSubmitted - Class in org.apache.spark.scheduler
 
SparkListenerStageSubmitted(StageInfo, Properties) - Constructor for class org.apache.spark.scheduler.SparkListenerStageSubmitted
 
SparkListenerTaskEnd - Class in org.apache.spark.scheduler
 
SparkListenerTaskEnd(int, int, String, TaskEndReason, TaskInfo, TaskMetrics) - Constructor for class org.apache.spark.scheduler.SparkListenerTaskEnd
 
SparkListenerTaskGettingResult - Class in org.apache.spark.scheduler
 
SparkListenerTaskGettingResult(TaskInfo) - Constructor for class org.apache.spark.scheduler.SparkListenerTaskGettingResult
 
SparkListenerTaskStart - Class in org.apache.spark.scheduler
 
SparkListenerTaskStart(int, int, TaskInfo) - Constructor for class org.apache.spark.scheduler.SparkListenerTaskStart
 
SparkListenerUnpersistRDD - Class in org.apache.spark.scheduler
 
SparkListenerUnpersistRDD(int) - Constructor for class org.apache.spark.scheduler.SparkListenerUnpersistRDD
 
SparkMasterRegex - Class in org.apache.spark
A collection of regexes for extracting information from the master string.
SparkMasterRegex() - Constructor for class org.apache.spark.SparkMasterRegex
 
sparkProperties() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SparkAppConfig
 
sparkProperties() - Method in class org.apache.spark.status.api.v1.ApplicationEnvironmentInfo
 
SparkRDefaults - Class in org.apache.spark.api.r
 
SparkRDefaults() - Constructor for class org.apache.spark.api.r.SparkRDefaults
 
sparkRPackagePath(boolean) - Static method in class org.apache.spark.api.r.RUtils
Get the list of paths for R packages in various deployment modes, of which the first path is for the SparkR package itself.
sparkSession() - Method in interface org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
 
sparkSession() - Method in interface org.apache.spark.ml.util.BaseReadWrite
Returns the user-specified Spark Session or the default.
sparkSession() - Method in class org.apache.spark.sql.Dataset
 
sparkSession() - Method in interface org.apache.spark.sql.hive.HiveStrategies
 
SparkSession - Class in org.apache.spark.sql
The entry point to programming Spark with the Dataset and DataFrame API.
sparkSession() - Method in class org.apache.spark.sql.SQLContext
 
sparkSession() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Returns the SparkSession associated with this.
SparkSession.Builder - Class in org.apache.spark.sql
Builder for SparkSession.
SparkSession.implicits$ - Class in org.apache.spark.sql
:: Experimental :: (Scala-specific) Implicit methods available in Scala for converting common Scala objects into DataFrames.
SparkSessionExtensions - Class in org.apache.spark.sql
:: Experimental :: Holder for injection points to the SparkSession.
SparkSessionExtensions() - Constructor for class org.apache.spark.sql.SparkSessionExtensions
 
SparkShutdownHook - Class in org.apache.spark.util
 
SparkShutdownHook(int, Function0<BoxedUnit>) - Constructor for class org.apache.spark.util.SparkShutdownHook
 
SparkStageInfo - Interface in org.apache.spark
Exposes information about Spark Stages.
SparkStageInfoImpl - Class in org.apache.spark
 
SparkStageInfoImpl(int, int, long, String, int, int, int, int) - Constructor for class org.apache.spark.SparkStageInfoImpl
 
SparkStatusTracker - Class in org.apache.spark
Low-level status reporting APIs for monitoring job and stage progress.
sparkUser() - Method in class org.apache.spark.api.java.JavaSparkContext
 
sparkUser() - Method in class org.apache.spark.scheduler.SparkListenerApplicationStart
 
sparkUser() - Method in class org.apache.spark.SparkContext
 
sparkUser() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
 
SparkUserDefinedFunction - Class in org.apache.spark.sql.expressions
 
SparkUserDefinedFunction() - Constructor for class org.apache.spark.sql.expressions.SparkUserDefinedFunction
 
sparkVersion() - Method in class org.apache.spark.scheduler.SparkListenerLogStart
 
sparse(int, int, int[], int[], double[]) - Static method in class org.apache.spark.ml.linalg.Matrices
Creates a column-major sparse matrix in Compressed Sparse Column (CSC) format.
sparse(int, int[], double[]) - Static method in class org.apache.spark.ml.linalg.Vectors
Creates a sparse vector providing its index array and value array.
sparse(int, Seq<Tuple2<Object, Object>>) - Static method in class org.apache.spark.ml.linalg.Vectors
Creates a sparse vector using unordered (index, value) pairs.
sparse(int, Iterable<Tuple2<Integer, Double>>) - Static method in class org.apache.spark.ml.linalg.Vectors
Creates a sparse vector using unordered (index, value) pairs in a Java friendly way.
sparse(int, int, int[], int[], double[]) - Static method in class org.apache.spark.mllib.linalg.Matrices
Creates a column-major sparse matrix in Compressed Sparse Column (CSC) format.
sparse(int, int[], double[]) - Static method in class org.apache.spark.mllib.linalg.Vectors
Creates a sparse vector providing its index array and value array.
sparse(int, Seq<Tuple2<Object, Object>>) - Static method in class org.apache.spark.mllib.linalg.Vectors
Creates a sparse vector using unordered (index, value) pairs.
sparse(int, Iterable<Tuple2<Integer, Double>>) - Static method in class org.apache.spark.mllib.linalg.Vectors
Creates a sparse vector using unordered (index, value) pairs in a Java friendly way.
SparseMatrix - Class in org.apache.spark.ml.linalg
Column-major sparse matrix.
SparseMatrix(int, int, int[], int[], double[], boolean) - Constructor for class org.apache.spark.ml.linalg.SparseMatrix
 
SparseMatrix(int, int, int[], int[], double[]) - Constructor for class org.apache.spark.ml.linalg.SparseMatrix
Column-major sparse matrix.
SparseMatrix - Class in org.apache.spark.mllib.linalg
Column-major sparse matrix.
SparseMatrix(int, int, int[], int[], double[], boolean) - Constructor for class org.apache.spark.mllib.linalg.SparseMatrix
 
SparseMatrix(int, int, int[], int[], double[]) - Constructor for class org.apache.spark.mllib.linalg.SparseMatrix
Column-major sparse matrix.
SparseVector - Class in org.apache.spark.ml.linalg
A sparse vector represented by an index array and a value array.
SparseVector(int, int[], double[]) - Constructor for class org.apache.spark.ml.linalg.SparseVector
 
SparseVector - Class in org.apache.spark.mllib.linalg
A sparse vector represented by an index array and a value array.
SparseVector(int, int[], double[]) - Constructor for class org.apache.spark.mllib.linalg.SparseVector
 
SPARSITY() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
 
sparsity() - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
spdiag(Vector) - Static method in class org.apache.spark.ml.linalg.SparseMatrix
Generate a diagonal matrix in SparseMatrix format from the supplied values.
spdiag(Vector) - Static method in class org.apache.spark.mllib.linalg.SparseMatrix
Generate a diagonal matrix in SparseMatrix format from the supplied values.
SpearmanCorrelation - Class in org.apache.spark.mllib.stat.correlation
Compute Spearman's correlation for two RDDs of the type RDD[Double] or the correlation matrix for an RDD of the type RDD[Vector].
SpearmanCorrelation() - Constructor for class org.apache.spark.mllib.stat.correlation.SpearmanCorrelation
 
SpecialLengths - Class in org.apache.spark.api.r
 
SpecialLengths() - Constructor for class org.apache.spark.api.r.SpecialLengths
 
speculative() - Method in class org.apache.spark.scheduler.TaskInfo
 
speculative() - Method in class org.apache.spark.status.api.v1.TaskData
 
speye(int) - Static method in class org.apache.spark.ml.linalg.Matrices
Generate a sparse Identity Matrix in Matrix format.
speye(int) - Static method in class org.apache.spark.ml.linalg.SparseMatrix
Generate an Identity Matrix in SparseMatrix format.
speye(int) - Static method in class org.apache.spark.mllib.linalg.Matrices
Generate a sparse Identity Matrix in Matrix format.
speye(int) - Static method in class org.apache.spark.mllib.linalg.SparseMatrix
Generate an Identity Matrix in SparseMatrix format.
SpillListener - Class in org.apache.spark
A SparkListener that detects whether spills have occurred in Spark jobs.
SpillListener() - Constructor for class org.apache.spark.SpillListener
 
split() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
 
split() - Method in class org.apache.spark.ml.tree.InternalNode
 
Split - Interface in org.apache.spark.ml.tree
Interface for a "Split," which specifies a test made at a decision tree node to choose the left or right path.
split() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
 
split() - Method in class org.apache.spark.mllib.tree.model.Node
 
Split - Class in org.apache.spark.mllib.tree.model
:: DeveloperApi :: Split applied to a feature param: feature feature index param: threshold Threshold for continuous feature.
Split(int, double, Enumeration.Value, List<Object>) - Constructor for class org.apache.spark.mllib.tree.model.Split
 
split(Column, String) - Static method in class org.apache.spark.sql.functions
Splits str around pattern (pattern is a regular expression).
splitAndCountPartitions(Iterator<String>) - Static method in class org.apache.spark.streaming.util.RawTextHelper
Splits lines and counts the words.
splitCommandString(String) - Static method in class org.apache.spark.util.Utils
Split a string of potentially quoted arguments from the command line the way that a shell would do it to determine arguments to a command.
SplitData(int, double[], int) - Constructor for class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData
 
SplitData(int, double, int, Seq<Object>) - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData
 
SplitData$() - Constructor for class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData$
 
SplitData$() - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData$
 
splitIndex() - Method in class org.apache.spark.storage.RDDBlockId
 
SplitInfo - Class in org.apache.spark.scheduler
 
SplitInfo(Class<?>, String, String, long, Object) - Constructor for class org.apache.spark.scheduler.SplitInfo
 
splits() - Method in class org.apache.spark.ml.feature.Bucketizer
Parameter for mapping continuous features into buckets.
splitsArray() - Method in class org.apache.spark.ml.feature.Bucketizer
Parameter for specifying multiple splits parameters.
spr(double, Vector, DenseVector) - Static method in class org.apache.spark.ml.linalg.BLAS
Adds alpha * x * x.t to a matrix in-place.
spr(double, Vector, double[]) - Static method in class org.apache.spark.ml.linalg.BLAS
Adds alpha * x * x.t to a matrix in-place.
spr(double, Vector, DenseVector) - Static method in class org.apache.spark.mllib.linalg.BLAS
Adds alpha * v * v.t to a matrix in-place.
spr(double, Vector, double[]) - Static method in class org.apache.spark.mllib.linalg.BLAS
Adds alpha * v * v.t to a matrix in-place.
sprand(int, int, double, Random) - Static method in class org.apache.spark.ml.linalg.Matrices
Generate a SparseMatrix consisting of i.i.d. gaussian random numbers.
sprand(int, int, double, Random) - Static method in class org.apache.spark.ml.linalg.SparseMatrix
Generate a SparseMatrix consisting of i.i.d.
sprand(int, int, double, Random) - Static method in class org.apache.spark.mllib.linalg.Matrices
Generate a SparseMatrix consisting of i.i.d. gaussian random numbers.
sprand(int, int, double, Random) - Static method in class org.apache.spark.mllib.linalg.SparseMatrix
Generate a SparseMatrix consisting of i.i.d.
sprandn(int, int, double, Random) - Static method in class org.apache.spark.ml.linalg.Matrices
Generate a SparseMatrix consisting of i.i.d. gaussian random numbers.
sprandn(int, int, double, Random) - Static method in class org.apache.spark.ml.linalg.SparseMatrix
Generate a SparseMatrix consisting of i.i.d.
sprandn(int, int, double, Random) - Static method in class org.apache.spark.mllib.linalg.Matrices
Generate a SparseMatrix consisting of i.i.d. gaussian random numbers.
sprandn(int, int, double, Random) - Static method in class org.apache.spark.mllib.linalg.SparseMatrix
Generate a SparseMatrix consisting of i.i.d.
sqdist(Vector, Vector) - Static method in class org.apache.spark.ml.linalg.Vectors
Returns the squared distance between two Vectors.
sqdist(Vector, Vector) - Static method in class org.apache.spark.mllib.linalg.Vectors
Returns the squared distance between two Vectors.
sql(String) - Method in class org.apache.spark.sql.SparkSession
Executes a SQL query using Spark, returning the result as a DataFrame.
sql(String) - Method in class org.apache.spark.sql.SQLContext
 
sql() - Method in class org.apache.spark.sql.types.ArrayType
 
sql() - Static method in class org.apache.spark.sql.types.BinaryType
 
sql() - Static method in class org.apache.spark.sql.types.BooleanType
 
sql() - Static method in class org.apache.spark.sql.types.ByteType
 
sql() - Static method in class org.apache.spark.sql.types.CalendarIntervalType
 
sql() - Method in class org.apache.spark.sql.types.DataType
 
sql() - Static method in class org.apache.spark.sql.types.DateType
 
sql() - Method in class org.apache.spark.sql.types.DecimalType
 
sql() - Static method in class org.apache.spark.sql.types.DoubleType
 
sql() - Static method in class org.apache.spark.sql.types.FloatType
 
sql() - Static method in class org.apache.spark.sql.types.IntegerType
 
sql() - Static method in class org.apache.spark.sql.types.LongType
 
sql() - Method in class org.apache.spark.sql.types.MapType
 
sql() - Static method in class org.apache.spark.sql.types.NullType
 
sql() - Static method in class org.apache.spark.sql.types.ShortType
 
sql() - Static method in class org.apache.spark.sql.types.StringType
 
sql() - Method in class org.apache.spark.sql.types.StructType
 
sql() - Static method in class org.apache.spark.sql.types.TimestampType
 
sqlContext() - Method in interface org.apache.spark.ml.util.BaseReadWrite
Returns the user-specified SQL context or the default.
sqlContext() - Method in class org.apache.spark.sql.Dataset
 
sqlContext() - Method in class org.apache.spark.sql.sources.BaseRelation
 
sqlContext() - Method in class org.apache.spark.sql.SparkSession
A wrapped version of this session in the form of a SQLContext, for backward compatibility.
SQLContext - Class in org.apache.spark.sql
The entry point for working with structured data (rows and columns) in Spark 1.x.
SQLContext(SparkContext) - Constructor for class org.apache.spark.sql.SQLContext
Deprecated.
Use SparkSession.builder instead. Since 2.0.0.
SQLContext(JavaSparkContext) - Constructor for class org.apache.spark.sql.SQLContext
Deprecated.
Use SparkSession.builder instead. Since 2.0.0.
SQLContext.implicits$ - Class in org.apache.spark.sql
:: Experimental :: (Scala-specific) Implicit methods available in Scala for converting common Scala objects into DataFrames.
SQLDataTypes - Class in org.apache.spark.ml.linalg
:: DeveloperApi :: SQL data types for vectors and matrices.
SQLDataTypes() - Constructor for class org.apache.spark.ml.linalg.SQLDataTypes
 
SQLImplicits - Class in org.apache.spark.sql
A collection of implicit methods for converting common Scala objects into Datasets.
SQLImplicits() - Constructor for class org.apache.spark.sql.SQLImplicits
 
SQLImplicits.StringToColumn - Class in org.apache.spark.sql
Converts $"col name" into a Column.
SQLTransformer - Class in org.apache.spark.ml.feature
Implements the transformations which are defined by SQL statement.
SQLTransformer(String) - Constructor for class org.apache.spark.ml.feature.SQLTransformer
 
SQLTransformer() - Constructor for class org.apache.spark.ml.feature.SQLTransformer
 
sqlType() - Method in class org.apache.spark.mllib.linalg.VectorUDT
 
SQLUserDefinedType - Annotation Type in org.apache.spark.sql.types
::DeveloperApi:: A user-defined type which can be automatically recognized by a SQLContext and registered.
SQLUtils - Class in org.apache.spark.sql.api.r
 
SQLUtils() - Constructor for class org.apache.spark.sql.api.r.SQLUtils
 
sqrt(Column) - Static method in class org.apache.spark.sql.functions
Computes the square root of the specified float value.
sqrt(String) - Static method in class org.apache.spark.sql.functions
Computes the square root of the specified float value.
Sqrt$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Sqrt$
 
SquaredError - Class in org.apache.spark.mllib.tree.loss
:: DeveloperApi :: Class for squared error loss calculation.
SquaredError() - Constructor for class org.apache.spark.mllib.tree.loss.SquaredError
 
SquaredEuclideanSilhouette - Class in org.apache.spark.ml.evaluation
SquaredEuclideanSilhouette computes the average of the Silhouette over all the data of the dataset, which is a measure of how appropriately the data have been clustered.
SquaredEuclideanSilhouette() - Constructor for class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette
 
SquaredEuclideanSilhouette.ClusterStats - Class in org.apache.spark.ml.evaluation
 
SquaredEuclideanSilhouette.ClusterStats$ - Class in org.apache.spark.ml.evaluation
 
SquaredL2Updater - Class in org.apache.spark.mllib.optimization
:: DeveloperApi :: Updater for L2 regularized problems.
SquaredL2Updater() - Constructor for class org.apache.spark.mllib.optimization.SquaredL2Updater
 
squaredNormSum() - Method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette.ClusterStats
 
Src - Static variable in class org.apache.spark.graphx.TripletFields
Expose the source and edge fields but not the destination field.
srcAttr() - Method in class org.apache.spark.graphx.EdgeContext
The vertex attribute of the edge's source vertex.
srcAttr() - Method in class org.apache.spark.graphx.EdgeTriplet
The source vertex attribute
srcAttr() - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
 
srcCol() - Method in interface org.apache.spark.ml.clustering.PowerIterationClusteringParams
Param for the name of the input column for source vertex IDs.
srcId() - Method in class org.apache.spark.graphx.Edge
 
srcId() - Method in class org.apache.spark.graphx.EdgeContext
The vertex id of the edge's source vertex.
srcId() - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
 
srdd() - Method in class org.apache.spark.api.java.JavaDoubleRDD
 
ssc() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
 
stackTrace() - Method in class org.apache.spark.ExceptionFailure
 
StackTrace - Class in org.apache.spark.status.api.v1
 
StackTrace(Seq<String>) - Constructor for class org.apache.spark.status.api.v1.StackTrace
 
stackTrace() - Method in class org.apache.spark.status.api.v1.ThreadStackTrace
 
stackTraceFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
stackTraceToJson(StackTraceElement[]) - Static method in class org.apache.spark.util.JsonProtocol
 
stage() - Method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
 
STAGE() - Static method in class org.apache.spark.status.TaskIndexNames
 
STAGE_DAG() - Static method in class org.apache.spark.ui.ToolTips
 
STAGE_TIMELINE() - Static method in class org.apache.spark.ui.ToolTips
 
stageAttempt() - Method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
 
stageAttemptId() - Method in class org.apache.spark.ContextBarrierId
 
stageAttemptId() - Method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklistedForStage
 
stageAttemptId() - Method in class org.apache.spark.scheduler.SparkListenerNodeBlacklistedForStage
 
stageAttemptId() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
 
stageAttemptId() - Method in class org.apache.spark.scheduler.SparkListenerTaskStart
 
stageAttemptNumber() - Method in class org.apache.spark.BarrierTaskContext
 
stageAttemptNumber() - Method in class org.apache.spark.TaskContext
How many times the stage that this task belongs to has been attempted.
stageCompletedFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
stageCompletedToJson(SparkListenerStageCompleted) - Static method in class org.apache.spark.util.JsonProtocol
 
StageData - Class in org.apache.spark.status.api.v1
 
stageFailed(String) - Method in class org.apache.spark.scheduler.StageInfo
 
stageId() - Method in class org.apache.spark.BarrierTaskContext
 
stageId() - Method in class org.apache.spark.ContextBarrierId
 
stageId() - Method in interface org.apache.spark.scheduler.Schedulable
 
stageId() - Method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklistedForStage
 
stageId() - Method in class org.apache.spark.scheduler.SparkListenerNodeBlacklistedForStage
 
stageId() - Method in class org.apache.spark.scheduler.SparkListenerSpeculativeTaskSubmitted
 
stageId() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
 
stageId() - Method in class org.apache.spark.scheduler.SparkListenerTaskStart
 
stageId() - Method in class org.apache.spark.scheduler.StageInfo
 
stageId() - Method in interface org.apache.spark.SparkStageInfo
 
stageId() - Method in class org.apache.spark.SparkStageInfoImpl
 
stageId() - Method in class org.apache.spark.status.api.v1.StageData
 
stageId() - Method in class org.apache.spark.TaskContext
The ID of the stage that this task belong to.
stageIds() - Method in class org.apache.spark.scheduler.SparkListenerJobStart
 
stageIds() - Method in interface org.apache.spark.SparkJobInfo
 
stageIds() - Method in class org.apache.spark.SparkJobInfoImpl
 
stageIds() - Method in class org.apache.spark.status.api.v1.JobData
 
stageIds() - Method in class org.apache.spark.status.LiveJob
 
stageIds() - Method in class org.apache.spark.status.SchedulerPool
 
stageInfo() - Method in class org.apache.spark.scheduler.SparkListenerStageCompleted
 
stageInfo() - Method in class org.apache.spark.scheduler.SparkListenerStageSubmitted
 
StageInfo - Class in org.apache.spark.scheduler
:: DeveloperApi :: Stores information about a stage to pass from the scheduler to SparkListeners.
StageInfo(int, int, String, int, Seq<RDDInfo>, Seq<Object>, String, TaskMetrics, Seq<Seq<TaskLocation>>) - Constructor for class org.apache.spark.scheduler.StageInfo
 
stageInfoFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
--------------------------------------------------------------------- * JSON deserialization methods for classes SparkListenerEvents depend on |
stageInfos() - Method in class org.apache.spark.scheduler.SparkListenerJobStart
 
stageInfoToJson(StageInfo) - Static method in class org.apache.spark.util.JsonProtocol
------------------------------------------------------------------- * JSON serialization methods for classes SparkListenerEvents depend on |
stageName() - Method in class org.apache.spark.ml.clustering.InternalKMeansModelWriter
 
stageName() - Method in class org.apache.spark.ml.clustering.PMMLKMeansModelWriter
 
stageName() - Method in class org.apache.spark.ml.regression.InternalLinearRegressionModelWriter
 
stageName() - Method in class org.apache.spark.ml.regression.PMMLLinearRegressionModelWriter
 
stageName() - Method in interface org.apache.spark.ml.util.MLFormatRegister
The string that represents the stage type that this writer supports.
stages() - Method in class org.apache.spark.ml.Pipeline
param for pipeline stages
stages() - Method in class org.apache.spark.ml.PipelineModel
 
StageStatus - Enum in org.apache.spark.status.api.v1
 
stageSubmittedFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
stageSubmittedToJson(SparkListenerStageSubmitted) - Static method in class org.apache.spark.util.JsonProtocol
 
standardization() - Method in interface org.apache.spark.ml.param.shared.HasStandardization
Param for whether to standardize the training features before fitting the model.
StandardNormalGenerator - Class in org.apache.spark.mllib.random
:: DeveloperApi :: Generates i.i.d.
StandardNormalGenerator() - Constructor for class org.apache.spark.mllib.random.StandardNormalGenerator
 
StandardScaler - Class in org.apache.spark.ml.feature
Standardizes features by removing the mean and scaling to unit variance using column summary statistics on the samples in the training set.
StandardScaler(String) - Constructor for class org.apache.spark.ml.feature.StandardScaler
 
StandardScaler() - Constructor for class org.apache.spark.ml.feature.StandardScaler
 
StandardScaler - Class in org.apache.spark.mllib.feature
Standardizes features by removing the mean and scaling to unit std using column summary statistics on the samples in the training set.
StandardScaler(boolean, boolean) - Constructor for class org.apache.spark.mllib.feature.StandardScaler
 
StandardScaler() - Constructor for class org.apache.spark.mllib.feature.StandardScaler
 
StandardScalerModel - Class in org.apache.spark.ml.feature
Model fitted by StandardScaler.
StandardScalerModel - Class in org.apache.spark.mllib.feature
Represents a StandardScaler model that can transform vectors.
StandardScalerModel(Vector, Vector, boolean, boolean) - Constructor for class org.apache.spark.mllib.feature.StandardScalerModel
 
StandardScalerModel(Vector, Vector) - Constructor for class org.apache.spark.mllib.feature.StandardScalerModel
 
StandardScalerModel(Vector) - Constructor for class org.apache.spark.mllib.feature.StandardScalerModel
 
StandardScalerParams - Interface in org.apache.spark.ml.feature
starGraph(SparkContext, int) - Static method in class org.apache.spark.graphx.util.GraphGenerators
Create a star graph with vertex 0 being the center.
start() - Method in interface org.apache.spark.metrics.sink.Sink
 
start() - Method in interface org.apache.spark.scheduler.SchedulerBackend
 
start() - Method in interface org.apache.spark.scheduler.TaskScheduler
 
start(String) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Starts the execution of the streaming query, which will continually output results to the given path as new data arrives.
start() - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Starts the execution of the streaming query, which will continually output results to the given path as new data arrives.
start() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Start the execution of the streams.
start() - Method in class org.apache.spark.streaming.dstream.ConstantInputDStream
 
start() - Method in class org.apache.spark.streaming.dstream.InputDStream
Method called to start receiving data.
start() - Method in class org.apache.spark.streaming.dstream.ReceiverInputDStream
 
start() - Method in class org.apache.spark.streaming.StreamingContext
Start the execution of the streams.
startApplication(SparkAppHandle.Listener...) - Method in class org.apache.spark.launcher.AbstractLauncher
Starts a Spark application.
startApplication(SparkAppHandle.Listener...) - Method in class org.apache.spark.launcher.InProcessLauncher
Starts a Spark application.
startApplication(SparkAppHandle.Listener...) - Method in class org.apache.spark.launcher.SparkLauncher
Starts a Spark application.
startIndexInLevel(int) - Static method in class org.apache.spark.mllib.tree.model.Node
Return the index of the first node in the given level.
startJettyServer(String, int, org.apache.spark.SSLOptions, Seq<ServletContextHandler>, SparkConf, String) - Static method in class org.apache.spark.ui.JettyUtils
Attempt to start a Jetty server bound to the supplied hostName:port using the given context handlers.
startOffset() - Method in class org.apache.spark.sql.streaming.SourceProgress
 
startOffset() - Method in exception org.apache.spark.sql.streaming.StreamingQueryException
 
startPosition() - Method in exception org.apache.spark.sql.AnalysisException
 
startServiceOnPort(int, Function1<Object, Tuple2<T, Object>>, SparkConf, String) - Static method in class org.apache.spark.util.Utils
Attempt to start a service on the given port, or fail after a number of attempts.
startsWith(Column) - Method in class org.apache.spark.sql.Column
String starts with.
startsWith(String) - Method in class org.apache.spark.sql.Column
String starts with another string literal.
startTime() - Method in class org.apache.spark.api.java.JavaSparkContext
 
startTime() - Method in class org.apache.spark.SparkContext
 
startTime() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
 
startTime() - Method in class org.apache.spark.status.api.v1.streaming.OutputOperationInfo
 
startTime() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
 
startTime() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
 
stat() - Method in class org.apache.spark.sql.Dataset
Returns a DataFrameStatFunctions for working statistic functions support.
StatCounter - Class in org.apache.spark.util
A class for tracking the statistics of a set of numbers (count, mean and variance) in a numerically robust way.
StatCounter(TraversableOnce<Object>) - Constructor for class org.apache.spark.util.StatCounter
 
StatCounter() - Constructor for class org.apache.spark.util.StatCounter
Initialize the StatCounter with no values.
state() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate
 
state() - Method in class org.apache.spark.scheduler.local.StatusUpdate
 
State<S> - Class in org.apache.spark.streaming
:: Experimental :: Abstract class for getting and updating the state in mapping function used in the mapWithState operation of a pair DStream (Scala) or a JavaPairDStream (Java).
State() - Constructor for class org.apache.spark.streaming.State
 
stateChanged(SparkAppHandle) - Method in interface org.apache.spark.launcher.SparkAppHandle.Listener
Callback for changes in the handle's state.
statement() - Method in class org.apache.spark.ml.feature.SQLTransformer
SQL statement parameter.
StateOperatorProgress - Class in org.apache.spark.sql.streaming
Information about updates made to stateful operators in a StreamingQuery during a trigger.
stateOperators() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
 
stateSnapshots() - Method in class org.apache.spark.streaming.api.java.JavaMapWithStateDStream
 
stateSnapshots() - Method in class org.apache.spark.streaming.dstream.MapWithStateDStream
Return a pair DStream where each RDD is the snapshot of the state of all the keys.
StateSpec<KeyType,ValueType,StateType,MappedType> - Class in org.apache.spark.streaming
:: Experimental :: Abstract class representing all the specifications of the DStream transformation mapWithState operation of a pair DStream (Scala) or a JavaPairDStream (Java).
StateSpec() - Constructor for class org.apache.spark.streaming.StateSpec
 
staticPageRank(int, double) - Method in class org.apache.spark.graphx.GraphOps
Run PageRank for a fixed number of iterations returning a graph with vertex attributes containing the PageRank and edge attributes the normalized edge weight.
staticParallelPersonalizedPageRank(long[], int, double) - Method in class org.apache.spark.graphx.GraphOps
Run parallel personalized PageRank for a given array of source vertices, such that all random walks are started relative to the source vertices
staticPersonalizedPageRank(long, int, double) - Method in class org.apache.spark.graphx.GraphOps
Run Personalized PageRank for a fixed number of iterations with with all iterations originating at the source node returning a graph with vertex attributes containing the PageRank and edge attributes the normalized edge weight.
StaticSources - Class in org.apache.spark.metrics.source
 
StaticSources() - Constructor for class org.apache.spark.metrics.source.StaticSources
 
statistic() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
 
statistic() - Method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTestResult
 
statistic() - Method in interface org.apache.spark.mllib.stat.test.TestResult
Test statistic.
Statistics - Class in org.apache.spark.mllib.stat
API for statistical functions in MLlib.
Statistics() - Constructor for class org.apache.spark.mllib.stat.Statistics
 
Statistics - Interface in org.apache.spark.sql.sources.v2.reader
An interface to represent statistics for a data source, which is returned by SupportsReportStatistics.estimateStatistics().
stats() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return a StatCounter object that captures the mean, variance and count of the RDD's elements in one operation.
stats() - Method in class org.apache.spark.mllib.tree.model.Node
 
stats() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
Return a StatCounter object that captures the mean, variance and count of the RDD's elements in one operation.
StatsdMetricType - Class in org.apache.spark.metrics.sink
 
StatsdMetricType() - Constructor for class org.apache.spark.metrics.sink.StatsdMetricType
 
StatsReportListener - Class in org.apache.spark.scheduler
:: DeveloperApi :: Simple SparkListener that logs a few summary statistics when each stage completes.
StatsReportListener() - Constructor for class org.apache.spark.scheduler.StatsReportListener
 
StatsReportListener - Class in org.apache.spark.streaming.scheduler
:: DeveloperApi :: A simple StreamingListener that logs summary statistics across Spark Streaming batches param: numBatchInfos Number of last batches to consider for generating statistics (default: 10)
StatsReportListener(int) - Constructor for class org.apache.spark.streaming.scheduler.StatsReportListener
 
status() - Method in class org.apache.spark.scheduler.TaskInfo
 
status() - Method in interface org.apache.spark.SparkJobInfo
 
status() - Method in class org.apache.spark.SparkJobInfoImpl
 
status() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Returns the current status of the query.
status() - Method in class org.apache.spark.status.api.v1.JobData
 
status() - Method in class org.apache.spark.status.api.v1.StageData
 
status() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
 
status() - Method in class org.apache.spark.status.api.v1.TaskData
 
status() - Method in class org.apache.spark.status.LiveJob
 
status() - Method in class org.apache.spark.status.LiveStage
 
STATUS() - Static method in class org.apache.spark.status.TaskIndexNames
 
status() - Method in class org.apache.spark.storage.BlockManagerMessages.BlockLocationsAndStatus
 
statusTracker() - Method in class org.apache.spark.api.java.JavaSparkContext
 
statusTracker() - Method in class org.apache.spark.SparkContext
 
StatusUpdate(String, long, Enumeration.Value, org.apache.spark.util.SerializableBuffer) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate
 
StatusUpdate - Class in org.apache.spark.scheduler.local
 
StatusUpdate(long, Enumeration.Value, ByteBuffer) - Constructor for class org.apache.spark.scheduler.local.StatusUpdate
 
StatusUpdate$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate$
 
STD() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
 
std() - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
std() - Method in class org.apache.spark.ml.feature.StandardScalerModel
 
std() - Method in class org.apache.spark.mllib.feature.StandardScalerModel
 
std() - Method in class org.apache.spark.mllib.random.LogNormalGenerator
 
stddev(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: alias for stddev_samp.
stddev(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: alias for stddev_samp.
stddev_pop(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the population standard deviation of the expression in a group.
stddev_pop(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the population standard deviation of the expression in a group.
stddev_samp(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the sample standard deviation of the expression in a group.
stddev_samp(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the sample standard deviation of the expression in a group.
stdev() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Compute the population standard deviation of this RDD's elements.
stdev() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
Compute the population standard deviation of this RDD's elements.
stdev() - Method in class org.apache.spark.util.StatCounter
Return the population standard deviation of the values.
stepSize() - Method in interface org.apache.spark.ml.param.shared.HasStepSize
Param for Step size to be used for each iteration of optimization (&gt; 0).
stepSize() - Method in interface org.apache.spark.ml.tree.GBTParams
Param for Step size (a.k.a.
stop() - Method in class org.apache.spark.api.java.JavaSparkContext
Shut down the SparkContext.
stop() - Method in interface org.apache.spark.broadcast.BroadcastFactory
 
stop() - Method in interface org.apache.spark.launcher.SparkAppHandle
Asks the application to stop.
stop() - Method in interface org.apache.spark.metrics.sink.Sink
 
stop() - Method in interface org.apache.spark.rpc.RpcEndpoint
A convenient method to stop RpcEndpoint.
stop() - Method in interface org.apache.spark.scheduler.SchedulerBackend
 
stop() - Method in interface org.apache.spark.scheduler.TaskScheduler
 
stop() - Method in class org.apache.spark.SparkContext
Shut down the SparkContext.
stop() - Method in class org.apache.spark.sql.SparkSession
Stop the underlying SparkContext.
stop() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
Stops the execution of this query if it is running.
stop() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Stop the execution of the streams.
stop(boolean) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Stop the execution of the streams.
stop(boolean, boolean) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Stop the execution of the streams.
stop() - Method in class org.apache.spark.streaming.dstream.ConstantInputDStream
 
stop() - Method in class org.apache.spark.streaming.dstream.InputDStream
Method called to stop receiving data.
stop() - Method in class org.apache.spark.streaming.dstream.ReceiverInputDStream
 
stop(String) - Method in class org.apache.spark.streaming.receiver.Receiver
Stop the receiver completely.
stop(String, Throwable) - Method in class org.apache.spark.streaming.receiver.Receiver
Stop the receiver completely due to an exception
stop(boolean) - Method in class org.apache.spark.streaming.StreamingContext
Stop the execution of the streams immediately (does not wait for all received data to be processed).
stop(boolean, boolean) - Method in class org.apache.spark.streaming.StreamingContext
Stop the execution of the streams, with option of ensuring all received data has been processed.
StopAllReceivers - Class in org.apache.spark.streaming.scheduler
This message will trigger ReceiverTrackerEndpoint to send stop signals to all registered receivers.
StopAllReceivers() - Constructor for class org.apache.spark.streaming.scheduler.StopAllReceivers
 
StopBlockManagerMaster$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.StopBlockManagerMaster$
 
StopCoordinator - Class in org.apache.spark.scheduler
 
StopCoordinator() - Constructor for class org.apache.spark.scheduler.StopCoordinator
 
StopDriver$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopDriver$
 
StopExecutor - Class in org.apache.spark.scheduler.local
 
StopExecutor() - Constructor for class org.apache.spark.scheduler.local.StopExecutor
 
StopExecutor$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopExecutor$
 
StopExecutors$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopExecutors$
 
StopMapOutputTracker - Class in org.apache.spark
 
StopMapOutputTracker() - Constructor for class org.apache.spark.StopMapOutputTracker
 
StopReceiver - Class in org.apache.spark.streaming.receiver
 
StopReceiver() - Constructor for class org.apache.spark.streaming.receiver.StopReceiver
 
stopWords() - Method in class org.apache.spark.ml.feature.StopWordsRemover
The words to be filtered out.
StopWordsRemover - Class in org.apache.spark.ml.feature
A feature transformer that filters out stop words from input.
StopWordsRemover(String) - Constructor for class org.apache.spark.ml.feature.StopWordsRemover
 
StopWordsRemover() - Constructor for class org.apache.spark.ml.feature.StopWordsRemover
 
storage() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
 
STORAGE_MEMORY() - Static method in class org.apache.spark.ui.ToolTips
 
storageLevel() - Method in class org.apache.spark.sql.Dataset
Get the Dataset's current storage level, or StorageLevel.NONE if not persisted.
storageLevel() - Method in class org.apache.spark.status.api.v1.RDDPartitionInfo
 
storageLevel() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
 
storageLevel() - Method in class org.apache.spark.status.LiveRDD
 
storageLevel() - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
 
storageLevel() - Method in class org.apache.spark.storage.BlockStatus
 
storageLevel() - Method in class org.apache.spark.storage.BlockUpdatedInfo
 
storageLevel() - Method in class org.apache.spark.storage.RDDInfo
 
StorageLevel - Class in org.apache.spark.storage
:: DeveloperApi :: Flags for controlling the storage of an RDD.
StorageLevel() - Constructor for class org.apache.spark.storage.StorageLevel
 
storageLevel() - Method in class org.apache.spark.streaming.receiver.Receiver
 
storageLevelFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
StorageLevels - Class in org.apache.spark.api.java
Expose some commonly useful storage level constants.
StorageLevels() - Constructor for class org.apache.spark.api.java.StorageLevels
 
storageLevelToJson(StorageLevel) - Static method in class org.apache.spark.util.JsonProtocol
 
StorageUtils - Class in org.apache.spark.storage
Helper methods for storage-related objects.
StorageUtils() - Constructor for class org.apache.spark.storage.StorageUtils
 
store(T) - Method in class org.apache.spark.streaming.receiver.Receiver
Store a single item of received data to Spark's memory.
store(ArrayBuffer<T>) - Method in class org.apache.spark.streaming.receiver.Receiver
Store an ArrayBuffer of received data as a data block into Spark's memory.
store(ArrayBuffer<T>, Object) - Method in class org.apache.spark.streaming.receiver.Receiver
Store an ArrayBuffer of received data as a data block into Spark's memory.
store(Iterator<T>) - Method in class org.apache.spark.streaming.receiver.Receiver
Store an iterator of received data as a data block into Spark's memory.
store(Iterator<T>, Object) - Method in class org.apache.spark.streaming.receiver.Receiver
Store an iterator of received data as a data block into Spark's memory.
store(Iterator<T>) - Method in class org.apache.spark.streaming.receiver.Receiver
Store an iterator of received data as a data block into Spark's memory.
store(Iterator<T>, Object) - Method in class org.apache.spark.streaming.receiver.Receiver
Store an iterator of received data as a data block into Spark's memory.
store(ByteBuffer) - Method in class org.apache.spark.streaming.receiver.Receiver
Store the bytes of received data as a data block into Spark's memory.
store(ByteBuffer, Object) - Method in class org.apache.spark.streaming.receiver.Receiver
Store the bytes of received data as a data block into Spark's memory.
storeBlock(StreamBlockId, ReceivedBlock) - Method in interface org.apache.spark.streaming.receiver.ReceivedBlockHandler
Store a received block with the given block id and return related metadata
storeValue(T) - Method in class org.apache.spark.storage.memory.DeserializedValuesHolder
 
storeValue(T) - Method in class org.apache.spark.storage.memory.SerializedValuesHolder
 
storeValue(T) - Method in interface org.apache.spark.storage.memory.ValuesHolder
 
strategy() - Method in interface org.apache.spark.ml.feature.ImputerParams
The imputation strategy.
Strategy - Class in org.apache.spark.mllib.tree.configuration
Stores all the configuration options for tree construction param: algo Learning goal.
Strategy(Enumeration.Value, Impurity, int, int, int, Enumeration.Value, Map<Object, Object>, int, double, int, double, boolean, int) - Constructor for class org.apache.spark.mllib.tree.configuration.Strategy
 
Strategy(Enumeration.Value, Impurity, int, int, int, Map<Integer, Integer>) - Constructor for class org.apache.spark.mllib.tree.configuration.Strategy
Java-friendly constructor for Strategy
StratifiedSamplingUtils - Class in org.apache.spark.util.random
Auxiliary functions and data structures for the sampleByKey method in PairRDDFunctions.
StratifiedSamplingUtils() - Constructor for class org.apache.spark.util.random.StratifiedSamplingUtils
 
STREAM() - Static method in class org.apache.spark.storage.BlockId
 
StreamBlockId - Class in org.apache.spark.storage
 
StreamBlockId(int, long) - Constructor for class org.apache.spark.storage.StreamBlockId
 
streamId() - Method in class org.apache.spark.status.api.v1.streaming.ReceiverInfo
 
streamId() - Method in class org.apache.spark.storage.StreamBlockId
 
streamId() - Method in class org.apache.spark.streaming.receiver.Receiver
Get the unique identifier the receiver input stream that this receiver is associated with.
streamId() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
 
streamIdToInputInfo() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
 
StreamingContext - Class in org.apache.spark.streaming
Main entry point for Spark Streaming functionality.
StreamingContext(SparkContext, Duration) - Constructor for class org.apache.spark.streaming.StreamingContext
Create a StreamingContext using an existing SparkContext.
StreamingContext(SparkConf, Duration) - Constructor for class org.apache.spark.streaming.StreamingContext
Create a StreamingContext by providing the configuration necessary for a new SparkContext.
StreamingContext(String, String, Duration, String, Seq<String>, Map<String, String>) - Constructor for class org.apache.spark.streaming.StreamingContext
Create a StreamingContext by providing the details necessary for creating a new SparkContext.
StreamingContext(String, Configuration) - Constructor for class org.apache.spark.streaming.StreamingContext
Recreate a StreamingContext from a checkpoint file.
StreamingContext(String) - Constructor for class org.apache.spark.streaming.StreamingContext
Recreate a StreamingContext from a checkpoint file.
StreamingContext(String, SparkContext) - Constructor for class org.apache.spark.streaming.StreamingContext
Recreate a StreamingContext from a checkpoint file using an existing SparkContext.
StreamingContextPythonHelper - Class in org.apache.spark.streaming
 
StreamingContextPythonHelper() - Constructor for class org.apache.spark.streaming.StreamingContextPythonHelper
 
StreamingContextState - Enum in org.apache.spark.streaming
:: DeveloperApi :: Represents the state of a StreamingContext.
StreamingKMeans - Class in org.apache.spark.mllib.clustering
StreamingKMeans provides methods for configuring a streaming k-means analysis, training the model on streaming, and using the model to make predictions on streaming data.
StreamingKMeans(int, double, String) - Constructor for class org.apache.spark.mllib.clustering.StreamingKMeans
 
StreamingKMeans() - Constructor for class org.apache.spark.mllib.clustering.StreamingKMeans
 
StreamingKMeansModel - Class in org.apache.spark.mllib.clustering
StreamingKMeansModel extends MLlib's KMeansModel for streaming algorithms, so it can keep track of a continuously updated weight associated with each cluster, and also update the model by doing a single iteration of the standard k-means algorithm.
StreamingKMeansModel(Vector[], double[]) - Constructor for class org.apache.spark.mllib.clustering.StreamingKMeansModel
 
StreamingLinearAlgorithm<M extends GeneralizedLinearModel,A extends GeneralizedLinearAlgorithm<M>> - Class in org.apache.spark.mllib.regression
:: DeveloperApi :: StreamingLinearAlgorithm implements methods for continuously training a generalized linear model on streaming data, and using it for prediction on (possibly different) streaming data.
StreamingLinearAlgorithm() - Constructor for class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
 
StreamingLinearRegressionWithSGD - Class in org.apache.spark.mllib.regression
Train or predict a linear regression model on streaming data.
StreamingLinearRegressionWithSGD() - Constructor for class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
Construct a StreamingLinearRegression object with default parameters: {stepSize: 0.1, numIterations: 50, miniBatchFraction: 1.0}.
StreamingListener - Interface in org.apache.spark.streaming.scheduler
:: DeveloperApi :: A listener interface for receiving information about an ongoing streaming computation.
StreamingListenerBatchCompleted - Class in org.apache.spark.streaming.scheduler
 
StreamingListenerBatchCompleted(BatchInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerBatchCompleted
 
StreamingListenerBatchStarted - Class in org.apache.spark.streaming.scheduler
 
StreamingListenerBatchStarted(BatchInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerBatchStarted
 
StreamingListenerBatchSubmitted - Class in org.apache.spark.streaming.scheduler
 
StreamingListenerBatchSubmitted(BatchInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerBatchSubmitted
 
StreamingListenerEvent - Interface in org.apache.spark.streaming.scheduler
:: DeveloperApi :: Base trait for events related to StreamingListener
StreamingListenerOutputOperationCompleted - Class in org.apache.spark.streaming.scheduler
 
StreamingListenerOutputOperationCompleted(OutputOperationInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationCompleted
 
StreamingListenerOutputOperationStarted - Class in org.apache.spark.streaming.scheduler
 
StreamingListenerOutputOperationStarted(OutputOperationInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationStarted
 
StreamingListenerReceiverError - Class in org.apache.spark.streaming.scheduler
 
StreamingListenerReceiverError(ReceiverInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerReceiverError
 
StreamingListenerReceiverStarted - Class in org.apache.spark.streaming.scheduler
 
StreamingListenerReceiverStarted(ReceiverInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted
 
StreamingListenerReceiverStopped - Class in org.apache.spark.streaming.scheduler
 
StreamingListenerReceiverStopped(ReceiverInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStopped
 
StreamingListenerStreamingStarted - Class in org.apache.spark.streaming.scheduler
 
StreamingListenerStreamingStarted(long) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerStreamingStarted
 
StreamingLogisticRegressionWithSGD - Class in org.apache.spark.mllib.classification
Train or predict a logistic regression model on streaming data.
StreamingLogisticRegressionWithSGD() - Constructor for class org.apache.spark.mllib.classification.StreamingLogisticRegressionWithSGD
Construct a StreamingLogisticRegression object with default parameters: {stepSize: 0.1, numIterations: 50, miniBatchFraction: 1.0, regParam: 0.0}.
StreamingQuery - Interface in org.apache.spark.sql.streaming
A handle to a query that is executing continuously in the background as new data arrives.
StreamingQueryException - Exception in org.apache.spark.sql.streaming
Exception that stopped a StreamingQuery.
StreamingQueryListener - Class in org.apache.spark.sql.streaming
Interface for listening to events related to StreamingQueries.
StreamingQueryListener() - Constructor for class org.apache.spark.sql.streaming.StreamingQueryListener
 
StreamingQueryListener.Event - Interface in org.apache.spark.sql.streaming
Base type of StreamingQueryListener events
StreamingQueryListener.QueryProgressEvent - Class in org.apache.spark.sql.streaming
Event representing any progress updates in a query.
StreamingQueryListener.QueryStartedEvent - Class in org.apache.spark.sql.streaming
Event representing the start of a query param: id A unique query id that persists across restarts.
StreamingQueryListener.QueryTerminatedEvent - Class in org.apache.spark.sql.streaming
Event representing that termination of a query.
StreamingQueryManager - Class in org.apache.spark.sql.streaming
A class to manage all the StreamingQuery active in a SparkSession.
StreamingQueryProgress - Class in org.apache.spark.sql.streaming
Information about progress made in the execution of a StreamingQuery during a trigger.
StreamingQueryStatus - Class in org.apache.spark.sql.streaming
Reports information about the instantaneous status of a streaming query.
StreamingStatistics - Class in org.apache.spark.status.api.v1.streaming
 
StreamingTest - Class in org.apache.spark.mllib.stat.test
Performs online 2-sample significance testing for a stream of (Boolean, Double) pairs.
StreamingTest() - Constructor for class org.apache.spark.mllib.stat.test.StreamingTest
 
StreamingTestMethod - Interface in org.apache.spark.mllib.stat.test
Significance testing methods for StreamingTest.
StreamInputInfo - Class in org.apache.spark.streaming.scheduler
:: DeveloperApi :: Track the information of input stream at specified batch time.
StreamInputInfo(int, long, Map<String, Object>) - Constructor for class org.apache.spark.streaming.scheduler.StreamInputInfo
 
streamName() - Method in class org.apache.spark.status.api.v1.streaming.ReceiverInfo
 
streams() - Method in class org.apache.spark.sql.SparkSession
:: Experimental :: Returns a StreamingQueryManager that allows managing all the StreamingQuerys active on this.
streams() - Method in class org.apache.spark.sql.SQLContext
 
StreamSinkProvider - Interface in org.apache.spark.sql.sources
::Experimental:: Implemented by objects that can produce a streaming Sink for a specific format or system.
StreamSourceProvider - Interface in org.apache.spark.sql.sources
::Experimental:: Implemented by objects that can produce a streaming Source for a specific format or system.
StreamWriter - Interface in org.apache.spark.sql.sources.v2.writer.streaming
A DataSourceWriter for use with structured streaming.
StreamWriteSupport - Interface in org.apache.spark.sql.sources.v2
A mix-in interface for DataSourceV2.
STRING() - Static method in class org.apache.spark.api.r.SerializationFormats
 
string() - Method in class org.apache.spark.sql.ColumnName
Creates a new StructField of type string.
STRING() - Static method in class org.apache.spark.sql.Encoders
An encoder for nullable string type.
StringAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.StringAccumulatorParam$
Deprecated.
 
StringArrayParam - Class in org.apache.spark.ml.param
:: DeveloperApi :: Specialized version of Param[Array[String} for Java.
StringArrayParam(Params, String, String, Function1<String[], Object>) - Constructor for class org.apache.spark.ml.param.StringArrayParam
 
StringArrayParam(Params, String, String) - Constructor for class org.apache.spark.ml.param.StringArrayParam
 
StringContains - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff the attribute evaluates to a string that contains the string value.
StringContains(String, String) - Constructor for class org.apache.spark.sql.sources.StringContains
 
StringEndsWith - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff the attribute evaluates to a string that ends with value.
StringEndsWith(String, String) - Constructor for class org.apache.spark.sql.sources.StringEndsWith
 
stringHalfWidth(String) - Static method in class org.apache.spark.util.Utils
Return the number of half widths in a given string.
StringIndexer - Class in org.apache.spark.ml.feature
A label indexer that maps a string column of labels to an ML column of label indices.
StringIndexer(String) - Constructor for class org.apache.spark.ml.feature.StringIndexer
 
StringIndexer() - Constructor for class org.apache.spark.ml.feature.StringIndexer
 
StringIndexerBase - Interface in org.apache.spark.ml.feature
Base trait for StringIndexer and StringIndexerModel.
StringIndexerModel - Class in org.apache.spark.ml.feature
Model fitted by StringIndexer.
StringIndexerModel(String, String[]) - Constructor for class org.apache.spark.ml.feature.StringIndexerModel
 
StringIndexerModel(String[]) - Constructor for class org.apache.spark.ml.feature.StringIndexerModel
 
stringIndexerOrderType() - Method in interface org.apache.spark.ml.feature.RFormulaBase
Param for how to order categories of a string FEATURE column used by StringIndexer.
stringOrderType() - Method in interface org.apache.spark.ml.feature.StringIndexerBase
Param for how to order labels of string column.
StringRRDD<T> - Class in org.apache.spark.api.r
An RDD that stores R objects as Array[String].
StringRRDD(RDD<T>, byte[], String, byte[], Object[], ClassTag<T>) - Constructor for class org.apache.spark.api.r.StringRRDD
 
StringStartsWith - Class in org.apache.spark.sql.sources
A filter that evaluates to true iff the attribute evaluates to a string that starts with value.
StringStartsWith(String, String) - Constructor for class org.apache.spark.sql.sources.StringStartsWith
 
StringToColumn(StringContext) - Constructor for class org.apache.spark.sql.SQLImplicits.StringToColumn
 
stringToSeq(String, Function1<String, T>) - Static method in class org.apache.spark.internal.config.ConfigHelpers
 
stringToSeq(String) - Static method in class org.apache.spark.util.Utils
 
StringType - Static variable in class org.apache.spark.sql.types.DataTypes
Gets the StringType object.
StringType - Class in org.apache.spark.sql.types
The data type representing String values.
StringType() - Constructor for class org.apache.spark.sql.types.StringType
 
stripXSS(String) - Static method in class org.apache.spark.ui.UIUtils
Remove suspicious characters of user input to prevent Cross-Site scripting (XSS) attacks
stronglyConnectedComponents(int) - Method in class org.apache.spark.graphx.GraphOps
Compute the strongly connected component (SCC) of each vertex and return a graph with the vertex value containing the lowest vertex id in the SCC containing that vertex.
StronglyConnectedComponents - Class in org.apache.spark.graphx.lib
Strongly connected components algorithm implementation.
StronglyConnectedComponents() - Constructor for class org.apache.spark.graphx.lib.StronglyConnectedComponents
 
struct(Seq<StructField>) - Method in class org.apache.spark.sql.ColumnName
Creates a new StructField of type struct.
struct(StructType) - Method in class org.apache.spark.sql.ColumnName
Creates a new StructField of type struct.
struct(Column...) - Static method in class org.apache.spark.sql.functions
Creates a new struct column.
struct(String, String...) - Static method in class org.apache.spark.sql.functions
Creates a new struct column that composes multiple input columns.
struct(Seq<Column>) - Static method in class org.apache.spark.sql.functions
Creates a new struct column.
struct(String, Seq<String>) - Static method in class org.apache.spark.sql.functions
Creates a new struct column that composes multiple input columns.
StructField - Class in org.apache.spark.sql.types
A field inside a StructType.
StructField(String, DataType, boolean, Metadata) - Constructor for class org.apache.spark.sql.types.StructField
 
StructType - Class in org.apache.spark.sql.types
A StructType object can be constructed by
StructType(StructField[]) - Constructor for class org.apache.spark.sql.types.StructType
 
StructType() - Constructor for class org.apache.spark.sql.types.StructType
No-arg constructor for kryo.
stsCredentials(String, String) - Method in class org.apache.spark.streaming.kinesis.SparkAWSCredentials.Builder
Use STS to assume an IAM role for temporary session-based authentication.
stsCredentials(String, String, String) - Method in class org.apache.spark.streaming.kinesis.SparkAWSCredentials.Builder
Use STS to assume an IAM role for temporary session-based authentication.
StudentTTest - Class in org.apache.spark.mllib.stat.test
Performs Students's 2-sample t-test.
StudentTTest() - Constructor for class org.apache.spark.mllib.stat.test.StudentTTest
 
subgraph(Function1<EdgeTriplet<VD, ED>, Object>, Function2<Object, VD, Object>) - Method in class org.apache.spark.graphx.Graph
Restricts the graph to only the vertices and edges satisfying the predicates.
subgraph(Function1<EdgeTriplet<VD, ED>, Object>, Function2<Object, VD, Object>) - Method in class org.apache.spark.graphx.impl.GraphImpl
 
submissionTime() - Method in class org.apache.spark.scheduler.StageInfo
When this stage was submitted from the DAGScheduler to a TaskScheduler.
submissionTime() - Method in interface org.apache.spark.SparkStageInfo
 
submissionTime() - Method in class org.apache.spark.SparkStageInfoImpl
 
submissionTime() - Method in class org.apache.spark.status.api.v1.JobData
 
submissionTime() - Method in class org.apache.spark.status.api.v1.StageData
 
submissionTime() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
 
submitJob(RDD<T>, Function1<Iterator<T>, U>, Seq<Object>, Function2<Object, U, BoxedUnit>, Function0<R>) - Method in interface org.apache.spark.JobSubmitter
Submit a job for execution and return a FutureAction holding the result.
submitJob(RDD<T>, Function1<Iterator<T>, U>, Seq<Object>, Function2<Object, U, BoxedUnit>, Function0<R>) - Method in class org.apache.spark.SparkContext
Submit a job for execution and return a FutureJob holding the result.
submitTasks(TaskSet) - Method in interface org.apache.spark.scheduler.TaskScheduler
 
subModels() - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
 
subModels() - Method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
 
subsamplingRate() - Method in interface org.apache.spark.ml.clustering.LDAParams
For Online optimizer only: optimizer = "online".
subsamplingRate() - Method in interface org.apache.spark.ml.tree.TreeEnsembleParams
Fraction of the training data used for learning each decision tree, in range (0, 1].
subsamplingRate() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
subsetAccuracy() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
Returns subset accuracy (for equal sets of labels)
substituteAppId(String, String) - Static method in class org.apache.spark.util.Utils
Replaces all the {{APP_ID}} occurrences with the App Id.
substituteAppNExecIds(String, String, String) - Static method in class org.apache.spark.util.Utils
Replaces all the {{EXECUTOR_ID}} occurrences with the Executor Id and {{APP_ID}} occurrences with the App Id.
substr(Column, Column) - Method in class org.apache.spark.sql.Column
An expression that returns a substring.
substr(int, int) - Method in class org.apache.spark.sql.Column
An expression that returns a substring.
substring(Column, int, int) - Static method in class org.apache.spark.sql.functions
Substring starts at pos and is of length len when str is String type or returns the slice of byte array that starts at pos in byte and is of length len when str is Binary type
substring_index(Column, String, int) - Static method in class org.apache.spark.sql.functions
Returns the substring from string str before count occurrences of the delimiter delim.
subtract(JavaDoubleRDD) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return an RDD with the elements from this that are not in other.
subtract(JavaDoubleRDD, int) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return an RDD with the elements from this that are not in other.
subtract(JavaDoubleRDD, Partitioner) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return an RDD with the elements from this that are not in other.
subtract(JavaPairRDD<K, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
Return an RDD with the elements from this that are not in other.
subtract(JavaPairRDD<K, V>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
Return an RDD with the elements from this that are not in other.
subtract(JavaPairRDD<K, V>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
Return an RDD with the elements from this that are not in other.
subtract(JavaRDD<T>) - Method in class org.apache.spark.api.java.JavaRDD
Return an RDD with the elements from this that are not in other.
subtract(JavaRDD<T>, int) - Method in class org.apache.spark.api.java.JavaRDD
Return an RDD with the elements from this that are not in other.
subtract(JavaRDD<T>, Partitioner) - Method in class org.apache.spark.api.java.JavaRDD
Return an RDD with the elements from this that are not in other.
subtract(BlockMatrix) - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
Subtracts the given block matrix other from this block matrix: this - other.
subtract(RDD<T>) - Method in class org.apache.spark.rdd.RDD
Return an RDD with the elements from this that are not in other.
subtract(RDD<T>, int) - Method in class org.apache.spark.rdd.RDD
Return an RDD with the elements from this that are not in other.
subtract(RDD<T>, Partitioner, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
Return an RDD with the elements from this that are not in other.
subtract(long, long) - Static method in class org.apache.spark.streaming.util.RawTextHelper
 
subtractByKey(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
Return an RDD with the pairs from this whose keys are not in other.
subtractByKey(JavaPairRDD<K, W>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
Return an RDD with the pairs from this whose keys are not in other.
subtractByKey(JavaPairRDD<K, W>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
Return an RDD with the pairs from this whose keys are not in other.
subtractByKey(RDD<Tuple2<K, W>>, ClassTag<W>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return an RDD with the pairs from this whose keys are not in other.
subtractByKey(RDD<Tuple2<K, W>>, int, ClassTag<W>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return an RDD with the pairs from this whose keys are not in other.
subtractByKey(RDD<Tuple2<K, W>>, Partitioner, ClassTag<W>) - Method in class org.apache.spark.rdd.PairRDDFunctions
Return an RDD with the pairs from this whose keys are not in other.
subtractMetrics(TaskMetrics, TaskMetrics) - Static method in class org.apache.spark.status.LiveEntityHelpers
Subtract m2 values from m1.
succeededTasks() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
succeededTasks() - Method in class org.apache.spark.status.LiveExecutorStageSummary
 
success(T) - Static method in class org.apache.spark.ml.feature.RFormulaParser
 
Success - Class in org.apache.spark
:: DeveloperApi :: Task succeeded.
Success() - Constructor for class org.apache.spark.Success
 
successful() - Method in class org.apache.spark.scheduler.TaskInfo
 
sum() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Add up the elements in this RDD.
Sum() - Static method in class org.apache.spark.mllib.tree.configuration.EnsembleCombiningStrategy
 
sum() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
Add up the elements in this RDD.
sum(MapFunction<T, Double>) - Static method in class org.apache.spark.sql.expressions.javalang.typed
Sum aggregate function for floating point (double) type.
sum(Function1<IN, Object>) - Static method in class org.apache.spark.sql.expressions.scalalang.typed
Sum aggregate function for floating point (double) type.
sum(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the sum of all values in the expression.
sum(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the sum of all values in the given column.
sum(String...) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Compute the sum for each numeric columns for each group.
sum(Seq<String>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
Compute the sum for each numeric columns for each group.
sum() - Method in class org.apache.spark.util.DoubleAccumulator
Returns the sum of elements added to the accumulator.
sum() - Method in class org.apache.spark.util.LongAccumulator
Returns the sum of elements added to the accumulator.
sum() - Method in class org.apache.spark.util.StatCounter
 
sumApprox(long, Double) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Approximate operation to return the sum within a timeout.
sumApprox(long) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Approximate operation to return the sum within a timeout.
sumApprox(long, double) - Method in class org.apache.spark.rdd.DoubleRDDFunctions
Approximate operation to return the sum within a timeout.
sumDistinct(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the sum of distinct values in the expression.
sumDistinct(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the sum of distinct values in the expression.
sumLong(MapFunction<T, Long>) - Static method in class org.apache.spark.sql.expressions.javalang.typed
Sum aggregate function for integral (long, i.e.
sumLong(Function1<IN, Object>) - Static method in class org.apache.spark.sql.expressions.scalalang.typed
Sum aggregate function for integral (long, i.e.
Summarizer - Class in org.apache.spark.ml.stat
Tools for vectorized statistics on MLlib Vectors.
Summarizer() - Constructor for class org.apache.spark.ml.stat.Summarizer
 
summary() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
Gets summary of model on training set.
summary() - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
Gets summary of model on training set.
summary() - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
Gets summary of model on training set.
summary() - Method in class org.apache.spark.ml.clustering.KMeansModel
Gets summary of model on training set.
summary() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
Gets R-like summary of model on training set.
summary() - Method in class org.apache.spark.ml.regression.LinearRegressionModel
Gets summary (e.g.
summary(Column, Column) - Method in class org.apache.spark.ml.stat.SummaryBuilder
Returns an aggregate object that contains the summary of the column with the requested metrics.
summary(Column) - Method in class org.apache.spark.ml.stat.SummaryBuilder
 
summary(String...) - Method in class org.apache.spark.sql.Dataset
Computes specified statistics for numeric and string columns.
summary(Seq<String>) - Method in class org.apache.spark.sql.Dataset
Computes specified statistics for numeric and string columns.
SummaryBuilder - Class in org.apache.spark.ml.stat
A builder object that provides summary statistics about a given column.
SummaryBuilder() - Constructor for class org.apache.spark.ml.stat.SummaryBuilder
 
supportDataType(DataType, boolean) - Method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
supportedFeatureSubsetStrategies() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
Accessor for supported featureSubsetStrategy settings: auto, all, onethird, sqrt, log2
supportedFeatureSubsetStrategies() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
Accessor for supported featureSubsetStrategy settings: auto, all, onethird, sqrt, log2
supportedFeatureSubsetStrategies() - Static method in class org.apache.spark.mllib.tree.RandomForest
List of supported feature subset sampling strategies.
supportedImpurities() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
Accessor for supported impurities: entropy, gini
supportedImpurities() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
Accessor for supported impurity settings: entropy, gini
supportedImpurities() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
Accessor for supported impurities: variance
supportedImpurities() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
Accessor for supported impurity settings: variance
supportedLossTypes() - Static method in class org.apache.spark.ml.classification.GBTClassifier
Accessor for supported loss settings: logistic
supportedLossTypes() - Static method in class org.apache.spark.ml.regression.GBTRegressor
Accessor for supported loss settings: squared (L2), absolute (L1)
supportedOptimizers() - Method in interface org.apache.spark.ml.clustering.LDAParams
Supported values for Param optimizer.
supportedSelectorTypes() - Static method in class org.apache.spark.mllib.feature.ChiSqSelector
Set of selector types that ChiSqSelector supports.
SupportsPushDownFilters - Interface in org.apache.spark.sql.sources.v2.reader
A mix-in interface for DataSourceReader.
SupportsPushDownRequiredColumns - Interface in org.apache.spark.sql.sources.v2.reader
A mix-in interface for DataSourceReader.
SupportsReportPartitioning - Interface in org.apache.spark.sql.sources.v2.reader
A mix in interface for DataSourceReader.
SupportsReportStatistics - Interface in org.apache.spark.sql.sources.v2.reader
A mix in interface for DataSourceReader.
SupportsScanColumnarBatch - Interface in org.apache.spark.sql.sources.v2.reader
A mix-in interface for DataSourceReader.
surrogateDF() - Method in class org.apache.spark.ml.feature.ImputerModel
 
SVDPlusPlus - Class in org.apache.spark.graphx.lib
Implementation of SVD++ algorithm.
SVDPlusPlus() - Constructor for class org.apache.spark.graphx.lib.SVDPlusPlus
 
SVDPlusPlus.Conf - Class in org.apache.spark.graphx.lib
Configuration parameters for SVDPlusPlus.
SVMDataGenerator - Class in org.apache.spark.mllib.util
:: DeveloperApi :: Generate sample data used for SVM.
SVMDataGenerator() - Constructor for class org.apache.spark.mllib.util.SVMDataGenerator
 
SVMModel - Class in org.apache.spark.mllib.classification
Model for Support Vector Machines (SVMs).
SVMModel(Vector, double) - Constructor for class org.apache.spark.mllib.classification.SVMModel
 
SVMWithSGD - Class in org.apache.spark.mllib.classification
Train a Support Vector Machine (SVM) using Stochastic Gradient Descent.
SVMWithSGD() - Constructor for class org.apache.spark.mllib.classification.SVMWithSGD
Construct a SVM object with default parameters: {stepSize: 1.0, numIterations: 100, regParm: 0.01, miniBatchFraction: 1.0}.
symbolToColumn(Symbol) - Method in class org.apache.spark.sql.SQLImplicits
An implicit conversion that turns a Scala Symbol into a Column.
symlink(File, File) - Static method in class org.apache.spark.util.Utils
Creates a symlink.
symmetricEigs(Function1<DenseVector<Object>, DenseVector<Object>>, int, int, double, int) - Static method in class org.apache.spark.mllib.linalg.EigenValueDecomposition
Compute the leading k eigenvalues and eigenvectors on a symmetric square matrix using ARPACK.
syr(double, Vector, DenseMatrix) - Static method in class org.apache.spark.ml.linalg.BLAS
A := alpha * x * x^T^ + A
syr(double, Vector, DenseMatrix) - Static method in class org.apache.spark.mllib.linalg.BLAS
A := alpha * x * x^T^ + A
SYSTEM_DEFAULT() - Static method in class org.apache.spark.sql.types.DecimalType
 
systemProperties() - Method in class org.apache.spark.status.api.v1.ApplicationEnvironmentInfo
 

T

t() - Method in class org.apache.spark.SerializableWritable
 
Table - Class in org.apache.spark.sql.catalog
A table in Spark, as returned by the listTables method in Catalog.
Table(String, String, String, String, boolean) - Constructor for class org.apache.spark.sql.catalog.Table
 
table(String) - Method in class org.apache.spark.sql.DataFrameReader
Returns the specified table as a DataFrame.
table() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
 
table(String) - Method in class org.apache.spark.sql.SparkSession
Returns the specified table/view as a DataFrame.
table(String) - Method in class org.apache.spark.sql.SQLContext
 
table(int) - Method in interface org.apache.spark.ui.PagedTable
 
TABLE_CLASS_NOT_STRIPED() - Static method in class org.apache.spark.ui.UIUtils
 
TABLE_CLASS_STRIPED() - Static method in class org.apache.spark.ui.UIUtils
 
TABLE_CLASS_STRIPED_SORTABLE() - Static method in class org.apache.spark.ui.UIUtils
 
TABLE_KEY - Static variable in class org.apache.spark.sql.sources.v2.DataSourceOptions
The option key for table name.
tableCssClass() - Method in interface org.apache.spark.ui.PagedTable
 
tableDesc() - Method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
 
tableExists(String) - Method in class org.apache.spark.sql.catalog.Catalog
Check if the table or view with the specified name exists.
tableExists(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
Check if the table or view with the specified name exists in the specified database.
tableExists(String, String) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Return whether a table/view with the specified name exists.
tableId() - Method in interface org.apache.spark.ui.PagedTable
 
tableName() - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
Returns the value of the table name option.
tableNames() - Method in class org.apache.spark.sql.SQLContext
 
tableNames(String) - Method in class org.apache.spark.sql.SQLContext
 
TableReader - Interface in org.apache.spark.sql.hive
A trait for subclasses that handle table scans.
tables() - Method in class org.apache.spark.sql.SQLContext
 
tables(String) - Method in class org.apache.spark.sql.SQLContext
 
TableScan - Interface in org.apache.spark.sql.sources
A BaseRelation that can produce all of its tuples as an RDD of Row objects.
tableType() - Method in class org.apache.spark.sql.catalog.Table
 
take(int) - Method in interface org.apache.spark.api.java.JavaRDDLike
Take the first num elements of the RDD.
take(int) - Method in class org.apache.spark.rdd.RDD
Take the first num elements of the RDD.
take(int) - Method in class org.apache.spark.sql.Dataset
Returns the first n rows in the Dataset.
takeAsList(int) - Method in class org.apache.spark.sql.Dataset
Returns the first n rows in the Dataset as a list.
takeAsync(int) - Method in interface org.apache.spark.api.java.JavaRDDLike
The asynchronous version of the take action, which returns a future for retrieving the first num elements of this RDD.
takeAsync(int) - Method in class org.apache.spark.rdd.AsyncRDDActions
Returns a future for retrieving the first num elements of the RDD.
takeOrdered(int, Comparator<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Returns the first k (smallest) elements from this RDD as defined by the specified Comparator[T] and maintains the order.
takeOrdered(int) - Method in interface org.apache.spark.api.java.JavaRDDLike
Returns the first k (smallest) elements from this RDD using the natural ordering for T while maintain the order.
takeOrdered(int, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
Returns the first k (smallest) elements from this RDD as defined by the specified implicit Ordering[T] and maintains the ordering.
takeSample(boolean, int) - Method in interface org.apache.spark.api.java.JavaRDDLike
 
takeSample(boolean, int, long) - Method in interface org.apache.spark.api.java.JavaRDDLike
 
takeSample(boolean, int, long) - Method in class org.apache.spark.rdd.RDD
Return a fixed-size sampled subset of this RDD in an array
tallSkinnyQR(boolean) - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
Compute QR decomposition for RowMatrix.
tan(Column) - Static method in class org.apache.spark.sql.functions
 
tan(String) - Static method in class org.apache.spark.sql.functions
 
tanh(Column) - Static method in class org.apache.spark.sql.functions
 
tanh(String) - Static method in class org.apache.spark.sql.functions
 
targetStorageLevel() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
targetStorageLevel() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
task() - Method in class org.apache.spark.CleanupTaskWeakReference
 
TASK_DESERIALIZATION_TIME() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
 
TASK_DESERIALIZATION_TIME() - Static method in class org.apache.spark.ui.ToolTips
 
TASK_INDEX() - Static method in class org.apache.spark.status.TaskIndexNames
 
TASK_TIME() - Static method in class org.apache.spark.ui.ToolTips
 
taskAttemptId() - Method in class org.apache.spark.BarrierTaskContext
 
taskAttemptId() - Method in class org.apache.spark.TaskContext
An ID that is unique to this task attempt (within the same SparkContext, no two task attempts will share the same attempt ID).
TaskCommitDenied - Class in org.apache.spark
:: DeveloperApi :: Task requested the driver to commit, but was denied.
TaskCommitDenied(int, int, int) - Constructor for class org.apache.spark.TaskCommitDenied
 
TaskCommitMessage(Object) - Constructor for class org.apache.spark.internal.io.FileCommitProtocol.TaskCommitMessage
 
TaskCompletionListener - Interface in org.apache.spark.util
:: DeveloperApi ::
TaskContext - Class in org.apache.spark
Contextual information about a task which can be read or mutated during execution.
TaskContext() - Constructor for class org.apache.spark.TaskContext
 
TaskData - Class in org.apache.spark.status.api.v1
 
TaskDetailsClassNames - Class in org.apache.spark.ui.jobs
Names of the CSS classes corresponding to each type of task detail.
TaskDetailsClassNames() - Constructor for class org.apache.spark.ui.jobs.TaskDetailsClassNames
 
taskEndFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
TaskEndReason - Interface in org.apache.spark
:: DeveloperApi :: Various possible reasons why a task ended.
taskEndReasonFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
taskEndReasonToJson(TaskEndReason) - Static method in class org.apache.spark.util.JsonProtocol
 
taskEndToJson(SparkListenerTaskEnd) - Static method in class org.apache.spark.util.JsonProtocol
 
TaskFailedReason - Interface in org.apache.spark
:: DeveloperApi :: Various possible reasons why a task failed.
TaskFailureListener - Interface in org.apache.spark.util
:: DeveloperApi ::
taskFailures() - Method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklisted
 
taskFailures() - Method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklistedForStage
 
taskGettingResultFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
taskGettingResultToJson(SparkListenerTaskGettingResult) - Static method in class org.apache.spark.util.JsonProtocol
 
taskId() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask
 
taskId() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate
 
taskId() - Method in class org.apache.spark.scheduler.local.KillTask
 
taskId() - Method in class org.apache.spark.scheduler.local.StatusUpdate
 
taskId() - Method in class org.apache.spark.scheduler.TaskInfo
 
taskId() - Method in class org.apache.spark.status.api.v1.TaskData
 
taskId() - Method in class org.apache.spark.storage.TaskResultBlockId
 
TaskIndexNames - Class in org.apache.spark.status
Tasks have a lot of indices that are used in a few different places.
TaskIndexNames() - Constructor for class org.apache.spark.status.TaskIndexNames
 
taskInfo() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
 
taskInfo() - Method in class org.apache.spark.scheduler.SparkListenerTaskGettingResult
 
taskInfo() - Method in class org.apache.spark.scheduler.SparkListenerTaskStart
 
TaskInfo - Class in org.apache.spark.scheduler
:: DeveloperApi :: Information about a running task attempt inside a TaskSet.
TaskInfo(long, int, int, long, String, String, Enumeration.Value, boolean) - Constructor for class org.apache.spark.scheduler.TaskInfo
 
taskInfoFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
taskInfoToJson(TaskInfo) - Static method in class org.apache.spark.util.JsonProtocol
 
TaskKilled - Class in org.apache.spark
:: DeveloperApi :: Task was killed intentionally and needs to be rescheduled.
TaskKilled(String, Seq<AccumulableInfo>, Seq<AccumulatorV2<?, ?>>) - Constructor for class org.apache.spark.TaskKilled
 
TaskKilledException - Exception in org.apache.spark
:: DeveloperApi :: Exception thrown when a task is explicitly killed (i.e., task failure is expected).
TaskKilledException(String) - Constructor for exception org.apache.spark.TaskKilledException
 
TaskKilledException() - Constructor for exception org.apache.spark.TaskKilledException
 
taskLocality() - Method in class org.apache.spark.scheduler.TaskInfo
 
TaskLocality - Class in org.apache.spark.scheduler
 
TaskLocality() - Constructor for class org.apache.spark.scheduler.TaskLocality
 
taskLocality() - Method in class org.apache.spark.status.api.v1.TaskData
 
TaskLocation - Interface in org.apache.spark.scheduler
A location where a task should run.
TaskMetricDistributions - Class in org.apache.spark.status.api.v1
 
taskMetrics() - Method in class org.apache.spark.BarrierTaskContext
 
taskMetrics() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
 
taskMetrics() - Method in class org.apache.spark.scheduler.StageInfo
 
taskMetrics() - Method in class org.apache.spark.status.api.v1.TaskData
 
TaskMetrics - Class in org.apache.spark.status.api.v1
 
taskMetrics() - Method in class org.apache.spark.TaskContext
 
taskMetricsFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
taskMetricsToJson(TaskMetrics) - Static method in class org.apache.spark.util.JsonProtocol
 
TaskResult<T> - Interface in org.apache.spark.scheduler
 
TASKRESULT() - Static method in class org.apache.spark.storage.BlockId
 
TaskResultBlockId - Class in org.apache.spark.storage
 
TaskResultBlockId(long) - Constructor for class org.apache.spark.storage.TaskResultBlockId
 
TaskResultLost - Class in org.apache.spark
:: DeveloperApi :: The task finished successfully, but the result was lost from the executor's block manager before it was fetched.
TaskResultLost() - Constructor for class org.apache.spark.TaskResultLost
 
tasks() - Method in class org.apache.spark.status.api.v1.StageData
 
TaskScheduler - Interface in org.apache.spark.scheduler
Low-level task scheduler interface, currently implemented exclusively by TaskSchedulerImpl.
TaskSchedulerIsSet - Class in org.apache.spark
An event that SparkContext uses to notify HeartbeatReceiver that SparkContext.taskScheduler is created.
TaskSchedulerIsSet() - Constructor for class org.apache.spark.TaskSchedulerIsSet
 
TaskSorting - Enum in org.apache.spark.status.api.v1
 
taskStartFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
taskStartToJson(SparkListenerTaskStart) - Static method in class org.apache.spark.util.JsonProtocol
 
TaskState - Class in org.apache.spark
 
TaskState() - Constructor for class org.apache.spark.TaskState
 
taskSucceeded(int, Object) - Method in interface org.apache.spark.scheduler.JobListener
 
taskTime() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
 
taskTime() - Method in class org.apache.spark.status.LiveExecutorStageSummary
 
taskType() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
 
TEMP_DIR_SHUTDOWN_PRIORITY() - Static method in class org.apache.spark.util.ShutdownHookManager
The shutdown priority of temp directory must be lower than the SparkContext shutdown priority.
TEMP_LOCAL() - Static method in class org.apache.spark.storage.BlockId
 
TEMP_SHUFFLE() - Static method in class org.apache.spark.storage.BlockId
 
tempFileWith(File) - Static method in class org.apache.spark.util.Utils
Returns a path of temporary file which is in the same directory with path.
TeradataDialect - Class in org.apache.spark.sql.jdbc
 
TeradataDialect() - Constructor for class org.apache.spark.sql.jdbc.TeradataDialect
 
Term - Interface in org.apache.spark.ml.feature
R formula terms.
terminateProcess(Process, long) - Static method in class org.apache.spark.util.Utils
Terminates a process waiting for at most the specified duration.
test(Dataset<Row>, String, String) - Static method in class org.apache.spark.ml.stat.ChiSquareTest
Conduct Pearson's independence test for every feature against the label.
test(Dataset<?>, String, String, double...) - Static method in class org.apache.spark.ml.stat.KolmogorovSmirnovTest
Convenience function to conduct a one-sample, two-sided Kolmogorov-Smirnov test for probability distribution equality.
test(Dataset<?>, String, Function1<Object, Object>) - Static method in class org.apache.spark.ml.stat.KolmogorovSmirnovTest
 
test(Dataset<?>, String, Function<Double, Double>) - Static method in class org.apache.spark.ml.stat.KolmogorovSmirnovTest
 
test(Dataset<?>, String, String, Seq<Object>) - Static method in class org.apache.spark.ml.stat.KolmogorovSmirnovTest
 
TEST() - Static method in class org.apache.spark.storage.BlockId
 
TEST_ACCUM() - Static method in class org.apache.spark.InternalAccumulator
 
testCommandAvailable(String) - Static method in class org.apache.spark.TestUtils
Test if a command is available.
testOneSample(RDD<Object>, String, double...) - Static method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTest
A convenience function that allows running the KS test for 1 set of sample data against a named distribution
testOneSample(RDD<Object>, Function1<Object, Object>) - Static method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTest
 
testOneSample(RDD<Object>, RealDistribution) - Static method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTest
 
testOneSample(RDD<Object>, String, Seq<Object>) - Static method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTest
 
TestResult<DF> - Interface in org.apache.spark.mllib.stat.test
Trait for hypothesis test results.
TestUtils - Class in org.apache.spark
Utilities for tests.
TestUtils() - Constructor for class org.apache.spark.TestUtils
 
text(String...) - Method in class org.apache.spark.sql.DataFrameReader
Loads text files and returns a DataFrame whose schema starts with a string column named "value", and followed by partitioned columns if there are any.
text(String) - Method in class org.apache.spark.sql.DataFrameReader
Loads text files and returns a DataFrame whose schema starts with a string column named "value", and followed by partitioned columns if there are any.
text(Seq<String>) - Method in class org.apache.spark.sql.DataFrameReader
Loads text files and returns a DataFrame whose schema starts with a string column named "value", and followed by partitioned columns if there are any.
text(String) - Method in class org.apache.spark.sql.DataFrameWriter
Saves the content of the DataFrame in a text file at the specified path.
text(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Loads text files and returns a DataFrame whose schema starts with a string column named "value", and followed by partitioned columns if there are any.
textFile(String) - Method in class org.apache.spark.api.java.JavaSparkContext
Read a text file from HDFS, a local file system (available on all nodes), or any Hadoop-supported file system URI, and return it as an RDD of Strings.
textFile(String, int) - Method in class org.apache.spark.api.java.JavaSparkContext
Read a text file from HDFS, a local file system (available on all nodes), or any Hadoop-supported file system URI, and return it as an RDD of Strings.
textFile(String, int) - Method in class org.apache.spark.SparkContext
Read a text file from HDFS, a local file system (available on all nodes), or any Hadoop-supported file system URI, and return it as an RDD of Strings.
textFile(String...) - Method in class org.apache.spark.sql.DataFrameReader
Loads text files and returns a Dataset of String.
textFile(String) - Method in class org.apache.spark.sql.DataFrameReader
Loads text files and returns a Dataset of String.
textFile(Seq<String>) - Method in class org.apache.spark.sql.DataFrameReader
Loads text files and returns a Dataset of String.
textFile(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
Loads text file(s) and returns a Dataset of String.
textFileStream(String) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create an input stream that monitors a Hadoop-compatible filesystem for new files and reads them as text files (using key as LongWritable, value as Text and input format as TextInputFormat).
textFileStream(String) - Method in class org.apache.spark.streaming.StreamingContext
Create an input stream that monitors a Hadoop-compatible filesystem for new files and reads them as text files (using key as LongWritable, value as Text and input format as TextInputFormat).
textResponderToServlet(Function1<HttpServletRequest, String>) - Static method in class org.apache.spark.ui.JettyUtils
 
theta() - Method in class org.apache.spark.ml.classification.NaiveBayesModel
 
theta() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$.Data
 
theta() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data
 
theta() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
 
thisClassName() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$
Hard-code class name string in case it changes in the future
thisClassName() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$
Hard-code class name string in case it changes in the future
thisClassName() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
 
thisFormatVersion() - Method in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$
 
thisFormatVersion() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$
 
thisFormatVersion() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$
 
thisFormatVersion() - Method in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$
 
thisFormatVersion() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
 
threadId() - Method in class org.apache.spark.status.api.v1.ThreadStackTrace
 
threadName() - Method in class org.apache.spark.status.api.v1.ThreadStackTrace
 
ThreadSafeRpcEndpoint - Interface in org.apache.spark.rpc
A trait that requires RpcEnv thread-safely sending messages to it.
ThreadStackTrace - Class in org.apache.spark.status.api.v1
 
ThreadStackTrace(long, String, Thread.State, StackTrace, Option<Object>, String, Seq<String>) - Constructor for class org.apache.spark.status.api.v1.ThreadStackTrace
 
threadState() - Method in class org.apache.spark.status.api.v1.ThreadStackTrace
 
ThreadUtils - Class in org.apache.spark.util
 
ThreadUtils() - Constructor for class org.apache.spark.util.ThreadUtils
 
threshold() - Method in interface org.apache.spark.ml.classification.LinearSVCParams
Param for threshold in binary classification prediction.
threshold() - Method in class org.apache.spark.ml.feature.Binarizer
Param for threshold used to binarize continuous features.
threshold() - Method in interface org.apache.spark.ml.param.shared.HasThreshold
Param for threshold in binary classification prediction, in range [0, 1].
threshold() - Method in class org.apache.spark.ml.tree.ContinuousSplit
 
threshold() - Method in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$.Data
 
threshold() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData
 
threshold() - Method in class org.apache.spark.mllib.tree.model.Split
 
thresholds() - Method in interface org.apache.spark.ml.param.shared.HasThresholds
Param for Thresholds in multi-class classification to adjust the probability of predicting each class.
thresholds() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
Returns thresholds in descending order.
throwBalls(int, RDD<?>, double, DefaultPartitionCoalescer.PartitionLocations) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
 
time() - Method in class org.apache.spark.scheduler.SparkListenerApplicationEnd
 
time() - Method in class org.apache.spark.scheduler.SparkListenerApplicationStart
 
time() - Method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
 
time() - Method in class org.apache.spark.scheduler.SparkListenerBlockManagerRemoved
 
time() - Method in class org.apache.spark.scheduler.SparkListenerExecutorAdded
 
time() - Method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklisted
 
time() - Method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklistedForStage
 
time() - Method in class org.apache.spark.scheduler.SparkListenerExecutorRemoved
 
time() - Method in class org.apache.spark.scheduler.SparkListenerExecutorUnblacklisted
 
time() - Method in class org.apache.spark.scheduler.SparkListenerJobEnd
 
time() - Method in class org.apache.spark.scheduler.SparkListenerJobStart
 
time() - Method in class org.apache.spark.scheduler.SparkListenerNodeBlacklisted
 
time() - Method in class org.apache.spark.scheduler.SparkListenerNodeBlacklistedForStage
 
time() - Method in class org.apache.spark.scheduler.SparkListenerNodeUnblacklisted
 
time(Function0<T>) - Method in class org.apache.spark.sql.SparkSession
Executes some code block and prints to stdout the time taken to execute the block.
time() - Method in exception org.apache.spark.sql.streaming.StreamingQueryException
Time when the exception occurred
time() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerStreamingStarted
 
Time - Class in org.apache.spark.streaming
This is a simple class that represents an absolute instant of time.
Time(long) - Constructor for class org.apache.spark.streaming.Time
 
timeFromString(String, TimeUnit) - Static method in class org.apache.spark.internal.config.ConfigHelpers
 
timeIt(int, Function0<BoxedUnit>, Option<Function0<BoxedUnit>>) - Static method in class org.apache.spark.util.Utils
Timing method based on iterations that permit JVM JIT optimization.
timeout(Duration) - Method in class org.apache.spark.streaming.StateSpec
Set the duration after which the state of an idle key will be removed.
TIMER() - Static method in class org.apache.spark.metrics.sink.StatsdMetricType
 
times(Decimal, Decimal) - Method in interface org.apache.spark.sql.types.Decimal.DecimalIsConflicted
 
times(int) - Method in class org.apache.spark.streaming.Duration
 
times(int, Function0<BoxedUnit>) - Static method in class org.apache.spark.util.Utils
Method executed for repeating a task for side effects.
timestamp() - Method in class org.apache.spark.sql.ColumnName
Creates a new StructField of type timestamp.
TIMESTAMP() - Static method in class org.apache.spark.sql.Encoders
An encoder for nullable timestamp type.
timestamp() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
 
TimestampType - Static variable in class org.apache.spark.sql.types.DataTypes
Gets the TimestampType object.
TimestampType - Class in org.apache.spark.sql.types
The data type representing java.sql.Timestamp values.
TimestampType() - Constructor for class org.apache.spark.sql.types.TimestampType
 
timeStringAsMs(String) - Static method in class org.apache.spark.util.Utils
Convert a time parameter such as (50s, 100ms, or 250us) to milliseconds for internal use.
timeStringAsSeconds(String) - Static method in class org.apache.spark.util.Utils
Convert a time parameter such as (50s, 100ms, or 250us) to seconds for internal use.
timeTakenMs(Function0<T>) - Static method in class org.apache.spark.util.Utils
Records the duration of running `body`.
timeToString(long, TimeUnit) - Static method in class org.apache.spark.internal.config.ConfigHelpers
 
TimeTrackingOutputStream - Class in org.apache.spark.storage
Intercepts write calls and tracks total time spent writing in order to update shuffle write metrics.
TimeTrackingOutputStream(ShuffleWriteMetrics, OutputStream) - Constructor for class org.apache.spark.storage.TimeTrackingOutputStream
 
timeUnit() - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
 
TIMING_DATA() - Static method in class org.apache.spark.api.r.SpecialLengths
 
to(Time, Duration) - Method in class org.apache.spark.streaming.Time
 
to_date(Column) - Static method in class org.apache.spark.sql.functions
Converts the column into DateType by casting rules to DateType.
to_date(Column, String) - Static method in class org.apache.spark.sql.functions
Converts the column into a DateType with a specified format
to_json(Column, Map<String, String>) - Static method in class org.apache.spark.sql.functions
(Scala-specific) Converts a column containing a StructType, ArrayType or a MapType into a JSON string with the specified schema.
to_json(Column, Map<String, String>) - Static method in class org.apache.spark.sql.functions
(Java-specific) Converts a column containing a StructType, ArrayType or a MapType into a JSON string with the specified schema.
to_json(Column) - Static method in class org.apache.spark.sql.functions
Converts a column containing a StructType, ArrayType or a MapType into a JSON string with the specified schema.
to_timestamp(Column) - Static method in class org.apache.spark.sql.functions
Converts to a timestamp by casting rules to TimestampType.
to_timestamp(Column, String) - Static method in class org.apache.spark.sql.functions
Converts time string with the given pattern to timestamp.
to_utc_timestamp(Column, String) - Static method in class org.apache.spark.sql.functions
Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a time in the given time zone, and renders that time as a timestamp in UTC.
to_utc_timestamp(Column, Column) - Static method in class org.apache.spark.sql.functions
Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a time in the given time zone, and renders that time as a timestamp in UTC.
toApacheCommonsStats(StatCounter) - Method in interface org.apache.spark.mllib.stat.test.StreamingTestMethod
Implicit adapter to convert between streaming summary statistics type and the type required by the t-testing libraries.
toApi() - Method in class org.apache.spark.status.LiveRDDDistribution
 
toApi() - Method in class org.apache.spark.status.LiveStage
 
toArray() - Method in class org.apache.spark.input.PortableDataStream
Read the file as a byte array
toArray() - Method in class org.apache.spark.ml.linalg.DenseVector
 
toArray() - Method in interface org.apache.spark.ml.linalg.Matrix
Converts to a dense array in column major.
toArray() - Method in class org.apache.spark.ml.linalg.SparseVector
 
toArray() - Method in interface org.apache.spark.ml.linalg.Vector
Converts the instance to a double array.
toArray() - Method in class org.apache.spark.mllib.linalg.DenseVector
 
toArray() - Method in interface org.apache.spark.mllib.linalg.Matrix
Converts to a dense array in column major.
toArray() - Method in class org.apache.spark.mllib.linalg.SparseVector
 
toArray() - Method in interface org.apache.spark.mllib.linalg.Vector
Converts the instance to a double array.
toBigDecimal() - Method in class org.apache.spark.sql.types.Decimal
 
toBlockMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
Converts to BlockMatrix.
toBlockMatrix(int, int) - Method in class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
Converts to BlockMatrix.
toBlockMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
Converts to BlockMatrix.
toBlockMatrix(int, int) - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
Converts to BlockMatrix.
toBoolean(String, String) - Static method in class org.apache.spark.internal.config.ConfigHelpers
 
toBooleanArray() - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
toBreeze() - Method in interface org.apache.spark.mllib.linalg.distributed.DistributedMatrix
Collects data and assembles a local dense breeze matrix (for test only).
toByte() - Method in class org.apache.spark.sql.types.Decimal
 
toByteArray() - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
toByteArray() - Method in class org.apache.spark.util.sketch.CountMinSketch
Serializes this CountMinSketch and returns the serialized form.
toByteBuffer() - Method in interface org.apache.spark.storage.BlockData
 
toByteBuffer() - Method in class org.apache.spark.storage.DiskBlockData
 
toCatalystDecimal(HiveDecimalObjectInspector, Object) - Static method in class org.apache.spark.sql.hive.HiveShim
 
toChunkedByteBuffer(Function1<Object, ByteBuffer>) - Method in interface org.apache.spark.storage.BlockData
 
toChunkedByteBuffer(Function1<Object, ByteBuffer>) - Method in class org.apache.spark.storage.DiskBlockData
 
toColumn() - Method in class org.apache.spark.sql.expressions.Aggregator
Returns this Aggregator as a TypedColumn that can be used in Dataset.
toCoordinateMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
Converts to CoordinateMatrix.
toCoordinateMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
Converts this matrix to a CoordinateMatrix.
toCryptoConf(SparkConf) - Static method in class org.apache.spark.security.CryptoStreamUtils
 
toDDL() - Method in class org.apache.spark.sql.types.StructField
Returns a string containing a schema in DDL format.
toDDL() - Method in class org.apache.spark.sql.types.StructType
Returns a string containing a schema in DDL format.
toDebugString() - Method in interface org.apache.spark.api.java.JavaRDDLike
A description of this RDD and its recursive dependencies for debugging.
toDebugString() - Method in interface org.apache.spark.ml.tree.DecisionTreeModel
Full description of model
toDebugString() - Method in interface org.apache.spark.ml.tree.TreeEnsembleModel
Full description of model
toDebugString() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
Print the full model to a string.
toDebugString() - Method in class org.apache.spark.rdd.RDD
A description of this RDD and its recursive dependencies for debugging.
toDebugString() - Method in class org.apache.spark.SparkConf
Return a string listing all keys and values, one per line.
toDebugString() - Method in class org.apache.spark.sql.types.Decimal
 
toDegrees(Column) - Static method in class org.apache.spark.sql.functions
Deprecated.
Use degrees. Since 2.1.0.
toDegrees(String) - Static method in class org.apache.spark.sql.functions
Deprecated.
Use degrees. Since 2.1.0.
toDense() - Method in interface org.apache.spark.ml.linalg.Matrix
Converts this matrix to a dense matrix while maintaining the layout of the current matrix.
toDense() - Method in interface org.apache.spark.ml.linalg.Vector
Converts this vector to a dense vector.
toDense() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
Generate a DenseMatrix from the given SparseMatrix.
toDense() - Method in interface org.apache.spark.mllib.linalg.Vector
Converts this vector to a dense vector.
toDenseColMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
Converts this matrix to a dense matrix in column major order.
toDenseMatrix(boolean) - Method in interface org.apache.spark.ml.linalg.Matrix
Converts this matrix to a dense matrix.
toDenseRowMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
Converts this matrix to a dense matrix in row major order.
toDF(String...) - Method in class org.apache.spark.sql.Dataset
Converts this strongly typed collection of data to generic DataFrame with columns renamed.
toDF() - Method in class org.apache.spark.sql.Dataset
Converts this strongly typed collection of data to generic Dataframe.
toDF(Seq<String>) - Method in class org.apache.spark.sql.Dataset
Converts this strongly typed collection of data to generic DataFrame with columns renamed.
toDF() - Method in class org.apache.spark.sql.DatasetHolder
 
toDF(Seq<String>) - Method in class org.apache.spark.sql.DatasetHolder
 
toDouble(Decimal) - Method in interface org.apache.spark.sql.types.Decimal.DecimalIsConflicted
 
toDouble() - Method in class org.apache.spark.sql.types.Decimal
 
toDoubleArray() - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
toDS() - Method in class org.apache.spark.sql.DatasetHolder
 
toEdgeTriplet() - Method in class org.apache.spark.graphx.EdgeContext
Converts the edge and vertex properties into an EdgeTriplet for convenience.
toErrorString() - Method in class org.apache.spark.ExceptionFailure
 
toErrorString() - Method in class org.apache.spark.ExecutorLostFailure
 
toErrorString() - Method in class org.apache.spark.FetchFailed
 
toErrorString() - Static method in class org.apache.spark.Resubmitted
 
toErrorString() - Method in class org.apache.spark.TaskCommitDenied
 
toErrorString() - Method in interface org.apache.spark.TaskFailedReason
Error message displayed in the web UI.
toErrorString() - Method in class org.apache.spark.TaskKilled
 
toErrorString() - Static method in class org.apache.spark.TaskResultLost
 
toErrorString() - Static method in class org.apache.spark.UnknownReason
 
toFloat(Decimal) - Method in interface org.apache.spark.sql.types.Decimal.DecimalIsConflicted
 
toFloat() - Method in class org.apache.spark.sql.types.Decimal
 
toFloatArray() - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
toFormattedString() - Method in class org.apache.spark.streaming.Duration
 
toIndexedRowMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
Converts to IndexedRowMatrix.
toIndexedRowMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
Converts to IndexedRowMatrix.
toInputStream() - Method in interface org.apache.spark.storage.BlockData
 
toInputStream() - Method in class org.apache.spark.storage.DiskBlockData
 
toInspector(DataType) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
toInspector(Expression) - Method in interface org.apache.spark.sql.hive.HiveInspectors
Map the catalyst expression to ObjectInspector, however, if the expression is Literal or foldable, a constant writable object inspector returns; Otherwise, we always get the object inspector according to its data type(in catalyst)
toInspector(DataType) - Static method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
toInspector(Expression) - Static method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
toInt(Decimal) - Method in interface org.apache.spark.sql.types.Decimal.DecimalIsConflicted
 
toInt() - Method in class org.apache.spark.sql.types.Decimal
 
toInt() - Method in class org.apache.spark.storage.StorageLevel
 
toIntArray() - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
toJavaBigDecimal() - Method in class org.apache.spark.sql.types.Decimal
 
toJavaBigInteger() - Method in class org.apache.spark.sql.types.Decimal
 
toJavaDStream() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Convert to a JavaDStream
toJavaRDD() - Method in class org.apache.spark.rdd.RDD
 
toJavaRDD() - Method in class org.apache.spark.sql.Dataset
Returns the content of the Dataset as a JavaRDD of Ts.
toJson(Matrix) - Static method in class org.apache.spark.ml.linalg.JsonMatrixConverter
Coverts the Matrix to a JSON string.
toJson(Vector) - Static method in class org.apache.spark.ml.linalg.JsonVectorConverter
Coverts the vector to a JSON string.
toJson() - Method in class org.apache.spark.mllib.linalg.DenseVector
 
toJson() - Method in class org.apache.spark.mllib.linalg.SparseVector
 
toJson() - Method in interface org.apache.spark.mllib.linalg.Vector
Converts the vector to a JSON string.
toJSON() - Method in class org.apache.spark.sql.Dataset
Returns the content of the Dataset as a Dataset of JSON strings.
Tokenizer - Class in org.apache.spark.ml.feature
A tokenizer that converts the input string to lowercase and then splits it by white spaces.
Tokenizer(String) - Constructor for class org.apache.spark.ml.feature.Tokenizer
 
Tokenizer() - Constructor for class org.apache.spark.ml.feature.Tokenizer
 
tokens() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.UpdateDelegationTokens
 
tol() - Method in interface org.apache.spark.ml.param.shared.HasTol
Param for the convergence tolerance for iterative algorithms (&gt;= 0).
toLocal() - Method in class org.apache.spark.ml.clustering.DistributedLDAModel
Convert this distributed model to a local representation.
toLocal() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
Convert model to a local model.
toLocalIterator() - Method in interface org.apache.spark.api.java.JavaRDDLike
Return an iterator that contains all of the elements in this RDD.
toLocalIterator() - Method in class org.apache.spark.rdd.RDD
Return an iterator that contains all of the elements in this RDD.
toLocalIterator() - Method in class org.apache.spark.sql.Dataset
Returns an iterator that contains all rows in this Dataset.
toLocalMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
Collect the distributed matrix on the driver as a DenseMatrix.
toLong(Decimal) - Method in interface org.apache.spark.sql.types.Decimal.DecimalIsConflicted
 
toLong() - Method in class org.apache.spark.sql.types.Decimal
 
toLongArray() - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
toLowercase() - Method in class org.apache.spark.ml.feature.RegexTokenizer
Indicates whether to convert all characters to lowercase before tokenizing.
toMetadata(Metadata) - Method in class org.apache.spark.ml.attribute.Attribute
Converts to ML metadata with some existing metadata.
toMetadata() - Method in class org.apache.spark.ml.attribute.Attribute
Converts to ML metadata
toMetadata(Metadata) - Method in class org.apache.spark.ml.attribute.AttributeGroup
Converts to ML metadata with some existing metadata.
toMetadata() - Method in class org.apache.spark.ml.attribute.AttributeGroup
Converts to ML metadata
toMetadata(Metadata) - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
toMetadata() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
toNetty() - Method in interface org.apache.spark.storage.BlockData
Returns a Netty-friendly wrapper for the block's data.
toNetty() - Method in class org.apache.spark.storage.DiskBlockData
Returns a Netty-friendly wrapper for the block's data.
toNumber(String, Function1<String, T>, String, String) - Static method in class org.apache.spark.internal.config.ConfigHelpers
 
toOld() - Method in interface org.apache.spark.ml.tree.DecisionTreeModel
Convert to spark.mllib DecisionTreeModel (losing some information)
toOld() - Method in interface org.apache.spark.ml.tree.Split
Convert to old Split format
tooltip(String, String) - Static method in class org.apache.spark.ui.UIUtils
 
ToolTips - Class in org.apache.spark.ui
 
ToolTips() - Constructor for class org.apache.spark.ui.ToolTips
 
toOps(T, ClassTag<VD>) - Method in interface org.apache.spark.graphx.impl.VertexPartitionBaseOpsConstructor
 
top(int, Comparator<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Returns the top k (largest) elements from this RDD as defined by the specified Comparator[T] and maintains the order.
top(int) - Method in interface org.apache.spark.api.java.JavaRDDLike
Returns the top k (largest) elements from this RDD using the natural ordering for T and maintains the order.
top(int, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
Returns the top k (largest) elements from this RDD as defined by the specified implicit Ordering[T] and maintains the ordering.
toPairDStreamFunctions(DStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>, Ordering<K>) - Static method in class org.apache.spark.streaming.dstream.DStream
 
topByKey(int, Ordering<V>) - Method in class org.apache.spark.mllib.rdd.MLPairRDDFunctions
Returns the top k (largest) elements for each key from this RDD as defined by the specified implicit Ordering[T].
topDocumentsPerTopic(int) - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
Return the top documents for each topic
topicAssignments() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
Return the top topic for each (doc, term) pair.
topicConcentration() - Method in interface org.apache.spark.ml.clustering.LDAParams
Concentration parameter (commonly named "beta" or "eta") for the prior placed on topics' distributions over terms.
topicConcentration() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
 
topicConcentration() - Method in class org.apache.spark.mllib.clustering.LDAModel
Concentration parameter (commonly named "beta" or "eta") for the prior placed on topics' distributions over terms.
topicConcentration() - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
 
topicDistribution(Vector) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
Predicts the topic mixture distribution for a document (often called "theta" in the literature).
topicDistributionCol() - Method in interface org.apache.spark.ml.clustering.LDAParams
Output column with estimates of the topic mixture distribution for each document (often called "theta" in the literature).
topicDistributions() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
For each document in the training set, return the distribution over topics for that document ("theta_doc").
topicDistributions(RDD<Tuple2<Object, Vector>>) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
Predicts the topic mixture distribution for each document (often called "theta" in the literature).
topicDistributions(JavaPairRDD<Long, Vector>) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
Java-friendly version of topicDistributions
topics() - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
 
topicsMatrix() - Method in class org.apache.spark.ml.clustering.LDAModel
Inferred topics, where each topic is represented by a distribution over terms.
topicsMatrix() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
Inferred topics, where each topic is represented by a distribution over terms.
topicsMatrix() - Method in class org.apache.spark.mllib.clustering.LDAModel
Inferred topics, where each topic is represented by a distribution over terms.
topicsMatrix() - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
 
topK(Iterator<Tuple2<String, Object>>, int) - Static method in class org.apache.spark.streaming.util.RawTextHelper
Gets the top k words in terms of word counts.
toPMML(StreamResult) - Method in interface org.apache.spark.mllib.pmml.PMMLExportable
Export the model to the stream result in PMML format
toPMML(String) - Method in interface org.apache.spark.mllib.pmml.PMMLExportable
Export the model to a local file in PMML format
toPMML(SparkContext, String) - Method in interface org.apache.spark.mllib.pmml.PMMLExportable
Export the model to a directory on a distributed file system in PMML format
toPMML(OutputStream) - Method in interface org.apache.spark.mllib.pmml.PMMLExportable
Export the model to the OutputStream in PMML format
toPMML() - Method in interface org.apache.spark.mllib.pmml.PMMLExportable
Export the model to a String in PMML format
topNode() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
 
Topology - Interface in org.apache.spark.ml.ann
Trait for the artificial neural network (ANN) topology properties
topologyFile() - Method in class org.apache.spark.storage.FileBasedTopologyMapper
 
topologyInfo() - Method in class org.apache.spark.storage.BlockManagerId
 
topologyMap() - Method in class org.apache.spark.storage.FileBasedTopologyMapper
 
TopologyMapper - Class in org.apache.spark.storage
::DeveloperApi:: TopologyMapper provides topology information for a given host param: conf SparkConf to get required properties, if needed
TopologyMapper(SparkConf) - Constructor for class org.apache.spark.storage.TopologyMapper
 
TopologyModel - Interface in org.apache.spark.ml.ann
Trait for ANN topology model
toPredict() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData
 
topTopicsPerDocument(int) - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
For each document, return the top k weighted topics for that document and their weights.
toRadians(Column) - Static method in class org.apache.spark.sql.functions
Deprecated.
Use radians. Since 2.1.0.
toRadians(String) - Static method in class org.apache.spark.sql.functions
Deprecated.
Use radians. Since 2.1.0.
toRDD(JavaDoubleRDD) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
 
toRDD(JavaPairRDD<K, V>) - Static method in class org.apache.spark.api.java.JavaPairRDD
 
toRDD(JavaRDD<T>) - Static method in class org.apache.spark.api.java.JavaRDD
 
toRowMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
Converts to RowMatrix, dropping row indices after grouping by row index.
toRowMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
Drops row indices and converts this matrix to a RowMatrix.
toScalaBigInt() - Method in class org.apache.spark.sql.types.Decimal
 
toSeq() - Method in class org.apache.spark.ml.param.ParamMap
Converts this param map to a sequence of param pairs.
toSeq() - Method in interface org.apache.spark.sql.Row
Return a Scala Seq representing the row.
toShort() - Method in class org.apache.spark.sql.types.Decimal
 
toShortArray() - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
toSparkContext(JavaSparkContext) - Static method in class org.apache.spark.api.java.JavaSparkContext
 
toSparse() - Method in interface org.apache.spark.ml.linalg.Matrix
Converts this matrix to a sparse matrix while maintaining the layout of the current matrix.
toSparse() - Method in interface org.apache.spark.ml.linalg.Vector
Converts this vector to a sparse vector with all explicit zeros removed.
toSparse() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
Generate a SparseMatrix from the given DenseMatrix.
toSparse() - Method in interface org.apache.spark.mllib.linalg.Vector
Converts this vector to a sparse vector with all explicit zeros removed.
toSparseColMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
Converts this matrix to a sparse matrix in column major order.
toSparseMatrix(boolean) - Method in interface org.apache.spark.ml.linalg.Matrix
Converts this matrix to a sparse matrix.
toSparseRowMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
Converts this matrix to a sparse matrix in row major order.
toSparseWithSize(int) - Method in interface org.apache.spark.ml.linalg.Vector
Converts this vector to a sparse vector with all explicit zeros removed when the size is known.
toSparseWithSize(int) - Method in interface org.apache.spark.mllib.linalg.Vector
Converts this vector to a sparse vector with all explicit zeros removed when the size is known.
toSplit() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData
 
toSplitInfo(Class<?>, String, InputSplit) - Static method in class org.apache.spark.scheduler.SplitInfo
 
toSplitInfo(Class<?>, String, InputSplit) - Static method in class org.apache.spark.scheduler.SplitInfo
 
toString() - Method in class org.apache.spark.Accumulable
Deprecated.
 
toString() - Method in class org.apache.spark.api.java.JavaRDD
 
toString() - Method in class org.apache.spark.api.java.Optional
 
toString() - Method in class org.apache.spark.broadcast.Broadcast
 
toString() - Static method in class org.apache.spark.CleanAccum
 
toString() - Static method in class org.apache.spark.CleanBroadcast
 
toString() - Static method in class org.apache.spark.CleanCheckpoint
 
toString() - Static method in class org.apache.spark.CleanRDD
 
toString() - Static method in class org.apache.spark.CleanShuffle
 
toString() - Method in class org.apache.spark.ContextBarrierId
 
toString() - Static method in class org.apache.spark.ExceptionFailure
 
toString() - Static method in class org.apache.spark.ExecutorLostFailure
 
toString() - Static method in class org.apache.spark.ExecutorRegistered
 
toString() - Static method in class org.apache.spark.ExecutorRemoved
 
toString() - Static method in class org.apache.spark.FetchFailed
 
toString() - Method in class org.apache.spark.graphx.EdgeDirection
 
toString() - Method in class org.apache.spark.graphx.EdgeTriplet
 
toString() - Method in class org.apache.spark.ml.attribute.Attribute
 
toString() - Method in class org.apache.spark.ml.attribute.AttributeGroup
 
toString() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
toString() - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
 
toString() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
 
toString() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
 
toString() - Method in class org.apache.spark.ml.classification.NaiveBayesModel
 
toString() - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
 
toString() - Static method in class org.apache.spark.ml.clustering.ClusterData
 
toString() - Method in class org.apache.spark.ml.feature.LabeledPoint
 
toString() - Method in class org.apache.spark.ml.feature.RFormula
 
toString() - Method in class org.apache.spark.ml.feature.RFormulaModel
 
toString() - Method in class org.apache.spark.ml.linalg.DenseVector
 
toString() - Method in interface org.apache.spark.ml.linalg.Matrix
A human readable representation of the matrix
toString(int, int) - Method in interface org.apache.spark.ml.linalg.Matrix
A human readable representation of the matrix with maximum lines and width
toString() - Method in class org.apache.spark.ml.linalg.SparseVector
 
toString() - Method in class org.apache.spark.ml.param.Param
 
toString() - Method in class org.apache.spark.ml.param.ParamMap
 
toString() - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
 
toString() - Method in class org.apache.spark.ml.regression.GBTRegressionModel
 
toString() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionTrainingSummary
 
toString() - Method in class org.apache.spark.ml.regression.RandomForestRegressionModel
 
toString() - Method in interface org.apache.spark.ml.tree.DecisionTreeModel
Summary of the model
toString() - Method in class org.apache.spark.ml.tree.InternalNode
 
toString() - Method in class org.apache.spark.ml.tree.LeafNode
 
toString() - Method in interface org.apache.spark.ml.tree.TreeEnsembleModel
Summary of the model
toString() - Method in interface org.apache.spark.ml.util.Identifiable
 
toString() - Static method in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$.Data
 
toString() - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
 
toString() - Static method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$.Data
 
toString() - Static method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data
 
toString() - Method in class org.apache.spark.mllib.classification.SVMModel
 
toString() - Static method in class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$.Data
 
toString() - Static method in class org.apache.spark.mllib.feature.VocabWord
 
toString() - Method in class org.apache.spark.mllib.fpm.AssociationRules.Rule
 
toString() - Method in class org.apache.spark.mllib.fpm.FPGrowth.FreqItemset
 
toString() - Method in class org.apache.spark.mllib.linalg.DenseVector
 
toString() - Static method in class org.apache.spark.mllib.linalg.distributed.IndexedRow
 
toString() - Static method in class org.apache.spark.mllib.linalg.distributed.MatrixEntry
 
toString() - Method in interface org.apache.spark.mllib.linalg.Matrix
A human readable representation of the matrix
toString(int, int) - Method in interface org.apache.spark.mllib.linalg.Matrix
A human readable representation of the matrix with maximum lines and width
toString() - Method in class org.apache.spark.mllib.linalg.SparseVector
 
toString() - Static method in class org.apache.spark.mllib.recommendation.Rating
 
toString() - Method in class org.apache.spark.mllib.regression.GeneralizedLinearModel
Print a summary of the model.
toString() - Static method in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$.Data
 
toString() - Method in class org.apache.spark.mllib.regression.LabeledPoint
 
toString() - Method in class org.apache.spark.mllib.stat.test.BinarySample
 
toString() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
 
toString() - Method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTestResult
 
toString() - Method in interface org.apache.spark.mllib.stat.test.TestResult
String explaining the hypothesis test result.
toString() - Static method in class org.apache.spark.mllib.tree.configuration.Algo
 
toString() - Static method in class org.apache.spark.mllib.tree.configuration.EnsembleCombiningStrategy
 
toString() - Static method in class org.apache.spark.mllib.tree.configuration.FeatureType
 
toString() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
 
toString() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
Print a summary of the model.
toString() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
 
toString() - Method in class org.apache.spark.mllib.tree.model.Node
 
toString() - Method in class org.apache.spark.mllib.tree.model.Predict
 
toString() - Method in class org.apache.spark.mllib.tree.model.Split
 
toString() - Method in class org.apache.spark.partial.BoundedDouble
 
toString() - Method in class org.apache.spark.partial.PartialResult
 
toString() - Static method in class org.apache.spark.rdd.CheckpointState
 
toString() - Static method in class org.apache.spark.rdd.DeterministicLevel
 
toString() - Method in class org.apache.spark.rdd.RDD
 
toString() - Static method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
 
toString() - Static method in class org.apache.spark.scheduler.BlacklistedExecutor
 
toString() - Static method in class org.apache.spark.scheduler.ExecutorKilled
 
toString() - Method in class org.apache.spark.scheduler.InputFormatInfo
 
toString() - Static method in class org.apache.spark.scheduler.local.KillTask
 
toString() - Static method in class org.apache.spark.scheduler.local.ReviveOffers
 
toString() - Static method in class org.apache.spark.scheduler.local.StatusUpdate
 
toString() - Static method in class org.apache.spark.scheduler.local.StopExecutor
 
toString() - Static method in class org.apache.spark.scheduler.LossReasonPending
 
toString() - Static method in class org.apache.spark.scheduler.SchedulingMode
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerApplicationEnd
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerApplicationStart
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerRemoved
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerBlockUpdated
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerEnvironmentUpdate
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorAdded
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklisted
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklistedForStage
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorRemoved
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorUnblacklisted
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerJobEnd
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerJobStart
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerLogStart
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerNodeBlacklisted
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerNodeBlacklistedForStage
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerNodeUnblacklisted
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerSpeculativeTaskSubmitted
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerStageCompleted
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerStageSubmitted
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerTaskEnd
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerTaskGettingResult
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerTaskStart
 
toString() - Static method in class org.apache.spark.scheduler.SparkListenerUnpersistRDD
 
toString() - Method in class org.apache.spark.scheduler.SplitInfo
 
toString() - Static method in class org.apache.spark.scheduler.TaskLocality
 
toString() - Method in class org.apache.spark.SerializableWritable
 
toString() - Method in class org.apache.spark.sql.catalog.Column
 
toString() - Method in class org.apache.spark.sql.catalog.Database
 
toString() - Method in class org.apache.spark.sql.catalog.Function
 
toString() - Method in class org.apache.spark.sql.catalog.Table
 
toString() - Method in class org.apache.spark.sql.Column
 
toString() - Method in class org.apache.spark.sql.Dataset
 
toString() - Static method in class org.apache.spark.sql.expressions.UserDefinedFunction
 
toString() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
 
toString() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
 
toString() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
 
toString() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
 
toString() - Static method in class org.apache.spark.sql.hive.HiveUDAFBuffer
 
toString() - Method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
toString() - Static method in class org.apache.spark.sql.hive.RelationConversions
 
toString() - Static method in class org.apache.spark.sql.jdbc.JdbcType
 
toString() - Method in class org.apache.spark.sql.KeyValueGroupedDataset
 
toString() - Method in interface org.apache.spark.sql.RelationalGroupedDataset.GroupType
 
toString() - Method in class org.apache.spark.sql.RelationalGroupedDataset
 
toString() - Method in interface org.apache.spark.sql.Row
 
toString() - Static method in class org.apache.spark.sql.sources.And
 
toString() - Static method in class org.apache.spark.sql.sources.EqualNullSafe
 
toString() - Static method in class org.apache.spark.sql.sources.EqualTo
 
toString() - Static method in class org.apache.spark.sql.sources.GreaterThan
 
toString() - Static method in class org.apache.spark.sql.sources.GreaterThanOrEqual
 
toString() - Method in class org.apache.spark.sql.sources.In
 
toString() - Static method in class org.apache.spark.sql.sources.IsNotNull
 
toString() - Static method in class org.apache.spark.sql.sources.IsNull
 
toString() - Static method in class org.apache.spark.sql.sources.LessThan
 
toString() - Static method in class org.apache.spark.sql.sources.LessThanOrEqual
 
toString() - Static method in class org.apache.spark.sql.sources.Not
 
toString() - Static method in class org.apache.spark.sql.sources.Or
 
toString() - Static method in class org.apache.spark.sql.sources.StringContains
 
toString() - Static method in class org.apache.spark.sql.sources.StringEndsWith
 
toString() - Static method in class org.apache.spark.sql.sources.StringStartsWith
 
toString() - Method in class org.apache.spark.sql.sources.v2.reader.streaming.Offset
 
toString() - Method in class org.apache.spark.sql.streaming.SinkProgress
 
toString() - Method in class org.apache.spark.sql.streaming.SourceProgress
 
toString() - Method in class org.apache.spark.sql.streaming.StateOperatorProgress
 
toString() - Method in exception org.apache.spark.sql.streaming.StreamingQueryException
 
toString() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
 
toString() - Method in class org.apache.spark.sql.streaming.StreamingQueryStatus
 
toString() - Static method in class org.apache.spark.sql.types.CharType
 
toString() - Method in class org.apache.spark.sql.types.Decimal
 
toString() - Method in class org.apache.spark.sql.types.DecimalType
 
toString() - Method in class org.apache.spark.sql.types.Metadata
 
toString() - Method in class org.apache.spark.sql.types.StructField
 
toString() - Static method in class org.apache.spark.sql.types.VarcharType
 
toString() - Static method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
 
toString() - Static method in class org.apache.spark.status.api.v1.ApplicationInfo
 
toString() - Method in class org.apache.spark.status.api.v1.StackTrace
 
toString() - Static method in class org.apache.spark.status.api.v1.ThreadStackTrace
 
toString() - Method in class org.apache.spark.storage.BlockId
 
toString() - Method in class org.apache.spark.storage.BlockManagerId
 
toString() - Static method in class org.apache.spark.storage.BroadcastBlockId
 
toString() - Static method in class org.apache.spark.storage.RDDBlockId
 
toString() - Method in class org.apache.spark.storage.RDDInfo
 
toString() - Static method in class org.apache.spark.storage.ShuffleBlockId
 
toString() - Static method in class org.apache.spark.storage.ShuffleDataBlockId
 
toString() - Static method in class org.apache.spark.storage.ShuffleIndexBlockId
 
toString() - Method in class org.apache.spark.storage.StorageLevel
 
toString() - Static method in class org.apache.spark.storage.StreamBlockId
 
toString() - Static method in class org.apache.spark.storage.TaskResultBlockId
 
toString() - Method in class org.apache.spark.streaming.Duration
 
toString() - Static method in class org.apache.spark.streaming.scheduler.BatchInfo
 
toString() - Static method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
 
toString() - Static method in class org.apache.spark.streaming.scheduler.ReceiverInfo
 
toString() - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
 
toString() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchCompleted
 
toString() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchStarted
 
toString() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchSubmitted
 
toString() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationCompleted
 
toString() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationStarted
 
toString() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverError
 
toString() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted
 
toString() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStopped
 
toString() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerStreamingStarted
 
toString() - Method in class org.apache.spark.streaming.State
 
toString() - Method in class org.apache.spark.streaming.Time
 
toString() - Static method in class org.apache.spark.TaskCommitDenied
 
toString() - Static method in class org.apache.spark.TaskKilled
 
toString() - Static method in class org.apache.spark.TaskState
 
toString() - Method in class org.apache.spark.util.AccumulatorV2
 
toString() - Method in class org.apache.spark.util.MutablePair
 
toString() - Method in class org.apache.spark.util.StatCounter
 
toStructField(Metadata) - Method in class org.apache.spark.ml.attribute.Attribute
Converts to a StructField with some existing metadata.
toStructField() - Method in class org.apache.spark.ml.attribute.Attribute
Converts to a StructField.
toStructField(Metadata) - Method in class org.apache.spark.ml.attribute.AttributeGroup
Converts to a StructField with some existing metadata.
toStructField() - Method in class org.apache.spark.ml.attribute.AttributeGroup
Converts to a StructField.
toStructField(Metadata) - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
toStructField() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
totalBlocksFetched() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
 
totalBytesRead(ShuffleReadMetrics) - Static method in class org.apache.spark.ui.jobs.ApiHelper
 
totalCores() - Method in class org.apache.spark.scheduler.cluster.ExecutorInfo
 
totalCores() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
totalCores() - Method in class org.apache.spark.status.LiveExecutor
 
totalCount() - Method in class org.apache.spark.util.sketch.CountMinSketch
Total count of items added to this CountMinSketch so far.
totalDelay() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
 
totalDelay() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
Time taken for all the jobs of this batch to finish processing from the time they were submitted.
totalDiskSize() - Method in class org.apache.spark.ui.storage.ExecutorStreamSummary
 
totalDuration() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
totalDuration() - Method in class org.apache.spark.status.LiveExecutor
 
totalGCTime() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
totalGcTime() - Method in class org.apache.spark.status.LiveExecutor
 
totalInputBytes() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
totalInputBytes() - Method in class org.apache.spark.status.LiveExecutor
 
totalIterations() - Method in interface org.apache.spark.ml.classification.LogisticRegressionTrainingSummary
Number of training iterations.
totalIterations() - Method in class org.apache.spark.ml.regression.LinearRegressionTrainingSummary
Number of training iterations until termination
totalMemSize() - Method in class org.apache.spark.ui.storage.ExecutorStreamSummary
 
totalNumNodes() - Method in interface org.apache.spark.ml.tree.TreeEnsembleModel
Total number of nodes, summed over all trees in the ensemble.
totalOffHeap() - Method in class org.apache.spark.status.LiveExecutor
 
totalOffHeapStorageMemory() - Method in interface org.apache.spark.SparkExecutorInfo
 
totalOffHeapStorageMemory() - Method in class org.apache.spark.SparkExecutorInfoImpl
 
totalOffHeapStorageMemory() - Method in class org.apache.spark.status.api.v1.MemoryMetrics
 
totalOnHeap() - Method in class org.apache.spark.status.LiveExecutor
 
totalOnHeapStorageMemory() - Method in interface org.apache.spark.SparkExecutorInfo
 
totalOnHeapStorageMemory() - Method in class org.apache.spark.SparkExecutorInfoImpl
 
totalOnHeapStorageMemory() - Method in class org.apache.spark.status.api.v1.MemoryMetrics
 
totalShuffleRead() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
totalShuffleRead() - Method in class org.apache.spark.status.LiveExecutor
 
totalShuffleWrite() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
totalShuffleWrite() - Method in class org.apache.spark.status.LiveExecutor
 
totalTasks() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
 
totalTasks() - Method in class org.apache.spark.status.LiveExecutor
 
toTuple() - Method in class org.apache.spark.graphx.EdgeTriplet
 
toTypeInfo() - Method in class org.apache.spark.sql.hive.HiveInspectors.typeInfoConversions
 
toUnscaledLong() - Method in class org.apache.spark.sql.types.Decimal
 
toVirtualHosts(Seq<String>) - Static method in class org.apache.spark.ui.JettyUtils
 
train(RDD<ALS.Rating<ID>>, int, int, int, int, double, boolean, double, boolean, StorageLevel, StorageLevel, int, long, ClassTag<ID>, Ordering<ID>) - Static method in class org.apache.spark.ml.recommendation.ALS
:: DeveloperApi :: Implementation of the ALS algorithm.
train(RDD<LabeledPoint>, int, double, double, Vector) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
Train a logistic regression model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int, double, double) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
Train a logistic regression model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int, double) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
Train a logistic regression model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
Train a logistic regression model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>) - Static method in class org.apache.spark.mllib.classification.NaiveBayes
Trains a Naive Bayes model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, double) - Static method in class org.apache.spark.mllib.classification.NaiveBayes
Trains a Naive Bayes model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, double, String) - Static method in class org.apache.spark.mllib.classification.NaiveBayes
Trains a Naive Bayes model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int, double, double, double, Vector) - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
Train a SVM model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int, double, double, double) - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
Train a SVM model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int, double, double) - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
Train a SVM model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int) - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
Train a SVM model given an RDD of (label, features) pairs.
train(RDD<Vector>, int, int, String, long) - Static method in class org.apache.spark.mllib.clustering.KMeans
Trains a k-means model using the given set of parameters.
train(RDD<Vector>, int, int, String) - Static method in class org.apache.spark.mllib.clustering.KMeans
Trains a k-means model using the given set of parameters.
train(RDD<Vector>, int, int, int, String, long) - Static method in class org.apache.spark.mllib.clustering.KMeans
Deprecated.
Use train method without 'runs'. Since 2.1.0.
train(RDD<Vector>, int, int, int, String) - Static method in class org.apache.spark.mllib.clustering.KMeans
Deprecated.
Use train method without 'runs'. Since 2.1.0.
train(RDD<Vector>, int, int) - Static method in class org.apache.spark.mllib.clustering.KMeans
Trains a k-means model using specified parameters and the default values for unspecified.
train(RDD<Vector>, int, int, int) - Static method in class org.apache.spark.mllib.clustering.KMeans
Deprecated.
Use train method without 'runs'. Since 2.1.0.
train(RDD<Rating>, int, int, double, int, long) - Static method in class org.apache.spark.mllib.recommendation.ALS
Train a matrix factorization model given an RDD of ratings by users for a subset of products.
train(RDD<Rating>, int, int, double, int) - Static method in class org.apache.spark.mllib.recommendation.ALS
Train a matrix factorization model given an RDD of ratings by users for a subset of products.
train(RDD<Rating>, int, int, double) - Static method in class org.apache.spark.mllib.recommendation.ALS
Train a matrix factorization model given an RDD of ratings by users for a subset of products.
train(RDD<Rating>, int, int) - Static method in class org.apache.spark.mllib.recommendation.ALS
Train a matrix factorization model given an RDD of ratings by users for a subset of products.
train(RDD<LabeledPoint>, int, double, double, double, Vector) - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
Train a Lasso model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int, double, double, double) - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
Train a Lasso model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int, double, double) - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
Train a Lasso model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int) - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
Train a Lasso model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int, double, double, Vector) - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
Train a Linear Regression model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int, double, double) - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
Train a LinearRegression model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int, double) - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
Train a LinearRegression model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int) - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
Train a LinearRegression model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int, double, double, double, Vector) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
Train a RidgeRegression model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int, double, double, double) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
Train a RidgeRegression model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int, double, double) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
Train a RidgeRegression model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, int) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
Train a RidgeRegression model given an RDD of (label, features) pairs.
train(RDD<LabeledPoint>, Strategy) - Static method in class org.apache.spark.mllib.tree.DecisionTree
Method to train a decision tree model.
train(RDD<LabeledPoint>, Enumeration.Value, Impurity, int) - Static method in class org.apache.spark.mllib.tree.DecisionTree
Method to train a decision tree model.
train(RDD<LabeledPoint>, Enumeration.Value, Impurity, int, int) - Static method in class org.apache.spark.mllib.tree.DecisionTree
Method to train a decision tree model.
train(RDD<LabeledPoint>, Enumeration.Value, Impurity, int, int, int, Enumeration.Value, Map<Object, Object>) - Static method in class org.apache.spark.mllib.tree.DecisionTree
Method to train a decision tree model.
train(RDD<LabeledPoint>, BoostingStrategy) - Static method in class org.apache.spark.mllib.tree.GradientBoostedTrees
Method to train a gradient boosting model.
train(JavaRDD<LabeledPoint>, BoostingStrategy) - Static method in class org.apache.spark.mllib.tree.GradientBoostedTrees
Java-friendly API for org.apache.spark.mllib.tree.GradientBoostedTrees.train
trainClassifier(RDD<LabeledPoint>, int, Map<Object, Object>, String, int, int) - Static method in class org.apache.spark.mllib.tree.DecisionTree
Method to train a decision tree model for binary or multiclass classification.
trainClassifier(JavaRDD<LabeledPoint>, int, Map<Integer, Integer>, String, int, int) - Static method in class org.apache.spark.mllib.tree.DecisionTree
Java-friendly API for org.apache.spark.mllib.tree.DecisionTree.trainClassifier
trainClassifier(RDD<LabeledPoint>, Strategy, int, String, int) - Static method in class org.apache.spark.mllib.tree.RandomForest
Method to train a decision tree model for binary or multiclass classification.
trainClassifier(RDD<LabeledPoint>, int, Map<Object, Object>, int, String, String, int, int, int) - Static method in class org.apache.spark.mllib.tree.RandomForest
Method to train a decision tree model for binary or multiclass classification.
trainClassifier(JavaRDD<LabeledPoint>, int, Map<Integer, Integer>, int, String, String, int, int, int) - Static method in class org.apache.spark.mllib.tree.RandomForest
Java-friendly API for org.apache.spark.mllib.tree.RandomForest.trainClassifier
trainImplicit(RDD<Rating>, int, int, double, int, double, long) - Static method in class org.apache.spark.mllib.recommendation.ALS
Train a matrix factorization model given an RDD of 'implicit preferences' given by users to some products, in the form of (userID, productID, preference) pairs.
trainImplicit(RDD<Rating>, int, int, double, int, double) - Static method in class org.apache.spark.mllib.recommendation.ALS
Train a matrix factorization model given an RDD of 'implicit preferences' of users for a subset of products.
trainImplicit(RDD<Rating>, int, int, double, double) - Static method in class org.apache.spark.mllib.recommendation.ALS
Train a matrix factorization model given an RDD of 'implicit preferences' of users for a subset of products.
trainImplicit(RDD<Rating>, int, int) - Static method in class org.apache.spark.mllib.recommendation.ALS
Train a matrix factorization model given an RDD of 'implicit preferences' of users for a subset of products.
trainingCost() - Method in class org.apache.spark.ml.clustering.KMeansSummary
 
trainingCost() - Method in class org.apache.spark.mllib.clustering.KMeansModel
 
trainingLogLikelihood() - Method in class org.apache.spark.ml.clustering.DistributedLDAModel
Log likelihood of the observed tokens in the training set, given the current parameter estimates: log P(docs | topics, topic distributions for docs, Dirichlet hyperparameters)
trainOn(DStream<Vector>) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
Update the clustering model by training on batches of data from a DStream.
trainOn(JavaDStream<Vector>) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
Java-friendly version of trainOn.
trainOn(DStream<LabeledPoint>) - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
Update the model by training on batches of data from a DStream.
trainOn(JavaDStream<LabeledPoint>) - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
Java-friendly version of trainOn.
trainRatio() - Method in interface org.apache.spark.ml.tuning.TrainValidationSplitParams
Param for ratio between train and validation data.
trainRegressor(RDD<LabeledPoint>, Map<Object, Object>, String, int, int) - Static method in class org.apache.spark.mllib.tree.DecisionTree
Method to train a decision tree model for regression.
trainRegressor(JavaRDD<LabeledPoint>, Map<Integer, Integer>, String, int, int) - Static method in class org.apache.spark.mllib.tree.DecisionTree
Java-friendly API for org.apache.spark.mllib.tree.DecisionTree.trainRegressor
trainRegressor(RDD<LabeledPoint>, Strategy, int, String, int) - Static method in class org.apache.spark.mllib.tree.RandomForest
Method to train a decision tree model for regression.
trainRegressor(RDD<LabeledPoint>, Map<Object, Object>, int, String, String, int, int, int) - Static method in class org.apache.spark.mllib.tree.RandomForest
Method to train a decision tree model for regression.
trainRegressor(JavaRDD<LabeledPoint>, Map<Integer, Integer>, int, String, String, int, int, int) - Static method in class org.apache.spark.mllib.tree.RandomForest
Java-friendly API for org.apache.spark.mllib.tree.RandomForest.trainRegressor
TrainValidationSplit - Class in org.apache.spark.ml.tuning
Validation for hyper-parameter tuning.
TrainValidationSplit(String) - Constructor for class org.apache.spark.ml.tuning.TrainValidationSplit
 
TrainValidationSplit() - Constructor for class org.apache.spark.ml.tuning.TrainValidationSplit
 
TrainValidationSplitModel - Class in org.apache.spark.ml.tuning
Model from train validation split.
TrainValidationSplitModel.TrainValidationSplitModelWriter - Class in org.apache.spark.ml.tuning
Writer for TrainValidationSplitModel.
TrainValidationSplitParams - Interface in org.apache.spark.ml.tuning
transferred() - Method in class org.apache.spark.storage.ReadableChannelFileRegion
 
transferTo(WritableByteChannel, long) - Method in class org.apache.spark.storage.ReadableChannelFileRegion
 
transform(Function1<Try<T>, Try<S>>, ExecutionContext) - Method in class org.apache.spark.ComplexFutureAction
 
transform(Function1<Try<T>, Try<S>>, ExecutionContext) - Method in interface org.apache.spark.FutureAction
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.classification.ClassificationModel
Transforms dataset by reading from featuresCol, and appending new columns as specified by parameters: - predicted labels as predictionCol of type Double - raw predictions (confidences) as rawPredictionCol of type Vector.
transform(Dataset<?>) - Method in class org.apache.spark.ml.classification.OneVsRestModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
Transforms dataset by reading from featuresCol, and appending new columns as specified by parameters: - predicted labels as predictionCol of type Double - raw predictions (confidences) as rawPredictionCol of type Vector - probability of each class as probabilityCol of type Vector.
transform(Dataset<?>) - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.clustering.KMeansModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.clustering.LDAModel
Transforms the input dataset.
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.Binarizer
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.Bucketizer
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.ChiSqSelectorModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.ColumnPruner
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.CountVectorizerModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.FeatureHasher
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.HashingTF
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.IDFModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.ImputerModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.IndexToString
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.Interaction
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.MaxAbsScalerModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.OneHotEncoder
Deprecated.
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.OneHotEncoderModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.PCAModel
Transform a vector by computed Principal Components.
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.RFormulaModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.SQLTransformer
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.StandardScalerModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.StopWordsRemover
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.StringIndexerModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.VectorAssembler
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.VectorAttributeRewriter
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.VectorIndexerModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.VectorSizeHint
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.VectorSlicer
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.feature.Word2VecModel
Transform a sentence column to a vector column to represent the whole sentence.
transform(Dataset<?>) - Method in class org.apache.spark.ml.fpm.FPGrowthModel
The transform method first generates the association rules according to the frequent itemsets.
transform(Dataset<?>) - Method in class org.apache.spark.ml.PipelineModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.PredictionModel
Transforms dataset by reading from featuresCol, calling predict, and storing the predictions as a new column predictionCol.
transform(Dataset<?>) - Method in class org.apache.spark.ml.recommendation.ALSModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
 
transform(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Method in class org.apache.spark.ml.Transformer
Transforms the dataset with optional parameters
transform(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Method in class org.apache.spark.ml.Transformer
Transforms the dataset with optional parameters
transform(Dataset<?>, ParamMap) - Method in class org.apache.spark.ml.Transformer
Transforms the dataset with provided parameter map as additional parameters.
transform(Dataset<?>) - Method in class org.apache.spark.ml.Transformer
Transforms the input dataset.
transform(Dataset<?>) - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
 
transform(Dataset<?>) - Method in class org.apache.spark.ml.UnaryTransformer
 
transform(Vector) - Method in class org.apache.spark.mllib.feature.ChiSqSelectorModel
Applies transformation on a vector.
transform(Vector) - Method in class org.apache.spark.mllib.feature.ElementwiseProduct
Does the hadamard product transformation.
transform(Iterable<?>) - Method in class org.apache.spark.mllib.feature.HashingTF
Transforms the input document into a sparse term frequency vector.
transform(Iterable<?>) - Method in class org.apache.spark.mllib.feature.HashingTF
Transforms the input document into a sparse term frequency vector (Java version).
transform(RDD<D>) - Method in class org.apache.spark.mllib.feature.HashingTF
Transforms the input document to term frequency vectors.
transform(JavaRDD<D>) - Method in class org.apache.spark.mllib.feature.HashingTF
Transforms the input document to term frequency vectors (Java version).
transform(RDD<Vector>) - Method in class org.apache.spark.mllib.feature.IDFModel
Transforms term frequency (TF) vectors to TF-IDF vectors.
transform(Vector) - Method in class org.apache.spark.mllib.feature.IDFModel
Transforms a term frequency (TF) vector to a TF-IDF vector
transform(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.feature.IDFModel
Transforms term frequency (TF) vectors to TF-IDF vectors (Java version).
transform(Vector) - Method in class org.apache.spark.mllib.feature.Normalizer
Applies unit length normalization on a vector.
transform(Vector) - Method in class org.apache.spark.mllib.feature.PCAModel
Transform a vector by computed Principal Components.
transform(Vector) - Method in class org.apache.spark.mllib.feature.StandardScalerModel
Applies standardization transformation on a vector.
transform(Vector) - Method in interface org.apache.spark.mllib.feature.VectorTransformer
Applies transformation on a vector.
transform(RDD<Vector>) - Method in interface org.apache.spark.mllib.feature.VectorTransformer
Applies transformation on an RDD[Vector].
transform(JavaRDD<Vector>) - Method in interface org.apache.spark.mllib.feature.VectorTransformer
Applies transformation on a JavaRDD[Vector].
transform(String) - Method in class org.apache.spark.mllib.feature.Word2VecModel
Transforms a word to its vector representation
transform(Function1<Try<T>, Try<S>>, ExecutionContext) - Method in class org.apache.spark.SimpleFutureAction
 
transform(Function1<Dataset<T>, Dataset<U>>) - Method in class org.apache.spark.sql.Dataset
Concise syntax for chaining custom transformations.
transform(Function<R, JavaRDD<U>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream.
transform(Function2<R, Time, JavaRDD<U>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream.
transform(List<JavaDStream<?>>, Function2<List<JavaRDD<?>>, Time, JavaRDD<T>>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create a new DStream in which each RDD is generated by applying a function on RDDs of the DStreams.
transform(Function1<RDD<T>, RDD<U>>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream.
transform(Function2<RDD<T>, Time, RDD<U>>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream.
transform(Seq<DStream<?>>, Function2<Seq<RDD<?>>, Time, RDD<T>>, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
Create a new DStream in which each RDD is generated by applying a function on RDDs of the DStreams.
Transformer - Class in org.apache.spark.ml
:: DeveloperApi :: Abstract class for transformers that transform one dataset into another.
Transformer() - Constructor for class org.apache.spark.ml.Transformer
 
transformOutputColumnSchema(StructField, String, boolean, boolean) - Static method in class org.apache.spark.ml.feature.OneHotEncoderCommon
Prepares the StructField with proper metadata for OneHotEncoder's output column.
transformSchema(StructType) - Method in class org.apache.spark.ml.classification.OneVsRest
 
transformSchema(StructType) - Method in class org.apache.spark.ml.classification.OneVsRestModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
 
transformSchema(StructType) - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.clustering.GaussianMixture
 
transformSchema(StructType) - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.clustering.KMeans
 
transformSchema(StructType) - Method in class org.apache.spark.ml.clustering.KMeansModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.clustering.LDA
 
transformSchema(StructType) - Method in class org.apache.spark.ml.clustering.LDAModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.Binarizer
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.Bucketizer
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.ChiSqSelector
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.ChiSqSelectorModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.ColumnPruner
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.CountVectorizer
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.CountVectorizerModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.FeatureHasher
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.HashingTF
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.IDF
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.IDFModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.Imputer
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.ImputerModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.IndexToString
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.Interaction
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.MaxAbsScaler
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.MaxAbsScalerModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.MinHashLSH
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.MinMaxScaler
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.OneHotEncoder
Deprecated.
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.OneHotEncoderModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.PCA
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.PCAModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.RFormula
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.RFormulaModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.SQLTransformer
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.StandardScaler
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.StandardScalerModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.StopWordsRemover
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.StringIndexer
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.StringIndexerModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.VectorAssembler
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.VectorAttributeRewriter
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.VectorIndexer
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.VectorIndexerModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.VectorSizeHint
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.VectorSlicer
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.Word2Vec
 
transformSchema(StructType) - Method in class org.apache.spark.ml.feature.Word2VecModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.fpm.FPGrowth
 
transformSchema(StructType) - Method in class org.apache.spark.ml.fpm.FPGrowthModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.Pipeline
 
transformSchema(StructType) - Method in class org.apache.spark.ml.PipelineModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.PipelineStage
:: DeveloperApi ::
transformSchema(StructType) - Method in class org.apache.spark.ml.PredictionModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.Predictor
 
transformSchema(StructType) - Method in class org.apache.spark.ml.recommendation.ALS
 
transformSchema(StructType) - Method in class org.apache.spark.ml.recommendation.ALSModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
 
transformSchema(StructType) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.regression.IsotonicRegression
 
transformSchema(StructType) - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.tuning.CrossValidator
 
transformSchema(StructType) - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
 
transformSchema(StructType) - Method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
 
transformSchema(StructType) - Method in class org.apache.spark.ml.UnaryTransformer
 
transformSchemaImpl(StructType) - Method in interface org.apache.spark.ml.tuning.ValidatorParams
 
transformToPair(Function<R, JavaPairRDD<K2, V2>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream.
transformToPair(Function2<R, Time, JavaPairRDD<K2, V2>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream.
transformToPair(List<JavaDStream<?>>, Function2<List<JavaRDD<?>>, Time, JavaPairRDD<K, V>>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create a new DStream in which each RDD is generated by applying a function on RDDs of the DStreams.
transformWith(Function1<Try<T>, Future<S>>, ExecutionContext) - Method in class org.apache.spark.ComplexFutureAction
 
transformWith(Function1<Try<T>, Future<S>>, ExecutionContext) - Method in interface org.apache.spark.FutureAction
 
transformWith(Function1<Try<T>, Future<S>>, ExecutionContext) - Method in class org.apache.spark.SimpleFutureAction
 
transformWith(JavaDStream<U>, Function3<R, JavaRDD<U>, Time, JavaRDD<W>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream and 'other' DStream.
transformWith(JavaPairDStream<K2, V2>, Function3<R, JavaPairRDD<K2, V2>, Time, JavaRDD<W>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream and 'other' DStream.
transformWith(DStream<U>, Function2<RDD<T>, RDD<U>, RDD<V>>, ClassTag<U>, ClassTag<V>) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream and 'other' DStream.
transformWith(DStream<U>, Function3<RDD<T>, RDD<U>, Time, RDD<V>>, ClassTag<U>, ClassTag<V>) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream and 'other' DStream.
transformWithToPair(JavaDStream<U>, Function3<R, JavaRDD<U>, Time, JavaPairRDD<K2, V2>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream and 'other' DStream.
transformWithToPair(JavaPairDStream<K2, V2>, Function3<R, JavaPairRDD<K2, V2>, Time, JavaPairRDD<K3, V3>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream and 'other' DStream.
translate(Column, String, String) - Static method in class org.apache.spark.sql.functions
Translate any character in the src by a character in replaceString.
transpose() - Method in class org.apache.spark.ml.linalg.DenseMatrix
 
transpose() - Method in interface org.apache.spark.ml.linalg.Matrix
Transpose the Matrix.
transpose() - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
transpose() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
 
transpose() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
Transpose this BlockMatrix.
transpose() - Method in class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
Transposes this CoordinateMatrix.
transpose() - Method in interface org.apache.spark.mllib.linalg.Matrix
Transpose the Matrix.
transpose() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
treeAggregate(U, Function2<U, T, U>, Function2<U, U, U>, int) - Method in interface org.apache.spark.api.java.JavaRDDLike
Aggregates the elements of this RDD in a multi-level tree pattern.
treeAggregate(U, Function2<U, T, U>, Function2<U, U, U>) - Method in interface org.apache.spark.api.java.JavaRDDLike
org.apache.spark.api.java.JavaRDDLike.treeAggregate with suggested depth 2.
treeAggregate(U, Function2<U, T, U>, Function2<U, U, U>, int, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
Aggregates the elements of this RDD in a multi-level tree pattern.
TreeClassifierParams - Interface in org.apache.spark.ml.tree
Parameters for Decision Tree-based classification algorithms.
TreeEnsembleModel<M extends DecisionTreeModel> - Interface in org.apache.spark.ml.tree
Abstraction for models which are ensembles of decision trees
TreeEnsembleParams - Interface in org.apache.spark.ml.tree
Parameters for Decision Tree-based ensemble algorithms.
treeID() - Method in class org.apache.spark.ml.tree.EnsembleModelReadWrite.EnsembleNodeData
 
treeId() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
 
treeReduce(Function2<T, T, T>, int) - Method in interface org.apache.spark.api.java.JavaRDDLike
Reduces the elements of this RDD in a multi-level tree pattern.
treeReduce(Function2<T, T, T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
org.apache.spark.api.java.JavaRDDLike.treeReduce with suggested depth 2.
treeReduce(Function2<T, T, T>, int) - Method in class org.apache.spark.rdd.RDD
Reduces the elements of this RDD in a multi-level tree pattern.
TreeRegressorParams - Interface in org.apache.spark.ml.tree
Parameters for Decision Tree-based regression algorithms.
trees() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
 
trees() - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
 
trees() - Method in class org.apache.spark.ml.regression.GBTRegressionModel
 
trees() - Method in class org.apache.spark.ml.regression.RandomForestRegressionModel
 
trees() - Method in interface org.apache.spark.ml.tree.TreeEnsembleModel
Trees in this ensemble.
trees() - Method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
 
trees() - Method in class org.apache.spark.mllib.tree.model.RandomForestModel
 
treeStrategy() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
treeString() - Method in class org.apache.spark.sql.types.StructType
 
treeWeights() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
 
treeWeights() - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
 
treeWeights() - Method in class org.apache.spark.ml.regression.GBTRegressionModel
 
treeWeights() - Method in class org.apache.spark.ml.regression.RandomForestRegressionModel
 
treeWeights() - Method in interface org.apache.spark.ml.tree.TreeEnsembleModel
Weights for each tree, zippable with trees
treeWeights() - Method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
 
triangleCount() - Method in class org.apache.spark.graphx.GraphOps
Compute the number of triangles passing through each vertex.
TriangleCount - Class in org.apache.spark.graphx.lib
Compute the number of triangles passing through each vertex.
TriangleCount() - Constructor for class org.apache.spark.graphx.lib.TriangleCount
 
trigger(Trigger) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
Set the trigger for the stream query.
Trigger - Class in org.apache.spark.sql.streaming
Policy used to indicate how often results should be produced by a [[StreamingQuery]].
Trigger() - Constructor for class org.apache.spark.sql.streaming.Trigger
 
TriggerThreadDump$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.TriggerThreadDump$
 
trim(Column) - Static method in class org.apache.spark.sql.functions
Trim the spaces from both ends for the specified string column.
trim(Column, String) - Static method in class org.apache.spark.sql.functions
Trim the specified character from both ends for the specified string column.
TrimHorizon() - Constructor for class org.apache.spark.streaming.kinesis.KinesisInitialPositions.TrimHorizon
 
TripletFields - Class in org.apache.spark.graphx
Represents a subset of the fields of an [[EdgeTriplet]] or [[EdgeContext]].
TripletFields() - Constructor for class org.apache.spark.graphx.TripletFields
Constructs a default TripletFields in which all fields are included.
TripletFields(boolean, boolean, boolean) - Constructor for class org.apache.spark.graphx.TripletFields
 
triplets() - Method in class org.apache.spark.graphx.Graph
An RDD containing the edge triplets, which are edges along with the vertex data associated with the adjacent vertices.
triplets() - Method in class org.apache.spark.graphx.impl.GraphImpl
Return an RDD that brings edges together with their source and destination vertices.
truePositiveRate(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns true positive rate for a given label (category)
truePositiveRateByLabel() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns true positive rate for each label (category).
trunc(Column, String) - Static method in class org.apache.spark.sql.functions
Returns date truncated to the unit specified by the format.
truncatedString(Seq<T>, String, String, String, int) - Static method in class org.apache.spark.util.Utils
Format a sequence with semantics similar to calling .mkString().
truncatedString(Seq<T>, String) - Static method in class org.apache.spark.util.Utils
Shorthand for calling truncatedString() without start or end strings.
tryLog(Function0<T>) - Static method in class org.apache.spark.util.Utils
Executes the given block in a Try, logging any uncaught exceptions.
tryLogNonFatalError(Function0<BoxedUnit>) - Static method in class org.apache.spark.util.Utils
Executes the given block.
tryOrExit(Function0<BoxedUnit>) - Static method in class org.apache.spark.util.Utils
Execute a block of code that evaluates to Unit, forwarding any uncaught exceptions to the default UncaughtExceptionHandler
tryOrIOException(Function0<T>) - Static method in class org.apache.spark.util.Utils
Execute a block of code that returns a value, re-throwing any non-fatal uncaught exceptions as IOException.
tryOrStopSparkContext(SparkContext, Function0<BoxedUnit>) - Static method in class org.apache.spark.util.Utils
Execute a block of code that evaluates to Unit, stop SparkContext if there is any uncaught exception
tryRecoverFromCheckpoint(String) - Method in class org.apache.spark.streaming.StreamingContextPythonHelper
This is a private method only for Python to implement getOrCreate.
tryWithResource(Function0<R>, Function1<R, T>) - Static method in class org.apache.spark.util.Utils
 
tryWithSafeFinally(Function0<T>, Function0<BoxedUnit>) - Static method in class org.apache.spark.util.Utils
Execute a block of code, then a finally block, but if exceptions happen in the finally block, do not suppress the original exception.
tryWithSafeFinallyAndFailureCallbacks(Function0<T>, Function0<BoxedUnit>, Function0<BoxedUnit>) - Static method in class org.apache.spark.util.Utils
Execute a block of code and call the failure callbacks in the catch block.
tuple(Encoder<T1>, Encoder<T2>) - Static method in class org.apache.spark.sql.Encoders
An encoder for 2-ary tuples.
tuple(Encoder<T1>, Encoder<T2>, Encoder<T3>) - Static method in class org.apache.spark.sql.Encoders
An encoder for 3-ary tuples.
tuple(Encoder<T1>, Encoder<T2>, Encoder<T3>, Encoder<T4>) - Static method in class org.apache.spark.sql.Encoders
An encoder for 4-ary tuples.
tuple(Encoder<T1>, Encoder<T2>, Encoder<T3>, Encoder<T4>, Encoder<T5>) - Static method in class org.apache.spark.sql.Encoders
An encoder for 5-ary tuples.
tValues() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionTrainingSummary
T-statistic of estimated coefficients and intercept.
tValues() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
T-statistic of estimated coefficients and intercept.
Tweedie$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Tweedie$
 
TYPE() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
 
typed - Class in org.apache.spark.sql.expressions.javalang
:: Experimental :: Type-safe functions available for Dataset operations in Java.
typed() - Constructor for class org.apache.spark.sql.expressions.javalang.typed
 
typed - Class in org.apache.spark.sql.expressions.scalalang
:: Experimental :: Type-safe functions available for Dataset operations in Scala.
typed() - Constructor for class org.apache.spark.sql.expressions.scalalang.typed
 
TypedColumn<T,U> - Class in org.apache.spark.sql
A Column where an Encoder has been given for the expected input and return type.
TypedColumn(Expression, ExpressionEncoder<U>) - Constructor for class org.apache.spark.sql.TypedColumn
 
typedLit(T, TypeTags.TypeTag<T>) - Static method in class org.apache.spark.sql.functions
Creates a Column of literal value.
typeInfoConversions(DataType) - Constructor for class org.apache.spark.sql.hive.HiveInspectors.typeInfoConversions
 
typeInfoConversions(DataType) - Static method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
typeName() - Method in class org.apache.spark.mllib.linalg.VectorUDT
 
typeName() - Static method in class org.apache.spark.sql.types.BinaryType
 
typeName() - Static method in class org.apache.spark.sql.types.BooleanType
 
typeName() - Static method in class org.apache.spark.sql.types.ByteType
 
typeName() - Static method in class org.apache.spark.sql.types.CalendarIntervalType
 
typeName() - Method in class org.apache.spark.sql.types.DataType
Name of the type used in JSON serialization.
typeName() - Static method in class org.apache.spark.sql.types.DateType
 
typeName() - Method in class org.apache.spark.sql.types.DecimalType
 
typeName() - Static method in class org.apache.spark.sql.types.DoubleType
 
typeName() - Static method in class org.apache.spark.sql.types.FloatType
 
typeName() - Static method in class org.apache.spark.sql.types.IntegerType
 
typeName() - Static method in class org.apache.spark.sql.types.LongType
 
typeName() - Static method in class org.apache.spark.sql.types.NullType
 
typeName() - Static method in class org.apache.spark.sql.types.ShortType
 
typeName() - Static method in class org.apache.spark.sql.types.StringType
 
typeName() - Static method in class org.apache.spark.sql.types.TimestampType
 

U

U() - Method in class org.apache.spark.mllib.linalg.SingularValueDecomposition
 
udf(Function0<RT>, TypeTags.TypeTag<RT>) - Static method in class org.apache.spark.sql.functions
Defines a Scala closure of 0 arguments as user-defined function (UDF).
udf(Function1<A1, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>) - Static method in class org.apache.spark.sql.functions
Defines a Scala closure of 1 arguments as user-defined function (UDF).
udf(Function2<A1, A2, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>) - Static method in class org.apache.spark.sql.functions
Defines a Scala closure of 2 arguments as user-defined function (UDF).
udf(Function3<A1, A2, A3, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>) - Static method in class org.apache.spark.sql.functions
Defines a Scala closure of 3 arguments as user-defined function (UDF).
udf(Function4<A1, A2, A3, A4, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>) - Static method in class org.apache.spark.sql.functions
Defines a Scala closure of 4 arguments as user-defined function (UDF).
udf(Function5<A1, A2, A3, A4, A5, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>) - Static method in class org.apache.spark.sql.functions
Defines a Scala closure of 5 arguments as user-defined function (UDF).
udf(Function6<A1, A2, A3, A4, A5, A6, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>) - Static method in class org.apache.spark.sql.functions
Defines a Scala closure of 6 arguments as user-defined function (UDF).
udf(Function7<A1, A2, A3, A4, A5, A6, A7, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>) - Static method in class org.apache.spark.sql.functions
Defines a Scala closure of 7 arguments as user-defined function (UDF).
udf(Function8<A1, A2, A3, A4, A5, A6, A7, A8, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>) - Static method in class org.apache.spark.sql.functions
Defines a Scala closure of 8 arguments as user-defined function (UDF).
udf(Function9<A1, A2, A3, A4, A5, A6, A7, A8, A9, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>) - Static method in class org.apache.spark.sql.functions
Defines a Scala closure of 9 arguments as user-defined function (UDF).
udf(Function10<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>) - Static method in class org.apache.spark.sql.functions
Defines a Scala closure of 10 arguments as user-defined function (UDF).
udf(UDF0<?>, DataType) - Static method in class org.apache.spark.sql.functions
Defines a Java UDF0 instance as user-defined function (UDF).
udf(UDF1<?, ?>, DataType) - Static method in class org.apache.spark.sql.functions
Defines a Java UDF1 instance as user-defined function (UDF).
udf(UDF2<?, ?, ?>, DataType) - Static method in class org.apache.spark.sql.functions
Defines a Java UDF2 instance as user-defined function (UDF).
udf(UDF3<?, ?, ?, ?>, DataType) - Static method in class org.apache.spark.sql.functions
Defines a Java UDF3 instance as user-defined function (UDF).
udf(UDF4<?, ?, ?, ?, ?>, DataType) - Static method in class org.apache.spark.sql.functions
Defines a Java UDF4 instance as user-defined function (UDF).
udf(UDF5<?, ?, ?, ?, ?, ?>, DataType) - Static method in class org.apache.spark.sql.functions
Defines a Java UDF5 instance as user-defined function (UDF).
udf(UDF6<?, ?, ?, ?, ?, ?, ?>, DataType) - Static method in class org.apache.spark.sql.functions
Defines a Java UDF6 instance as user-defined function (UDF).
udf(UDF7<?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Static method in class org.apache.spark.sql.functions
Defines a Java UDF7 instance as user-defined function (UDF).
udf(UDF8<?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Static method in class org.apache.spark.sql.functions
Defines a Java UDF8 instance as user-defined function (UDF).
udf(UDF9<?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Static method in class org.apache.spark.sql.functions
Defines a Java UDF9 instance as user-defined function (UDF).
udf(UDF10<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Static method in class org.apache.spark.sql.functions
Defines a Java UDF10 instance as user-defined function (UDF).
udf(Object, DataType) - Static method in class org.apache.spark.sql.functions
Defines a deterministic user-defined function (UDF) using a Scala closure.
udf() - Method in class org.apache.spark.sql.SparkSession
A collection of methods for registering user-defined functions (UDF).
udf() - Method in class org.apache.spark.sql.SQLContext
A collection of methods for registering user-defined functions (UDF).
UDF0<R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 0 arguments.
UDF1<T1,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 1 arguments.
UDF10<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 10 arguments.
UDF11<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 11 arguments.
UDF12<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 12 arguments.
UDF13<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 13 arguments.
UDF14<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 14 arguments.
UDF15<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 15 arguments.
UDF16<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 16 arguments.
UDF17<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 17 arguments.
UDF18<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17,T18,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 18 arguments.
UDF19<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17,T18,T19,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 19 arguments.
UDF2<T1,T2,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 2 arguments.
UDF20<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17,T18,T19,T20,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 20 arguments.
UDF21<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17,T18,T19,T20,T21,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 21 arguments.
UDF22<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17,T18,T19,T20,T21,T22,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 22 arguments.
UDF3<T1,T2,T3,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 3 arguments.
UDF4<T1,T2,T3,T4,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 4 arguments.
UDF5<T1,T2,T3,T4,T5,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 5 arguments.
UDF6<T1,T2,T3,T4,T5,T6,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 6 arguments.
UDF7<T1,T2,T3,T4,T5,T6,T7,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 7 arguments.
UDF8<T1,T2,T3,T4,T5,T6,T7,T8,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 8 arguments.
UDF9<T1,T2,T3,T4,T5,T6,T7,T8,T9,R> - Interface in org.apache.spark.sql.api.java
A Spark SQL UDF that has 9 arguments.
UDFRegistration - Class in org.apache.spark.sql
Functions for registering user-defined functions.
UDTRegistration - Class in org.apache.spark.sql.types
This object keeps the mappings between user classes and their User Defined Types (UDTs).
UDTRegistration() - Constructor for class org.apache.spark.sql.types.UDTRegistration
 
uid() - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
 
uid() - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
 
uid() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
 
uid() - Method in class org.apache.spark.ml.classification.GBTClassifier
 
uid() - Method in class org.apache.spark.ml.classification.LinearSVC
 
uid() - Method in class org.apache.spark.ml.classification.LinearSVCModel
 
uid() - Method in class org.apache.spark.ml.classification.LogisticRegression
 
uid() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
 
uid() - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
 
uid() - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
 
uid() - Method in class org.apache.spark.ml.classification.NaiveBayes
 
uid() - Method in class org.apache.spark.ml.classification.NaiveBayesModel
 
uid() - Method in class org.apache.spark.ml.classification.OneVsRest
 
uid() - Method in class org.apache.spark.ml.classification.OneVsRestModel
 
uid() - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
 
uid() - Method in class org.apache.spark.ml.classification.RandomForestClassifier
 
uid() - Method in class org.apache.spark.ml.clustering.BisectingKMeans
 
uid() - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
 
uid() - Method in class org.apache.spark.ml.clustering.GaussianMixture
 
uid() - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
 
uid() - Method in class org.apache.spark.ml.clustering.KMeans
 
uid() - Method in class org.apache.spark.ml.clustering.KMeansModel
 
uid() - Method in class org.apache.spark.ml.clustering.LDA
 
uid() - Method in class org.apache.spark.ml.clustering.LDAModel
 
uid() - Method in class org.apache.spark.ml.clustering.PowerIterationClustering
 
uid() - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
 
uid() - Method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
 
uid() - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
 
uid() - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
 
uid() - Method in class org.apache.spark.ml.feature.Binarizer
 
uid() - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
 
uid() - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
 
uid() - Method in class org.apache.spark.ml.feature.Bucketizer
 
uid() - Method in class org.apache.spark.ml.feature.ChiSqSelector
 
uid() - Method in class org.apache.spark.ml.feature.ChiSqSelectorModel
 
uid() - Method in class org.apache.spark.ml.feature.ColumnPruner
 
uid() - Method in class org.apache.spark.ml.feature.CountVectorizer
 
uid() - Method in class org.apache.spark.ml.feature.CountVectorizerModel
 
uid() - Method in class org.apache.spark.ml.feature.DCT
 
uid() - Method in class org.apache.spark.ml.feature.ElementwiseProduct
 
uid() - Method in class org.apache.spark.ml.feature.FeatureHasher
 
uid() - Method in class org.apache.spark.ml.feature.HashingTF
 
uid() - Method in class org.apache.spark.ml.feature.IDF
 
uid() - Method in class org.apache.spark.ml.feature.IDFModel
 
uid() - Method in class org.apache.spark.ml.feature.Imputer
 
uid() - Method in class org.apache.spark.ml.feature.ImputerModel
 
uid() - Method in class org.apache.spark.ml.feature.IndexToString
 
uid() - Method in class org.apache.spark.ml.feature.Interaction
 
uid() - Method in class org.apache.spark.ml.feature.MaxAbsScaler
 
uid() - Method in class org.apache.spark.ml.feature.MaxAbsScalerModel
 
uid() - Method in class org.apache.spark.ml.feature.MinHashLSH
 
uid() - Method in class org.apache.spark.ml.feature.MinHashLSHModel
 
uid() - Method in class org.apache.spark.ml.feature.MinMaxScaler
 
uid() - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
 
uid() - Method in class org.apache.spark.ml.feature.NGram
 
uid() - Method in class org.apache.spark.ml.feature.Normalizer
 
uid() - Method in class org.apache.spark.ml.feature.OneHotEncoder
Deprecated.
 
uid() - Method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
 
uid() - Method in class org.apache.spark.ml.feature.OneHotEncoderModel
 
uid() - Method in class org.apache.spark.ml.feature.PCA
 
uid() - Method in class org.apache.spark.ml.feature.PCAModel
 
uid() - Method in class org.apache.spark.ml.feature.PolynomialExpansion
 
uid() - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
 
uid() - Method in class org.apache.spark.ml.feature.RegexTokenizer
 
uid() - Method in class org.apache.spark.ml.feature.RFormula
 
uid() - Method in class org.apache.spark.ml.feature.RFormulaModel
 
uid() - Method in class org.apache.spark.ml.feature.SQLTransformer
 
uid() - Method in class org.apache.spark.ml.feature.StandardScaler
 
uid() - Method in class org.apache.spark.ml.feature.StandardScalerModel
 
uid() - Method in class org.apache.spark.ml.feature.StopWordsRemover
 
uid() - Method in class org.apache.spark.ml.feature.StringIndexer
 
uid() - Method in class org.apache.spark.ml.feature.StringIndexerModel
 
uid() - Method in class org.apache.spark.ml.feature.Tokenizer
 
uid() - Method in class org.apache.spark.ml.feature.VectorAssembler
 
uid() - Method in class org.apache.spark.ml.feature.VectorAttributeRewriter
 
uid() - Method in class org.apache.spark.ml.feature.VectorIndexer
 
uid() - Method in class org.apache.spark.ml.feature.VectorIndexerModel
 
uid() - Method in class org.apache.spark.ml.feature.VectorSizeHint
 
uid() - Method in class org.apache.spark.ml.feature.VectorSlicer
 
uid() - Method in class org.apache.spark.ml.feature.Word2Vec
 
uid() - Method in class org.apache.spark.ml.feature.Word2VecModel
 
uid() - Method in class org.apache.spark.ml.fpm.FPGrowth
 
uid() - Method in class org.apache.spark.ml.fpm.FPGrowthModel
 
uid() - Method in class org.apache.spark.ml.fpm.PrefixSpan
 
uid() - Method in class org.apache.spark.ml.Pipeline
 
uid() - Method in class org.apache.spark.ml.PipelineModel
 
uid() - Method in class org.apache.spark.ml.recommendation.ALS
 
uid() - Method in class org.apache.spark.ml.recommendation.ALSModel
 
uid() - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
 
uid() - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
uid() - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
 
uid() - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
 
uid() - Method in class org.apache.spark.ml.regression.GBTRegressionModel
 
uid() - Method in class org.apache.spark.ml.regression.GBTRegressor
 
uid() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
 
uid() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
 
uid() - Method in class org.apache.spark.ml.regression.IsotonicRegression
 
uid() - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
 
uid() - Method in class org.apache.spark.ml.regression.LinearRegression
 
uid() - Method in class org.apache.spark.ml.regression.LinearRegressionModel
 
uid() - Method in class org.apache.spark.ml.regression.RandomForestRegressionModel
 
uid() - Method in class org.apache.spark.ml.regression.RandomForestRegressor
 
uid() - Method in class org.apache.spark.ml.tuning.CrossValidator
 
uid() - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
 
uid() - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
 
uid() - Method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
 
uid() - Method in interface org.apache.spark.ml.util.Identifiable
An immutable unique ID for the object and its derivatives.
uiRoot() - Method in interface org.apache.spark.status.api.v1.ApiRequestContext
 
UIRoot - Interface in org.apache.spark.status.api.v1
This trait is shared by the all the root containers for application UI information -- the HistoryServer and the application UI.
uiRoot(HttpServletRequest) - Static method in class org.apache.spark.ui.UIUtils
 
UIRootFromServletContext - Class in org.apache.spark.status.api.v1
 
UIRootFromServletContext() - Constructor for class org.apache.spark.status.api.v1.UIRootFromServletContext
 
UIUtils - Class in org.apache.spark.streaming.ui
 
UIUtils() - Constructor for class org.apache.spark.streaming.ui.UIUtils
 
UIUtils - Class in org.apache.spark.ui
Utility functions for generating XML pages with spark content.
UIUtils() - Constructor for class org.apache.spark.ui.UIUtils
 
uiWebUrl() - Method in class org.apache.spark.SparkContext
 
UIWorkloadGenerator - Class in org.apache.spark.ui
Continuously generates jobs that expose various features of the WebUI (internal testing tool).
UIWorkloadGenerator() - Constructor for class org.apache.spark.ui.UIWorkloadGenerator
 
unapply(EdgeContext<VD, ED, A>) - Static method in class org.apache.spark.graphx.EdgeContext
Extractor mainly used for Graph#aggregateMessages*.
unapply(DenseVector) - Static method in class org.apache.spark.ml.linalg.DenseVector
Extracts the value array from a dense vector.
unapply(SparseVector) - Static method in class org.apache.spark.ml.linalg.SparseVector
 
unapply(DenseVector) - Static method in class org.apache.spark.mllib.linalg.DenseVector
Extracts the value array from a dense vector.
unapply(SparseVector) - Static method in class org.apache.spark.mllib.linalg.SparseVector
 
unapply(Column) - Static method in class org.apache.spark.sql.Column
 
unapply(Expression) - Method in class org.apache.spark.sql.types.DecimalType.Expression$
 
unapply(DecimalType) - Method in class org.apache.spark.sql.types.DecimalType.Fixed$
 
unapply(DataType) - Static method in class org.apache.spark.sql.types.DecimalType
 
unapply(Expression) - Static method in class org.apache.spark.sql.types.DecimalType
 
unapply(Expression) - Static method in class org.apache.spark.sql.types.NumericType
Enables matching against NumericType for expressions:
unapply(Throwable) - Static method in class org.apache.spark.util.CausedBy
 
unapply(String) - Static method in class org.apache.spark.util.IntParam
 
unapply(String) - Static method in class org.apache.spark.util.MemoryParam
 
UnaryTransformer<IN,OUT,T extends UnaryTransformer<IN,OUT,T>> - Class in org.apache.spark.ml
:: DeveloperApi :: Abstract class for transformers that take one input column, apply transformation, and output the result as a new column.
UnaryTransformer() - Constructor for class org.apache.spark.ml.UnaryTransformer
 
unbase64(Column) - Static method in class org.apache.spark.sql.functions
Decodes a BASE64 encoded string column and returns it as a binary column.
unboundedFollowing() - Static method in class org.apache.spark.sql.expressions.Window
Value representing the last row in the partition, equivalent to "UNBOUNDED FOLLOWING" in SQL.
unboundedFollowing() - Static method in class org.apache.spark.sql.functions
Deprecated.
Use Window.unboundedFollowing. Since 2.4.0.
unboundedPreceding() - Static method in class org.apache.spark.sql.expressions.Window
Value representing the first row in the partition, equivalent to "UNBOUNDED PRECEDING" in SQL.
unboundedPreceding() - Static method in class org.apache.spark.sql.functions
Deprecated.
Use Window.unboundedPreceding. Since 2.4.0.
unbroadcast(long, boolean, boolean) - Method in interface org.apache.spark.broadcast.BroadcastFactory
 
uncacheTable(String) - Method in class org.apache.spark.sql.catalog.Catalog
Removes the specified table from the in-memory cache.
uncacheTable(String) - Method in class org.apache.spark.sql.SQLContext
Removes the specified table from the in-memory cache.
UNCAUGHT_EXCEPTION() - Static method in class org.apache.spark.util.SparkExitCode
The default uncaught exception handler was reached.
UNCAUGHT_EXCEPTION_TWICE() - Static method in class org.apache.spark.util.SparkExitCode
The default uncaught exception handler was called and an exception was encountered while
undefinedImageType() - Static method in class org.apache.spark.ml.image.ImageSchema
 
underlyingSplit() - Method in class org.apache.spark.scheduler.SplitInfo
 
unhandledFilters(Filter[]) - Method in class org.apache.spark.sql.sources.BaseRelation
Returns the list of Filters that this datasource may not be able to handle.
unhex(Column) - Static method in class org.apache.spark.sql.functions
Inverse of hex.
UniformGenerator - Class in org.apache.spark.mllib.random
:: DeveloperApi :: Generates i.i.d.
UniformGenerator() - Constructor for class org.apache.spark.mllib.random.UniformGenerator
 
uniformJavaRDD(JavaSparkContext, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Java-friendly version of RandomRDDs.uniformRDD.
uniformJavaRDD(JavaSparkContext, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.uniformJavaRDD with the default seed.
uniformJavaRDD(JavaSparkContext, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.uniformJavaRDD with the default number of partitions and the default seed.
uniformJavaVectorRDD(JavaSparkContext, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Java-friendly version of RandomRDDs.uniformVectorRDD.
uniformJavaVectorRDD(JavaSparkContext, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.uniformJavaVectorRDD with the default seed.
uniformJavaVectorRDD(JavaSparkContext, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
RandomRDDs.uniformJavaVectorRDD with the default number of partitions and the default seed.
uniformRDD(SparkContext, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Generates an RDD comprised of i.i.d. samples from the uniform distribution U(0.0, 1.0).
uniformVectorRDD(SparkContext, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from the uniform distribution on U(0.0, 1.0).
union(JavaDoubleRDD) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Return the union of this RDD and another one.
union(JavaPairRDD<K, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
Return the union of this RDD and another one.
union(JavaRDD<T>) - Method in class org.apache.spark.api.java.JavaRDD
Return the union of this RDD and another one.
union(JavaRDD<T>, List<JavaRDD<T>>) - Method in class org.apache.spark.api.java.JavaSparkContext
Build the union of two or more RDDs.
union(JavaPairRDD<K, V>, List<JavaPairRDD<K, V>>) - Method in class org.apache.spark.api.java.JavaSparkContext
Build the union of two or more RDDs.
union(JavaDoubleRDD, List<JavaDoubleRDD>) - Method in class org.apache.spark.api.java.JavaSparkContext
Build the union of two or more RDDs.
union(RDD<T>) - Method in class org.apache.spark.rdd.RDD
Return the union of this RDD and another one.
union(Seq<RDD<T>>, ClassTag<T>) - Method in class org.apache.spark.SparkContext
Build the union of a list of RDDs.
union(RDD<T>, Seq<RDD<T>>, ClassTag<T>) - Method in class org.apache.spark.SparkContext
Build the union of a list of RDDs passed as variable-length arguments.
union(Dataset<T>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset containing union of rows in this Dataset and another Dataset.
union(JavaDStream<T>) - Method in class org.apache.spark.streaming.api.java.JavaDStream
Return a new DStream by unifying data of another DStream with this DStream.
union(JavaPairDStream<K, V>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream by unifying data of another DStream with this DStream.
union(JavaDStream<T>, List<JavaDStream<T>>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create a unified DStream from multiple DStreams of the same type and same slide duration.
union(JavaPairDStream<K, V>, List<JavaPairDStream<K, V>>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
Create a unified DStream from multiple DStreams of the same type and same slide duration.
union(DStream<T>) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream by unifying data of another DStream with this DStream.
union(Seq<DStream<T>>, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
Create a unified DStream from multiple DStreams of the same type and same slide duration.
unionAll(Dataset<T>) - Method in class org.apache.spark.sql.Dataset
Deprecated.
use union(). Since 2.0.0.
unionByName(Dataset<T>) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset containing union of rows in this Dataset and another Dataset.
UnionRDD<T> - Class in org.apache.spark.rdd
 
UnionRDD(SparkContext, Seq<RDD<T>>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.UnionRDD
 
uniqueId() - Method in class org.apache.spark.storage.StreamBlockId
 
unix_timestamp() - Static method in class org.apache.spark.sql.functions
Returns the current Unix timestamp (in seconds) as a long.
unix_timestamp(Column) - Static method in class org.apache.spark.sql.functions
Converts time string in format yyyy-MM-dd HH:mm:ss to Unix timestamp (in seconds), using the default timezone and the default locale.
unix_timestamp(Column, String) - Static method in class org.apache.spark.sql.functions
Converts time string with given pattern to Unix timestamp (in seconds).
UnknownReason - Class in org.apache.spark
:: DeveloperApi :: We don't know why the task ended -- for example, because of a ClassNotFound exception when deserializing the task result.
UnknownReason() - Constructor for class org.apache.spark.UnknownReason
 
UNLIMITED_DECIMAL_PRECISION() - Static method in class org.apache.spark.sql.hive.HiveShim
 
UNLIMITED_DECIMAL_SCALE() - Static method in class org.apache.spark.sql.hive.HiveShim
 
unlink(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.CLogLog$
 
unlink(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Identity$
 
unlink(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Inverse$
 
unlink(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Log$
 
unlink(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Logit$
 
unlink(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Probit$
 
unlink(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Sqrt$
 
UNORDERED() - Static method in class org.apache.spark.rdd.DeterministicLevel
 
unpersist() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
unpersist(boolean) - Method in class org.apache.spark.api.java.JavaDoubleRDD
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
unpersist() - Method in class org.apache.spark.api.java.JavaPairRDD
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
unpersist(boolean) - Method in class org.apache.spark.api.java.JavaPairRDD
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
unpersist() - Method in class org.apache.spark.api.java.JavaRDD
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
unpersist(boolean) - Method in class org.apache.spark.api.java.JavaRDD
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
unpersist() - Method in class org.apache.spark.broadcast.Broadcast
Asynchronously delete cached copies of this broadcast on the executors.
unpersist(boolean) - Method in class org.apache.spark.broadcast.Broadcast
Delete cached copies of this broadcast on the executors.
unpersist(boolean) - Method in class org.apache.spark.graphx.Graph
Uncaches both vertices and edges of this graph.
unpersist(boolean) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
 
unpersist(boolean) - Method in class org.apache.spark.graphx.impl.GraphImpl
 
unpersist(boolean) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
unpersist() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
Unpersist intermediate RDDs used in the computation.
unpersist(boolean) - Method in class org.apache.spark.rdd.RDD
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
unpersist(boolean) - Method in class org.apache.spark.sql.Dataset
Mark the Dataset as non-persistent, and remove all blocks for it from memory and disk.
unpersist() - Method in class org.apache.spark.sql.Dataset
Mark the Dataset as non-persistent, and remove all blocks for it from memory and disk.
unpersistRDDFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
unpersistRDDToJson(SparkListenerUnpersistRDD) - Static method in class org.apache.spark.util.JsonProtocol
 
unpersistVertices(boolean) - Method in class org.apache.spark.graphx.Graph
Uncaches only the vertices of this graph, leaving the edges alone.
unpersistVertices(boolean) - Method in class org.apache.spark.graphx.impl.GraphImpl
 
UnrecognizedBlockId - Exception in org.apache.spark.storage
 
UnrecognizedBlockId(String) - Constructor for exception org.apache.spark.storage.UnrecognizedBlockId
 
unregister(QueryExecutionListener) - Method in class org.apache.spark.sql.util.ExecutionListenerManager
Unregisters the specified QueryExecutionListener.
unregisterDialect(JdbcDialect) - Static method in class org.apache.spark.sql.jdbc.JdbcDialects
Unregister a dialect.
Unresolved() - Static method in class org.apache.spark.ml.attribute.AttributeType
Unresolved type.
UnresolvedAttribute - Class in org.apache.spark.ml.attribute
:: DeveloperApi :: An unresolved attribute.
UnresolvedAttribute() - Constructor for class org.apache.spark.ml.attribute.UnresolvedAttribute
 
unset() - Static method in class org.apache.spark.rdd.InputFileBlockHolder
Clears the input file block to default value.
unset(String) - Method in class org.apache.spark.sql.RuntimeConfig
Resets the configuration property for the given key.
until(Time, Duration) - Method in class org.apache.spark.streaming.Time
 
unwrapOrcStructs(Configuration, StructType, StructType, Option<StructObjectInspector>, Iterator<Writable>) - Static method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
unwrapperFor(ObjectInspector) - Method in interface org.apache.spark.sql.hive.HiveInspectors
Builds unwrappers ahead of time according to object inspector types to avoid pattern matching and branching costs per row.
unwrapperFor(StructField) - Method in interface org.apache.spark.sql.hive.HiveInspectors
Builds unwrappers ahead of time according to object inspector types to avoid pattern matching and branching costs per row.
unwrapperFor(ObjectInspector) - Static method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
unwrapperFor(StructField) - Static method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
update(int, int, double) - Method in interface org.apache.spark.ml.linalg.Matrix
Update element at (i, j)
update(Function1<Object, Object>) - Method in interface org.apache.spark.ml.linalg.Matrix
Update all the values of this matrix using the function f.
update(RDD<Vector>, double, String) - Method in class org.apache.spark.mllib.clustering.StreamingKMeansModel
Perform a k-means update on a batch of data.
update(int, int, double) - Method in interface org.apache.spark.mllib.linalg.Matrix
Update element at (i, j)
update(Function1<Object, Object>) - Method in interface org.apache.spark.mllib.linalg.Matrix
Update all the values of this matrix using the function f.
update() - Method in class org.apache.spark.scheduler.AccumulableInfo
 
update(int, Object) - Method in class org.apache.spark.sql.expressions.MutableAggregationBuffer
Update the ith value of this buffer.
update(MutableAggregationBuffer, Row) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
Updates the given aggregation buffer buffer with new input data from input.
update(S) - Method in interface org.apache.spark.sql.streaming.GroupState
Update the value of the state.
Update() - Static method in class org.apache.spark.sql.streaming.OutputMode
OutputMode in which only the rows that were updated in the streaming DataFrame/Dataset will be written to the sink every time there are some updates.
update(int, Object) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
 
update(int, Object) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
 
update() - Method in class org.apache.spark.status.api.v1.AccumulableInfo
 
update(Seq<String>, String, long, long) - Method in class org.apache.spark.status.LiveRDDPartition
 
update(S) - Method in class org.apache.spark.streaming.State
Update the state with a new value.
update(T1, T2) - Method in class org.apache.spark.util.MutablePair
Updates this pair with new values and returns itself
UpdateBlockInfo(BlockManagerId, BlockId, StorageLevel, long, long) - Constructor for class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
 
UpdateBlockInfo() - Constructor for class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
 
UpdateBlockInfo$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo$
 
UPDATED_BLOCK_STATUSES() - Static method in class org.apache.spark.InternalAccumulator
 
UpdateDelegationTokens(byte[]) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.UpdateDelegationTokens
 
UpdateDelegationTokens$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.UpdateDelegationTokens$
 
updateMetrics(TaskMetrics) - Method in class org.apache.spark.status.LiveTask
Update the metrics for the task and return the difference between the previous and new values.
updatePrediction(Vector, double, DecisionTreeRegressionModel, double) - Static method in class org.apache.spark.ml.tree.impl.GradientBoostedTrees
Add prediction from a new boosting iteration to an existing prediction.
updatePredictionError(RDD<LabeledPoint>, RDD<Tuple2<Object, Object>>, double, DecisionTreeRegressionModel, Loss) - Static method in class org.apache.spark.ml.tree.impl.GradientBoostedTrees
Update a zipped predictionError RDD (as obtained with computeInitialPredictionAndError)
updatePredictionError(RDD<LabeledPoint>, RDD<Tuple2<Object, Object>>, double, DecisionTreeModel, Loss) - Static method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
:: DeveloperApi :: Update a zipped predictionError RDD (as obtained with computeInitialPredictionAndError)
Updater - Class in org.apache.spark.mllib.optimization
:: DeveloperApi :: Class used to perform steps (weight update) using Gradient Descent methods.
Updater() - Constructor for class org.apache.spark.mllib.optimization.Updater
 
updateSparkConfigFromProperties(SparkConf, Map<String, String>) - Static method in class org.apache.spark.util.Utils
Updates Spark config with properties from a set of Properties.
updateStateByKey(Function2<List<V>, Optional<S>, Optional<S>>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new "state" DStream where the state for each key is updated by applying the given function on the previous state of the key and the new values of each key.
updateStateByKey(Function2<List<V>, Optional<S>, Optional<S>>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new "state" DStream where the state for each key is updated by applying the given function on the previous state of the key and the new values of each key.
updateStateByKey(Function2<List<V>, Optional<S>, Optional<S>>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new "state" DStream where the state for each key is updated by applying the given function on the previous state of the key and the new values of the key.
updateStateByKey(Function2<List<V>, Optional<S>, Optional<S>>, Partitioner, JavaPairRDD<K, S>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new "state" DStream where the state for each key is updated by applying the given function on the previous state of the key and the new values of the key.
updateStateByKey(Function2<Seq<V>, Option<S>, Option<S>>, ClassTag<S>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new "state" DStream where the state for each key is updated by applying the given function on the previous state of the key and the new values of each key.
updateStateByKey(Function2<Seq<V>, Option<S>, Option<S>>, int, ClassTag<S>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new "state" DStream where the state for each key is updated by applying the given function on the previous state of the key and the new values of each key.
updateStateByKey(Function2<Seq<V>, Option<S>, Option<S>>, Partitioner, ClassTag<S>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new "state" DStream where the state for each key is updated by applying the given function on the previous state of the key and the new values of the key.
updateStateByKey(Function1<Iterator<Tuple3<K, Seq<V>, Option<S>>>, Iterator<Tuple2<K, S>>>, Partitioner, boolean, ClassTag<S>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new "state" DStream where the state for each key is updated by applying the given function on the previous state of the key and the new values of each key.
updateStateByKey(Function2<Seq<V>, Option<S>, Option<S>>, Partitioner, RDD<Tuple2<K, S>>, ClassTag<S>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new "state" DStream where the state for each key is updated by applying the given function on the previous state of the key and the new values of the key.
updateStateByKey(Function1<Iterator<Tuple3<K, Seq<V>, Option<S>>>, Iterator<Tuple2<K, S>>>, Partitioner, boolean, RDD<Tuple2<K, S>>, ClassTag<S>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new "state" DStream where the state for each key is updated by applying the given function on the previous state of the key and the new values of each key.
updateStateByKey(Function4<Time, K, Seq<V>, Option<S>, Option<S>>, Partitioner, boolean, Option<RDD<Tuple2<K, S>>>, ClassTag<S>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
Return a new "state" DStream where the state for each key is updated by applying the given function on the previous state of the key and the new values of the key.
upper(Column) - Static method in class org.apache.spark.sql.functions
Converts a string column to upper case.
upperBoundsOnCoefficients() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
The upper bounds on coefficients if fitting under bound constrained optimization.
upperBoundsOnIntercepts() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
The upper bounds on intercepts if fitting under bound constrained optimization.
useCommitCoordinator() - Method in interface org.apache.spark.sql.sources.v2.writer.DataSourceWriter
Returns whether Spark should use the commit coordinator to ensure that at most one task for each partition commits.
useDisk() - Method in class org.apache.spark.storage.StorageLevel
 
usedOffHeap() - Method in class org.apache.spark.status.LiveExecutor
 
usedOffHeapStorageMemory() - Method in interface org.apache.spark.SparkExecutorInfo
 
usedOffHeapStorageMemory() - Method in class org.apache.spark.SparkExecutorInfoImpl
 
usedOffHeapStorageMemory() - Method in class org.apache.spark.status.api.v1.MemoryMetrics
 
usedOnHeap() - Method in class org.apache.spark.status.LiveExecutor
 
usedOnHeapStorageMemory() - Method in interface org.apache.spark.SparkExecutorInfo
 
usedOnHeapStorageMemory() - Method in class org.apache.spark.SparkExecutorInfoImpl
 
usedOnHeapStorageMemory() - Method in class org.apache.spark.status.api.v1.MemoryMetrics
 
useDst - Variable in class org.apache.spark.graphx.TripletFields
Indicates whether the destination vertex attribute is included.
useEdge - Variable in class org.apache.spark.graphx.TripletFields
Indicates whether the edge attribute is included.
useMemory() - Method in class org.apache.spark.storage.StorageLevel
 
useNodeIdCache() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
 
useOffHeap() - Method in class org.apache.spark.storage.StorageLevel
 
user() - Method in class org.apache.spark.ml.recommendation.ALS.Rating
 
user() - Method in class org.apache.spark.mllib.recommendation.Rating
 
USER_DEFAULT() - Static method in class org.apache.spark.sql.types.DecimalType
 
userClass() - Method in class org.apache.spark.mllib.linalg.VectorUDT
 
userCol() - Method in interface org.apache.spark.ml.recommendation.ALSModelParams
Param for the column name for user ids.
UserDefinedAggregateFunction - Class in org.apache.spark.sql.expressions
The base class for implementing user-defined aggregate functions (UDAF).
UserDefinedAggregateFunction() - Constructor for class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
 
UserDefinedFunction - Class in org.apache.spark.sql.expressions
A user-defined function.
userFactors() - Method in class org.apache.spark.ml.recommendation.ALSModel
 
userFeatures() - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
 
userPort(int, int) - Static method in class org.apache.spark.util.Utils
Returns the user port to try when trying to bind a service.
useSrc - Variable in class org.apache.spark.graphx.TripletFields
Indicates whether the source vertex attribute is included.
usingBoundConstrainedOptimization() - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
 
Utils - Class in org.apache.spark.ml.impl
 
Utils() - Constructor for class org.apache.spark.ml.impl.Utils
 
Utils - Class in org.apache.spark.util
Various utility methods used by Spark.
Utils() - Constructor for class org.apache.spark.util.Utils
 
UUIDFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
 
UUIDToJson(UUID) - Static method in class org.apache.spark.util.JsonProtocol
 

V

V() - Method in class org.apache.spark.mllib.linalg.SingularValueDecomposition
 
validate() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
Validates the block matrix info against the matrix data (blocks) and throws an exception if any error is found.
validateAndTransformSchema(StructType, boolean, DataType) - Method in interface org.apache.spark.ml.classification.ClassifierParams
 
validateAndTransformSchema(StructType, boolean, DataType) - Method in interface org.apache.spark.ml.classification.LogisticRegressionParams
 
validateAndTransformSchema(StructType, boolean, DataType) - Method in interface org.apache.spark.ml.classification.ProbabilisticClassifierParams
 
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.clustering.BisectingKMeansParams
Validates and transforms the input schema.
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.clustering.GaussianMixtureParams
Validates and transforms the input schema.
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.clustering.KMeansParams
Validates and transforms the input schema.
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.clustering.LDAParams
Validates and transforms the input schema.
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.feature.CountVectorizerParams
Validates and transforms the input schema.
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.feature.IDFBase
Validate and transform the input schema.
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.feature.ImputerParams
Validates and transforms the input schema.
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.feature.LSHParams
Transform the Schema for LSH
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.feature.MaxAbsScalerParams
Validates and transforms the input schema.
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.feature.MinMaxScalerParams
Validates and transforms the input schema.
validateAndTransformSchema(StructType, boolean, boolean) - Method in interface org.apache.spark.ml.feature.OneHotEncoderBase
 
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.feature.PCAParams
Validates and transforms the input schema.
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.feature.StandardScalerParams
Validates and transforms the input schema.
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.feature.StringIndexerBase
Validates and transforms the input schema.
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.feature.Word2VecBase
Validate and transform the input schema.
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.fpm.FPGrowthParams
Validates and transforms the input schema.
validateAndTransformSchema(StructType, boolean, DataType) - Method in interface org.apache.spark.ml.PredictorParams
Validates and transforms the input schema with the provided param map.
validateAndTransformSchema(StructType) - Method in interface org.apache.spark.ml.recommendation.ALSParams
Validates and transforms the input schema.
validateAndTransformSchema(StructType, boolean) - Method in interface org.apache.spark.ml.regression.AFTSurvivalRegressionParams
Validates and transforms the input schema with the provided param map.
validateAndTransformSchema(StructType, boolean, DataType) - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
 
validateAndTransformSchema(StructType, boolean) - Method in interface org.apache.spark.ml.regression.IsotonicRegressionBase
Validates and transforms input schema.
validateAndTransformSchema(StructType, boolean, DataType) - Method in interface org.apache.spark.ml.regression.LinearRegressionParams
 
validateAndTransformSchema(StructType, boolean, DataType) - Method in interface org.apache.spark.ml.tree.DecisionTreeRegressorParams
 
validateDirectoryUri(String) - Method in interface org.apache.spark.rpc.RpcEnvFileServer
Validates and normalizes the base URI for directories.
validateStages(PipelineStage[]) - Method in class org.apache.spark.ml.Pipeline.SharedReadWrite$
Check that all stages are Writable
validateURL(URI) - Static method in class org.apache.spark.util.Utils
Validate that a given URI is actually a valid URL as well.
validateVectorCompatibleColumn(StructType, String) - Static method in class org.apache.spark.ml.util.SchemaUtils
Check whether the given column in the schema is one of the supporting vector type: Vector, Array[Float].
validationIndicatorCol() - Method in interface org.apache.spark.ml.param.shared.HasValidationIndicatorCol
Param for name of the column that indicates whether each row is for training or for validation.
validationMetrics() - Method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
 
validationTol() - Method in interface org.apache.spark.ml.tree.GBTParams
Threshold for stopping early when fit with validation is used.
validationTol() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
 
ValidatorParams - Interface in org.apache.spark.ml.tuning
value() - Method in class org.apache.spark.Accumulable
Deprecated.
Access the accumulator's current value; only allowed on driver.
value() - Method in class org.apache.spark.broadcast.Broadcast
Get the broadcasted value.
value() - Method in class org.apache.spark.ComplexFutureAction
 
value() - Method in interface org.apache.spark.FutureAction
The value of this Future.
value() - Method in class org.apache.spark.ml.param.ParamPair
 
value() - Method in class org.apache.spark.mllib.linalg.distributed.MatrixEntry
 
value() - Method in class org.apache.spark.mllib.stat.test.BinarySample
 
value() - Method in class org.apache.spark.scheduler.AccumulableInfo
 
value() - Method in class org.apache.spark.SerializableWritable
 
value() - Method in class org.apache.spark.SimpleFutureAction
 
value() - Method in class org.apache.spark.sql.sources.EqualNullSafe
 
value() - Method in class org.apache.spark.sql.sources.EqualTo
 
value() - Method in class org.apache.spark.sql.sources.GreaterThan
 
value() - Method in class org.apache.spark.sql.sources.GreaterThanOrEqual
 
value() - Method in class org.apache.spark.sql.sources.LessThan
 
value() - Method in class org.apache.spark.sql.sources.LessThanOrEqual
 
value() - Method in class org.apache.spark.sql.sources.StringContains
 
value() - Method in class org.apache.spark.sql.sources.StringEndsWith
 
value() - Method in class org.apache.spark.sql.sources.StringStartsWith
 
value() - Method in class org.apache.spark.status.api.v1.AccumulableInfo
 
value() - Method in class org.apache.spark.status.LiveRDDPartition
 
value() - Method in class org.apache.spark.storage.memory.DeserializedMemoryEntry
 
value() - Method in class org.apache.spark.util.AccumulatorV2
Defines the current value of this accumulator
value() - Method in class org.apache.spark.util.CollectionAccumulator
 
value() - Method in class org.apache.spark.util.DoubleAccumulator
 
value() - Method in class org.apache.spark.util.LegacyAccumulatorWrapper
 
value() - Method in class org.apache.spark.util.LongAccumulator
 
valueArray() - Method in class org.apache.spark.sql.vectorized.ColumnarMap
 
valueContainsNull() - Method in class org.apache.spark.sql.types.MapType
 
valueOf(String) - Static method in enum org.apache.spark.graphx.impl.EdgeActiveness
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.spark.JobExecutionStatus
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.spark.launcher.SparkAppHandle.State
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.spark.sql.SaveMode
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.spark.status.api.v1.ApplicationStatus
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.spark.status.api.v1.StageStatus
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.spark.status.api.v1.streaming.BatchStatus
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.spark.status.api.v1.TaskSorting
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.spark.streaming.StreamingContextState
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.spark.util.sketch.BloomFilter.Version
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.spark.util.sketch.CountMinSketch.Version
Returns the enum constant of this type with the specified name.
values() - Method in class org.apache.spark.api.java.JavaPairRDD
Return an RDD with the values of each tuple.
values() - Static method in enum org.apache.spark.graphx.impl.EdgeActiveness
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.spark.JobExecutionStatus
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.spark.launcher.SparkAppHandle.State
Returns an array containing the constants of this enum type, in the order they are declared.
VALUES() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
 
values() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
 
values() - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
values() - Method in class org.apache.spark.ml.linalg.DenseMatrix
 
values() - Method in class org.apache.spark.ml.linalg.DenseVector
 
values() - Method in class org.apache.spark.ml.linalg.SparseMatrix
 
values() - Method in class org.apache.spark.ml.linalg.SparseVector
 
values() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
 
values() - Method in class org.apache.spark.mllib.linalg.DenseVector
 
values() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
 
values() - Method in class org.apache.spark.mllib.linalg.SparseVector
 
values() - Static method in class org.apache.spark.mllib.tree.configuration.Algo
 
values() - Static method in class org.apache.spark.mllib.tree.configuration.EnsembleCombiningStrategy
 
values() - Static method in class org.apache.spark.mllib.tree.configuration.FeatureType
 
values() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
 
values() - Static method in class org.apache.spark.rdd.CheckpointState
 
values() - Static method in class org.apache.spark.rdd.DeterministicLevel
 
values() - Method in class org.apache.spark.rdd.PairRDDFunctions
Return an RDD with the values of each tuple.
values() - Static method in class org.apache.spark.scheduler.SchedulingMode
 
values() - Static method in class org.apache.spark.scheduler.TaskLocality
 
values() - Static method in enum org.apache.spark.sql.SaveMode
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Method in class org.apache.spark.sql.sources.In
 
values() - Static method in enum org.apache.spark.status.api.v1.ApplicationStatus
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.spark.status.api.v1.StageStatus
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.spark.status.api.v1.streaming.BatchStatus
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.spark.status.api.v1.TaskSorting
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
 
values() - Static method in enum org.apache.spark.streaming.StreamingContextState
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in class org.apache.spark.TaskState
 
values() - Static method in enum org.apache.spark.util.sketch.BloomFilter.Version
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.spark.util.sketch.CountMinSketch.Version
Returns an array containing the constants of this enum type, in the order they are declared.
ValuesHolder<T> - Interface in org.apache.spark.storage.memory
 
valueType() - Method in class org.apache.spark.sql.types.MapType
 
var_pop(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the population variance of the values in a group.
var_pop(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the population variance of the values in a group.
var_samp(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the unbiased variance of the values in a group.
var_samp(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: returns the unbiased variance of the values in a group.
VarcharType - Class in org.apache.spark.sql.types
Hive varchar type.
VarcharType(int) - Constructor for class org.apache.spark.sql.types.VarcharType
 
variance() - Method in class org.apache.spark.api.java.JavaDoubleRDD
Compute the population variance of this RDD's elements.
variance(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
 
variance(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
 
variance(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
 
variance(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
 
variance(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
variance(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
 
variance() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
Unbiased estimate of sample variance of each dimension.
variance() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
Sample variance vector.
Variance - Class in org.apache.spark.mllib.tree.impurity
Class for calculating variance during regression
Variance() - Constructor for class org.apache.spark.mllib.tree.impurity.Variance
 
variance() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
Compute the population variance of this RDD's elements.
variance(Column) - Static method in class org.apache.spark.sql.functions
Aggregate function: alias for var_samp.
variance(String) - Static method in class org.apache.spark.sql.functions
Aggregate function: alias for var_samp.
variance() - Method in class org.apache.spark.util.StatCounter
Return the population variance of the values.
varianceCol() - Method in interface org.apache.spark.ml.param.shared.HasVarianceCol
Param for Column name for the biased sample variance of prediction.
variancePower() - Method in interface org.apache.spark.ml.regression.GeneralizedLinearRegressionBase
Param for the power in the variance function of the Tweedie distribution which provides the relationship between the variance and mean of the distribution.
vClassTag() - Method in class org.apache.spark.api.java.JavaHadoopRDD
 
vClassTag() - Method in class org.apache.spark.api.java.JavaNewHadoopRDD
 
vClassTag() - Method in class org.apache.spark.api.java.JavaPairRDD
 
vClassTag() - Method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
 
vClassTag() - Method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
 
Vector - Interface in org.apache.spark.ml.linalg
Represents a numeric vector, whose index type is Int and value type is Double.
vector() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRow
 
Vector - Interface in org.apache.spark.mllib.linalg
Represents a numeric vector, whose index type is Int and value type is Double.
vector() - Method in class org.apache.spark.storage.memory.DeserializedValuesHolder
 
VectorAssembler - Class in org.apache.spark.ml.feature
A feature transformer that merges multiple columns into a vector column.
VectorAssembler(String) - Constructor for class org.apache.spark.ml.feature.VectorAssembler
 
VectorAssembler() - Constructor for class org.apache.spark.ml.feature.VectorAssembler
 
VectorAttributeRewriter - Class in org.apache.spark.ml.feature
Utility transformer that rewrites Vector attribute names via prefix replacement.
VectorAttributeRewriter(String, String, Map<String, String>) - Constructor for class org.apache.spark.ml.feature.VectorAttributeRewriter
 
VectorAttributeRewriter(String, Map<String, String>) - Constructor for class org.apache.spark.ml.feature.VectorAttributeRewriter
 
vectorCol() - Method in class org.apache.spark.ml.feature.VectorAttributeRewriter
 
VectorImplicits - Class in org.apache.spark.mllib.linalg
Implicit methods available in Scala for converting Vector to Vector and vice versa.
VectorImplicits() - Constructor for class org.apache.spark.mllib.linalg.VectorImplicits
 
VectorIndexer - Class in org.apache.spark.ml.feature
Class for indexing categorical feature columns in a dataset of Vector.
VectorIndexer(String) - Constructor for class org.apache.spark.ml.feature.VectorIndexer
 
VectorIndexer() - Constructor for class org.apache.spark.ml.feature.VectorIndexer
 
VectorIndexerModel - Class in org.apache.spark.ml.feature
Model fitted by VectorIndexer.
VectorIndexerParams - Interface in org.apache.spark.ml.feature
Private trait for params for VectorIndexer and VectorIndexerModel
Vectors - Class in org.apache.spark.ml.linalg
Factory methods for Vector.
Vectors() - Constructor for class org.apache.spark.ml.linalg.Vectors
 
Vectors - Class in org.apache.spark.mllib.linalg
Factory methods for Vector.
Vectors() - Constructor for class org.apache.spark.mllib.linalg.Vectors
 
vectorSize() - Method in interface org.apache.spark.ml.feature.Word2VecBase
The dimension of the code that you want to transform from words.
VectorSizeHint - Class in org.apache.spark.ml.feature
:: Experimental :: A feature transformer that adds size information to the metadata of a vector column.
VectorSizeHint(String) - Constructor for class org.apache.spark.ml.feature.VectorSizeHint
 
VectorSizeHint() - Constructor for class org.apache.spark.ml.feature.VectorSizeHint
 
VectorSlicer - Class in org.apache.spark.ml.feature
This class takes a feature vector and outputs a new feature vector with a subarray of the original features.
VectorSlicer(String) - Constructor for class org.apache.spark.ml.feature.VectorSlicer
 
VectorSlicer() - Constructor for class org.apache.spark.ml.feature.VectorSlicer
 
VectorTransformer - Interface in org.apache.spark.mllib.feature
:: DeveloperApi :: Trait for transformation of a vector
VectorType() - Static method in class org.apache.spark.ml.linalg.SQLDataTypes
Data type for Vector.
VectorUDT - Class in org.apache.spark.mllib.linalg
:: AlphaComponent ::
VectorUDT() - Constructor for class org.apache.spark.mllib.linalg.VectorUDT
 
version() - Method in class org.apache.spark.api.java.JavaSparkContext
The version of Spark on which this application is running.
version() - Method in class org.apache.spark.io.SnappyCompressionCodec
 
version() - Method in class org.apache.spark.SparkContext
The version of Spark on which this application is running.
version() - Method in interface org.apache.spark.sql.hive.client.HiveClient
Returns the Hive Version of this client.
version() - Method in class org.apache.spark.sql.SparkSession
The version of Spark on which this application is running.
VersionInfo - Class in org.apache.spark.status.api.v1
 
VersionUtils - Class in org.apache.spark.util
Utilities for working with Spark version strings
VersionUtils() - Constructor for class org.apache.spark.util.VersionUtils
 
vertcat(Matrix[]) - Static method in class org.apache.spark.ml.linalg.Matrices
Vertically concatenate a sequence of matrices.
vertcat(Matrix[]) - Static method in class org.apache.spark.mllib.linalg.Matrices
Vertically concatenate a sequence of matrices.
vertexAttr(long) - Method in class org.apache.spark.graphx.EdgeTriplet
Get the vertex object for the given vertex in the edge.
VertexPartitionBaseOpsConstructor<T extends org.apache.spark.graphx.impl.VertexPartitionBase<Object>> - Interface in org.apache.spark.graphx.impl
A typeclass for subclasses of VertexPartitionBase representing the ability to wrap them in a VertexPartitionBaseOps.
VertexRDD<VD> - Class in org.apache.spark.graphx
Extends RDD[(VertexId, VD)] by ensuring that there is only one entry for each vertex and by pre-indexing the entries for fast, efficient joins.
VertexRDD(SparkContext, Seq<Dependency<?>>) - Constructor for class org.apache.spark.graphx.VertexRDD
 
VertexRDDImpl<VD> - Class in org.apache.spark.graphx.impl
 
vertices() - Method in class org.apache.spark.graphx.Graph
An RDD containing the vertices and their associated attributes.
vertices() - Method in class org.apache.spark.graphx.impl.GraphImpl
 
viewToSeq(KVStoreView<T>, int, Function1<T, Object>) - Static method in class org.apache.spark.status.KVUtils
Turns a KVStoreView into a Scala sequence, applying a filter.
visit(int, int, String, String, String, String[]) - Method in class org.apache.spark.util.InnerClosureFinder
 
visitMethod(int, String, String, String, String[]) - Method in class org.apache.spark.util.InnerClosureFinder
 
visitMethod(int, String, String, String, String[]) - Method in class org.apache.spark.util.ReturnStatementFinder
 
vizHeaderNodes(HttpServletRequest) - Static method in class org.apache.spark.ui.UIUtils
 
vManifest() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
 
vocabSize() - Method in class org.apache.spark.ml.clustering.LDAModel
 
vocabSize() - Method in interface org.apache.spark.ml.feature.CountVectorizerParams
Max size of the vocabulary.
vocabSize() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
 
vocabSize() - Method in class org.apache.spark.mllib.clustering.LDAModel
Vocabulary size (number of terms or terms in the vocabulary)
vocabSize() - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
 
vocabulary() - Method in class org.apache.spark.ml.feature.CountVectorizerModel
 
VocabWord - Class in org.apache.spark.mllib.feature
Entry in vocabulary
VocabWord(String, long, int[], int[], int) - Constructor for class org.apache.spark.mllib.feature.VocabWord
 
VoidFunction<T> - Interface in org.apache.spark.api.java.function
A function with no return value.
VoidFunction2<T1,T2> - Interface in org.apache.spark.api.java.function
A two-argument function that takes arguments of type T1 and T2 with no return value.
Vote() - Static method in class org.apache.spark.mllib.tree.configuration.EnsembleCombiningStrategy
 

W

w(boolean) - Method in class org.apache.spark.ml.param.BooleanParam
Creates a param pair with the given value (for Java).
w(List<List<Double>>) - Method in class org.apache.spark.ml.param.DoubleArrayArrayParam
Creates a param pair with a `java.util.List` of values (for Java and Python).
w(List<Double>) - Method in class org.apache.spark.ml.param.DoubleArrayParam
Creates a param pair with a `java.util.List` of values (for Java and Python).
w(double) - Method in class org.apache.spark.ml.param.DoubleParam
Creates a param pair with the given value (for Java).
w(float) - Method in class org.apache.spark.ml.param.FloatParam
Creates a param pair with the given value (for Java).
w(List<Integer>) - Method in class org.apache.spark.ml.param.IntArrayParam
Creates a param pair with a `java.util.List` of values (for Java and Python).
w(int) - Method in class org.apache.spark.ml.param.IntParam
Creates a param pair with the given value (for Java).
w(long) - Method in class org.apache.spark.ml.param.LongParam
Creates a param pair with the given value (for Java).
w(T) - Method in class org.apache.spark.ml.param.Param
Creates a param pair with the given value (for Java).
w(List<String>) - Method in class org.apache.spark.ml.param.StringArrayParam
Creates a param pair with a `java.util.List` of values (for Java and Python).
waitTillTime(long) - Method in interface org.apache.spark.util.Clock
 
waitUntilEmpty(long) - Method in class org.apache.spark.scheduler.AsyncEventQueue
For testing only.
warmUp(SparkContext) - Static method in class org.apache.spark.streaming.util.RawTextHelper
Warms up the SparkContext in master and slave by running tasks to force JIT kick in before real workload starts.
weakIntern(String) - Static method in class org.apache.spark.status.LiveEntityHelpers
String interning to reduce the memory usage.
weekofyear(Column) - Static method in class org.apache.spark.sql.functions
Extracts the week number as an integer from a given date/timestamp/string.
WeibullGenerator - Class in org.apache.spark.mllib.random
:: DeveloperApi :: Generates i.i.d.
WeibullGenerator(double, double) - Constructor for class org.apache.spark.mllib.random.WeibullGenerator
 
weight() - Method in interface org.apache.spark.ml.optim.aggregator.DifferentiableLossAggregator
Weighted count of instances in this aggregator.
weight() - Method in interface org.apache.spark.scheduler.Schedulable
 
weightCol() - Method in interface org.apache.spark.ml.param.shared.HasWeightCol
Param for weight column name.
weightedFalsePositiveRate() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns weighted false positive rate.
weightedFalsePositiveRate() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns weighted false positive rate
weightedFMeasure(double) - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns weighted averaged f-measure.
weightedFMeasure() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns weighted averaged f1-measure.
weightedFMeasure(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns weighted averaged f-measure
weightedFMeasure() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns weighted averaged f1-measure
weightedPrecision() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns weighted averaged precision.
weightedPrecision() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns weighted averaged precision
weightedRecall() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns weighted averaged recall.
weightedRecall() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns weighted averaged recall (equals to precision, recall and f-measure)
weightedTruePositiveRate() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
Returns weighted true positive rate.
weightedTruePositiveRate() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
Returns weighted true positive rate (equals to precision, recall and f-measure)
weights() - Method in interface org.apache.spark.ml.ann.LayerModel
 
weights() - Method in interface org.apache.spark.ml.ann.TopologyModel
 
weights() - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
 
weights() - Method in class org.apache.spark.ml.clustering.ExpectationAggregator
 
weights() - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
 
weights() - Method in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$.Data
 
weights() - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
 
weights() - Method in class org.apache.spark.mllib.classification.SVMModel
 
weights() - Method in class org.apache.spark.mllib.clustering.ExpectationSum
 
weights() - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
 
weights() - Method in class org.apache.spark.mllib.regression.GeneralizedLinearModel
 
weights() - Method in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$.Data
 
weights() - Method in class org.apache.spark.mllib.regression.LassoModel
 
weights() - Method in class org.apache.spark.mllib.regression.LinearRegressionModel
 
weights() - Method in class org.apache.spark.mllib.regression.RidgeRegressionModel
 
weightSize() - Method in interface org.apache.spark.ml.ann.Layer
Number of weights that is used to allocate memory for the weights vector
weightSum() - Method in interface org.apache.spark.ml.optim.aggregator.DifferentiableLossAggregator
 
WelchTTest - Class in org.apache.spark.mllib.stat.test
Performs Welch's 2-sample t-test.
WelchTTest() - Constructor for class org.apache.spark.mllib.stat.test.WelchTTest
 
when(Column, Object) - Method in class org.apache.spark.sql.Column
Evaluates a list of conditions and returns one of multiple possible result expressions.
when(Column, Object) - Static method in class org.apache.spark.sql.functions
Evaluates a list of conditions and returns one of multiple possible result expressions.
where(Column) - Method in class org.apache.spark.sql.Dataset
Filters rows using the given condition.
where(String) - Method in class org.apache.spark.sql.Dataset
Filters rows using the given SQL expression.
wholeTextFiles(String, int) - Method in class org.apache.spark.api.java.JavaSparkContext
Read a directory of text files from HDFS, a local file system (available on all nodes), or any Hadoop-supported file system URI.
wholeTextFiles(String) - Method in class org.apache.spark.api.java.JavaSparkContext
Read a directory of text files from HDFS, a local file system (available on all nodes), or any Hadoop-supported file system URI.
wholeTextFiles(String, int) - Method in class org.apache.spark.SparkContext
Read a directory of text files from HDFS, a local file system (available on all nodes), or any Hadoop-supported file system URI.
width() - Method in class org.apache.spark.util.sketch.CountMinSketch
Width of this CountMinSketch.
Window - Class in org.apache.spark.sql.expressions
Utility functions for defining window in DataFrames.
Window() - Constructor for class org.apache.spark.sql.expressions.Window
 
window(Column, String, String, String) - Static method in class org.apache.spark.sql.functions
Bucketize rows into one or more time windows given a timestamp specifying column.
window(Column, String, String) - Static method in class org.apache.spark.sql.functions
Bucketize rows into one or more time windows given a timestamp specifying column.
window(Column, String) - Static method in class org.apache.spark.sql.functions
Generates tumbling time windows given a timestamp specifying column.
window(Duration) - Method in class org.apache.spark.streaming.api.java.JavaDStream
Return a new DStream in which each RDD contains all the elements in seen in a sliding window of time over this DStream.
window(Duration, Duration) - Method in class org.apache.spark.streaming.api.java.JavaDStream
Return a new DStream in which each RDD contains all the elements in seen in a sliding window of time over this DStream.
window(Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream which is computed based on windowed batches of this DStream.
window(Duration, Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
Return a new DStream which is computed based on windowed batches of this DStream.
window(Duration) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD contains all the elements in seen in a sliding window of time over this DStream.
window(Duration, Duration) - Method in class org.apache.spark.streaming.dstream.DStream
Return a new DStream in which each RDD contains all the elements in seen in a sliding window of time over this DStream.
windowsDrive() - Static method in class org.apache.spark.util.Utils
Pattern for matching a Windows drive, which contains only a single alphabet character.
windowSize() - Method in interface org.apache.spark.ml.feature.Word2VecBase
The window size (context words from [-window, window]).
WindowSpec - Class in org.apache.spark.sql.expressions
A window specification that defines the partitioning, ordering, and frame boundaries.
wipe() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
 
withColumn(String, Column) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset by adding a column or replacing the existing column that has the same name.
withColumnRenamed(String, String) - Method in class org.apache.spark.sql.Dataset
Returns a new Dataset with a column renamed.
withComment(String) - Method in class org.apache.spark.sql.types.StructField
Updates the StructField with a new comment value.
withContextClassLoader(ClassLoader, Function0<T>) - Static method in class org.apache.spark.util.Utils
Run a segment of code using a different context class loader in the current thread
withDummyCallSite(SparkContext, Function0<T>) - Static method in class org.apache.spark.util.Utils
To avoid calling Utils.getCallSite for every single RDD we create in the body, set a dummy call site that RDDs use instead.
withEdges(EdgeRDD<?>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
 
withEdges(EdgeRDD<?>) - Method in class org.apache.spark.graphx.VertexRDD
Prepares this VertexRDD for efficient joins with the given EdgeRDD.
withExtensions(Function1<SparkSessionExtensions, BoxedUnit>) - Method in class org.apache.spark.sql.SparkSession.Builder
Inject extensions into the SparkSession.
withHiveExternalCatalog(SparkContext) - Static method in class org.apache.spark.sql.hive.HiveUtils
 
withHiveState(Function0<A>) - Method in interface org.apache.spark.sql.hive.client.HiveClient
Run a function within Hive state (SessionState, HiveConf, Hive client and class loader)
withIndex(int) - Method in class org.apache.spark.ml.attribute.Attribute
Copy with a new index.
withIndex(int) - Method in class org.apache.spark.ml.attribute.BinaryAttribute
 
withIndex(int) - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
withIndex(int) - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
withIndex(int) - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
withListener(Function1<org.apache.spark.streaming.ui.StreamingJobProgressListener, T>) - Method in interface org.apache.spark.status.api.v1.streaming.BaseStreamingAppResource
 
withListener(SparkContext, L, Function1<L, BoxedUnit>) - Static method in class org.apache.spark.TestUtils
Runs some code with the given listener installed in the SparkContext.
withMapStatuses(Function1<MapStatus[], T>) - Method in class org.apache.spark.ShuffleStatus
Helper function which provides thread-safe access to the mapStatuses array.
withMax(double) - Method in class org.apache.spark.ml.attribute.NumericAttribute
Copy with a new max value.
withMean() - Method in interface org.apache.spark.ml.feature.StandardScalerParams
Whether to center the data with mean before scaling.
withMean() - Method in class org.apache.spark.mllib.feature.StandardScalerModel
 
withMetadata(Metadata) - Method in class org.apache.spark.sql.types.MetadataBuilder
Include the content of an existing Metadata instance.
withMin(double) - Method in class org.apache.spark.ml.attribute.NumericAttribute
Copy with a new min value.
withName(String) - Method in class org.apache.spark.ml.attribute.Attribute
Copy with a new name.
withName(String) - Method in class org.apache.spark.ml.attribute.BinaryAttribute
 
withName(String) - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
withName(String) - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
withName(String) - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
withName(String) - Static method in class org.apache.spark.mllib.tree.configuration.Algo
 
withName(String) - Static method in class org.apache.spark.mllib.tree.configuration.EnsembleCombiningStrategy
 
withName(String) - Static method in class org.apache.spark.mllib.tree.configuration.FeatureType
 
withName(String) - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
 
withName(String) - Static method in class org.apache.spark.rdd.CheckpointState
 
withName(String) - Static method in class org.apache.spark.rdd.DeterministicLevel
 
withName(String) - Static method in class org.apache.spark.scheduler.SchedulingMode
 
withName(String) - Static method in class org.apache.spark.scheduler.TaskLocality
 
withName(String) - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
Updates UserDefinedFunction with a given name.
withName(String) - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
 
withName(String) - Static method in class org.apache.spark.TaskState
 
withNullSafe(Function1<Object, Object>) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
withNumValues(int) - Method in class org.apache.spark.ml.attribute.NominalAttribute
Copy with a new numValues and empty values.
withoutIndex() - Method in class org.apache.spark.ml.attribute.Attribute
Copy without the index.
withoutIndex() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
 
withoutIndex() - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
withoutIndex() - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
withoutIndex() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
withoutMax() - Method in class org.apache.spark.ml.attribute.NumericAttribute
Copy without the max value.
withoutMin() - Method in class org.apache.spark.ml.attribute.NumericAttribute
Copy without the min value.
withoutName() - Method in class org.apache.spark.ml.attribute.Attribute
Copy without the name.
withoutName() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
 
withoutName() - Method in class org.apache.spark.ml.attribute.NominalAttribute
 
withoutName() - Method in class org.apache.spark.ml.attribute.NumericAttribute
 
withoutName() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
 
withoutNumValues() - Method in class org.apache.spark.ml.attribute.NominalAttribute
Copy without the numValues.
withoutSparsity() - Method in class org.apache.spark.ml.attribute.NumericAttribute
Copy without the sparsity.
withoutStd() - Method in class org.apache.spark.ml.attribute.NumericAttribute
Copy without the standard deviation.
withoutSummary() - Method in class org.apache.spark.ml.attribute.NumericAttribute
Copy without summary statistics.
withoutValues() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
Copy without the values.
withoutValues() - Method in class org.apache.spark.ml.attribute.NominalAttribute
Copy without the values.
withPathFilter(double, SparkSession, long, Function0<T>) - Static method in class org.apache.spark.ml.image.SamplePathFilter
Sets the HDFS PathFilter flag and then restores it.
withPosition(Option<Object>, Option<Object>) - Method in exception org.apache.spark.sql.AnalysisException
 
withRecursiveFlag(boolean, SparkSession, Function0<T>) - Static method in class org.apache.spark.ml.image.RecursiveFlag
Sets the spark recursive flag and then restores it.
withSparkUI(String, Option<String>, Function1<org.apache.spark.ui.SparkUI, T>) - Method in interface org.apache.spark.status.api.v1.UIRoot
Runs some code with the current SparkUI instance for the app / attempt.
withSparsity(double) - Method in class org.apache.spark.ml.attribute.NumericAttribute
Copy with a new sparsity.
withStd(double) - Method in class org.apache.spark.ml.attribute.NumericAttribute
Copy with a new standard deviation.
withStd() - Method in interface org.apache.spark.ml.feature.StandardScalerParams
Whether to scale the data to unit standard deviation.
withStd() - Method in class org.apache.spark.mllib.feature.StandardScalerModel
 
withUI(Function1<org.apache.spark.ui.SparkUI, T>) - Method in interface org.apache.spark.status.api.v1.BaseAppResource
 
withValues(String, String) - Method in class org.apache.spark.ml.attribute.BinaryAttribute
Copy with new values.
withValues(String, String...) - Method in class org.apache.spark.ml.attribute.NominalAttribute
Copy with new values and empty numValues.
withValues(String[]) - Method in class org.apache.spark.ml.attribute.NominalAttribute
Copy with new values and empty numValues.
withValues(String, Seq<String>) - Method in class org.apache.spark.ml.attribute.NominalAttribute
Copy with new values and empty numValues.
withWatermark(String, String) - Method in class org.apache.spark.sql.Dataset
Defines an event time watermark for this Dataset.
word() - Method in class org.apache.spark.mllib.feature.VocabWord
 
Word2Vec - Class in org.apache.spark.ml.feature
Word2Vec trains a model of Map(String, Vector), i.e.
Word2Vec(String) - Constructor for class org.apache.spark.ml.feature.Word2Vec
 
Word2Vec() - Constructor for class org.apache.spark.ml.feature.Word2Vec
 
Word2Vec - Class in org.apache.spark.mllib.feature
Word2Vec creates vector representation of words in a text corpus.
Word2Vec() - Constructor for class org.apache.spark.mllib.feature.Word2Vec
 
Word2VecBase - Interface in org.apache.spark.ml.feature
Params for Word2Vec and Word2VecModel.
Word2VecModel - Class in org.apache.spark.ml.feature
Model fitted by Word2Vec.
Word2VecModel - Class in org.apache.spark.mllib.feature
Word2Vec model param: wordIndex maps each word to an index, which can retrieve the corresponding vector from wordVectors param: wordVectors array of length numWords * vectorSize, vector corresponding to the word mapped with index i can be retrieved by the slice (i * vectorSize, i * vectorSize + vectorSize)
Word2VecModel(Map<String, float[]>) - Constructor for class org.apache.spark.mllib.feature.Word2VecModel
 
Word2VecModel.Word2VecModelWriter$ - Class in org.apache.spark.ml.feature
 
Word2VecModelWriter$() - Constructor for class org.apache.spark.ml.feature.Word2VecModel.Word2VecModelWriter$
 
workerId() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveWorker
 
workerRemoved(String, String, String) - Method in interface org.apache.spark.scheduler.TaskScheduler
Process a removed worker
Workspace(int) - Constructor for class org.apache.spark.mllib.optimization.NNLS.Workspace
 
wrap(Object, ObjectInspector, DataType) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
wrap(InternalRow, Function1<Object, Object>[], Object[], DataType[]) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
wrap(Seq<Object>, Function1<Object, Object>[], Object[], DataType[]) - Method in interface org.apache.spark.sql.hive.HiveInspectors
 
wrap(Object, ObjectInspector, DataType) - Static method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
wrap(InternalRow, Function1<Object, Object>[], Object[], DataType[]) - Static method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
wrap(Seq<Object>, Function1<Object, Object>[], Object[], DataType[]) - Static method in class org.apache.spark.sql.hive.orc.OrcFileFormat
 
wrapperClass() - Static method in class org.apache.spark.serializer.JavaIterableWrapperSerializer
 
wrapperFor(ObjectInspector, DataType) - Method in interface org.apache.spark.sql.hive.HiveInspectors
Wraps with Hive types based on object inspector.
wrapperToFileSinkDesc(HiveShim.ShimFileSinkDesc) - Static method in class org.apache.spark.sql.hive.HiveShim
 
wrapRDD(RDD<Double>) - Method in class org.apache.spark.api.java.JavaDoubleRDD
 
wrapRDD(RDD<Tuple2<K, V>>) - Method in class org.apache.spark.api.java.JavaPairRDD
 
wrapRDD(RDD<T>) - Method in class org.apache.spark.api.java.JavaRDD
 
wrapRDD(RDD<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
 
wrapRDD(RDD<T>) - Method in class org.apache.spark.streaming.api.java.JavaDStream
 
wrapRDD(RDD<T>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
 
wrapRDD(RDD<Tuple2<K, V>>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
 
write(Tuple2<K, V>) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
 
write(RDD<Tuple2<K, V>>, HadoopWriteConfigUtil<K, V>, ClassTag<V>) - Static method in class org.apache.spark.internal.io.SparkHadoopWriter
Basic work flow of this command is: 1.
write(int) - Method in class org.apache.spark.io.SnappyOutputStreamWrapper
 
write(byte[]) - Method in class org.apache.spark.io.SnappyOutputStreamWrapper
 
write(byte[], int, int) - Method in class org.apache.spark.io.SnappyOutputStreamWrapper
 
write() - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
 
write() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
 
write() - Method in class org.apache.spark.ml.classification.LinearSVCModel
 
write() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
Returns a MLWriter instance for this ML instance.
write() - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
 
write() - Method in class org.apache.spark.ml.classification.NaiveBayesModel
 
write() - Method in class org.apache.spark.ml.classification.OneVsRest
 
write() - Method in class org.apache.spark.ml.classification.OneVsRestModel
 
write() - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
 
write() - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
 
write() - Method in class org.apache.spark.ml.clustering.DistributedLDAModel
 
write() - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
Returns a MLWriter instance for this ML instance.
write(String, SparkSession, Map<String, String>, PipelineStage) - Method in class org.apache.spark.ml.clustering.InternalKMeansModelWriter
 
write() - Method in class org.apache.spark.ml.clustering.KMeansModel
Returns a GeneralMLWriter instance for this ML instance.
write() - Method in class org.apache.spark.ml.clustering.LocalLDAModel
 
write(String, SparkSession, Map<String, String>, PipelineStage) - Method in class org.apache.spark.ml.clustering.PMMLKMeansModelWriter
 
write() - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
 
write() - Method in class org.apache.spark.ml.feature.ChiSqSelectorModel
 
write() - Method in class org.apache.spark.ml.feature.ColumnPruner
 
write() - Method in class org.apache.spark.ml.feature.CountVectorizerModel
 
write() - Method in class org.apache.spark.ml.feature.IDFModel
 
write() - Method in class org.apache.spark.ml.feature.ImputerModel
 
write() - Method in class org.apache.spark.ml.feature.MaxAbsScalerModel
 
write() - Method in class org.apache.spark.ml.feature.MinHashLSHModel
 
write() - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
 
write() - Method in class org.apache.spark.ml.feature.OneHotEncoderModel
 
write() - Method in class org.apache.spark.ml.feature.PCAModel
 
write() - Method in class org.apache.spark.ml.feature.RFormulaModel
 
write() - Method in class org.apache.spark.ml.feature.StandardScalerModel
 
write() - Method in class org.apache.spark.ml.feature.StringIndexerModel
 
write() - Method in class org.apache.spark.ml.feature.VectorAttributeRewriter
 
write() - Method in class org.apache.spark.ml.feature.VectorIndexerModel
 
write() - Method in class org.apache.spark.ml.feature.Word2VecModel
 
write() - Method in class org.apache.spark.ml.fpm.FPGrowthModel
 
write() - Method in class org.apache.spark.ml.Pipeline
 
write() - Method in class org.apache.spark.ml.PipelineModel
 
write() - Method in class org.apache.spark.ml.recommendation.ALSModel
 
write() - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
 
write() - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
 
write() - Method in class org.apache.spark.ml.regression.GBTRegressionModel
 
write() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
Returns a MLWriter instance for this ML instance.
write(String, SparkSession, Map<String, String>, PipelineStage) - Method in class org.apache.spark.ml.regression.InternalLinearRegressionModelWriter
 
write() - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
 
write() - Method in class org.apache.spark.ml.regression.LinearRegressionModel
Returns a GeneralMLWriter instance for this ML instance.
write(String, SparkSession, Map<String, String>, PipelineStage) - Method in class org.apache.spark.ml.regression.PMMLLinearRegressionModelWriter
 
write() - Method in class org.apache.spark.ml.regression.RandomForestRegressionModel
 
write() - Method in class org.apache.spark.ml.tuning.CrossValidator
 
write() - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
 
write() - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
 
write() - Method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
 
write() - Method in interface org.apache.spark.ml.util.DefaultParamsWritable
 
write() - Method in interface org.apache.spark.ml.util.GeneralMLWritable
Returns an MLWriter instance for this ML instance.
write() - Method in interface org.apache.spark.ml.util.MLWritable
Returns an MLWriter instance for this ML instance.
write(String, SparkSession, Map<String, String>, PipelineStage) - Method in interface org.apache.spark.ml.util.MLWriterFormat
Function to write the provided pipeline stage out.
write(Kryo, Output, Iterable<?>) - Method in class org.apache.spark.serializer.JavaIterableWrapperSerializer
 
write() - Method in class org.apache.spark.sql.Dataset
Interface for saving the content of the non-streaming Dataset out into external storage.
write(InternalRow) - Method in class org.apache.spark.sql.hive.execution.HiveOutputWriter
 
write(T) - Method in interface org.apache.spark.sql.sources.v2.writer.DataWriter
Writes one record.
write(ByteBuffer) - Method in class org.apache.spark.storage.CountingWritableChannel
 
write(int) - Method in class org.apache.spark.storage.TimeTrackingOutputStream
 
write(byte[]) - Method in class org.apache.spark.storage.TimeTrackingOutputStream
 
write(byte[], int, int) - Method in class org.apache.spark.storage.TimeTrackingOutputStream
 
write(ByteBuffer, long) - Method in class org.apache.spark.streaming.util.WriteAheadLog
Write the record to the log and return a record handle, which contains all the information necessary to read back the written record.
WRITE_TIME() - Method in class org.apache.spark.InternalAccumulator.shuffleWrite$
 
WriteAheadLog - Class in org.apache.spark.streaming.util
:: DeveloperApi :: This abstract class represents a write ahead log (aka journal) that is used by Spark Streaming to save the received data (by receivers) and associated metadata to a reliable storage, so that they can be recovered after driver failures.
WriteAheadLog() - Constructor for class org.apache.spark.streaming.util.WriteAheadLog
 
WriteAheadLogRecordHandle - Class in org.apache.spark.streaming.util
:: DeveloperApi :: This abstract class represents a handle that refers to a record written in a WriteAheadLog.
WriteAheadLogRecordHandle() - Constructor for class org.apache.spark.streaming.util.WriteAheadLogRecordHandle
 
WriteAheadLogUtils - Class in org.apache.spark.streaming.util
A helper class with utility functions related to the WriteAheadLog interface
WriteAheadLogUtils() - Constructor for class org.apache.spark.streaming.util.WriteAheadLogUtils
 
writeAll(Iterator<T>, ClassTag<T>) - Method in class org.apache.spark.serializer.SerializationStream
 
writeBoolean(DataOutputStream, boolean) - Static method in class org.apache.spark.api.r.SerDe
 
writeBooleanArr(DataOutputStream, boolean[]) - Static method in class org.apache.spark.api.r.SerDe
 
writeByteBuffer(ByteBuffer, DataOutput) - Static method in class org.apache.spark.util.Utils
Primitive often used when writing ByteBuffer to DataOutput
writeByteBuffer(ByteBuffer, OutputStream) - Static method in class org.apache.spark.util.Utils
Primitive often used when writing ByteBuffer to OutputStream
writeBytes(DataOutputStream, byte[]) - Static method in class org.apache.spark.api.r.SerDe
 
writeBytes() - Method in class org.apache.spark.status.api.v1.ShuffleWriteMetricDistributions
 
writeDate(DataOutputStream, Date) - Static method in class org.apache.spark.api.r.SerDe
 
writeDouble(DataOutputStream, double) - Static method in class org.apache.spark.api.r.SerDe
 
writeDoubleArr(DataOutputStream, double[]) - Static method in class org.apache.spark.api.r.SerDe
 
writeEventLogs(String, Option<String>, ZipOutputStream) - Method in interface org.apache.spark.status.api.v1.UIRoot
Write the event logs for the given app to the ZipOutputStream instance.
writeExternal(ObjectOutput) - Method in class org.apache.spark.serializer.JavaSerializer
 
writeExternal(ObjectOutput) - Method in class org.apache.spark.storage.BlockManagerId
 
writeExternal(ObjectOutput) - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
 
writeExternal(ObjectOutput) - Method in class org.apache.spark.storage.StorageLevel
 
writeInt(DataOutputStream, int) - Static method in class org.apache.spark.api.r.SerDe
 
writeIntArr(DataOutputStream, int[]) - Static method in class org.apache.spark.api.r.SerDe
 
writeJObj(DataOutputStream, Object, JVMObjectTracker) - Static method in class org.apache.spark.api.r.SerDe
 
writeKey(T, ClassTag<T>) - Method in class org.apache.spark.serializer.SerializationStream
Writes the object representing the key of a key-value pair.
writeObject(DataOutputStream, Object, JVMObjectTracker) - Static method in class org.apache.spark.api.r.SerDe
 
writeObject(T, ClassTag<T>) - Method in class org.apache.spark.serializer.SerializationStream
The most general-purpose method to write an object.
WriterCommitMessage - Interface in org.apache.spark.sql.sources.v2.writer
A commit message returned by DataWriter.commit() and will be sent back to the driver side as the input parameter of DataSourceWriter.commit(WriterCommitMessage[]).
writeRecords() - Method in class org.apache.spark.status.api.v1.ShuffleWriteMetricDistributions
 
writeSqlObject(DataOutputStream, Object) - Static method in class org.apache.spark.sql.api.r.SQLUtils
 
writeStream() - Method in class org.apache.spark.sql.Dataset
Interface for saving the content of the streaming Dataset out into external storage.
writeString(DataOutputStream, String) - Static method in class org.apache.spark.api.r.SerDe
 
writeStringArr(DataOutputStream, String[]) - Static method in class org.apache.spark.api.r.SerDe
 
WriteSupport - Interface in org.apache.spark.sql.sources.v2
A mix-in interface for DataSourceV2.
writeTime(DataOutputStream, Time) - Static method in class org.apache.spark.api.r.SerDe
 
writeTime(DataOutputStream, Timestamp) - Static method in class org.apache.spark.api.r.SerDe
 
writeTime() - Method in class org.apache.spark.status.api.v1.ShuffleWriteMetricDistributions
 
writeTime() - Method in class org.apache.spark.status.api.v1.ShuffleWriteMetrics
 
writeTo(OutputStream) - Method in class org.apache.spark.util.sketch.BloomFilter
Writes out this BloomFilter to an output stream in binary format.
writeTo(OutputStream) - Method in class org.apache.spark.util.sketch.CountMinSketch
Writes out this CountMinSketch to an output stream in binary format.
writeType(DataOutputStream, String) - Static method in class org.apache.spark.api.r.SerDe
 
writeValue(T, ClassTag<T>) - Method in class org.apache.spark.serializer.SerializationStream
Writes the object representing the value of a key-value pair.

X

x() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
 

Y

year(Column) - Static method in class org.apache.spark.sql.functions
Extracts the year as an integer from a given date/timestamp/string.

Z

zero() - Method in class org.apache.spark.Accumulable
Deprecated.
 
zero(R) - Method in interface org.apache.spark.AccumulableParam
Deprecated.
Return the "zero" (identity) value for an accumulator type, given its initial value.
zero(double) - Method in class org.apache.spark.AccumulatorParam.DoubleAccumulatorParam$
Deprecated.
 
zero(float) - Method in class org.apache.spark.AccumulatorParam.FloatAccumulatorParam$
Deprecated.
 
zero(int) - Method in class org.apache.spark.AccumulatorParam.IntAccumulatorParam$
Deprecated.
 
zero(long) - Method in class org.apache.spark.AccumulatorParam.LongAccumulatorParam$
Deprecated.
 
zero(String) - Method in class org.apache.spark.AccumulatorParam.StringAccumulatorParam$
Deprecated.
 
zero(int, int) - Static method in class org.apache.spark.mllib.clustering.ExpectationSum
 
zero() - Method in class org.apache.spark.sql.expressions.Aggregator
A zero value for this aggregation.
zeros(int, int) - Static method in class org.apache.spark.ml.linalg.DenseMatrix
Generate a DenseMatrix consisting of zeros.
zeros(int, int) - Static method in class org.apache.spark.ml.linalg.Matrices
Generate a Matrix consisting of zeros.
zeros(int) - Static method in class org.apache.spark.ml.linalg.Vectors
Creates a vector of all zeros.
zeros(int, int) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
Generate a DenseMatrix consisting of zeros.
zeros(int, int) - Static method in class org.apache.spark.mllib.linalg.Matrices
Generate a Matrix consisting of zeros.
zeros(int) - Static method in class org.apache.spark.mllib.linalg.Vectors
Creates a vector of all zeros.
zip(JavaRDDLike<U, ?>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Zips this RDD with another one, returning key-value pairs with the first element in each RDD, second element in each RDD, etc.
zip(RDD<U>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
Zips this RDD with another one, returning key-value pairs with the first element in each RDD, second element in each RDD, etc.
zipPartitions(JavaRDDLike<U, ?>, FlatMapFunction2<Iterator<T>, Iterator<U>, V>) - Method in interface org.apache.spark.api.java.JavaRDDLike
Zip this RDD's partitions with one (or more) RDD(s) and return a new RDD by applying a function to the zipped partitions.
zipPartitions(RDD<B>, boolean, Function2<Iterator<T>, Iterator<B>, Iterator<V>>, ClassTag<B>, ClassTag<V>) - Method in class org.apache.spark.rdd.RDD
Zip this RDD's partitions with one (or more) RDD(s) and return a new RDD by applying a function to the zipped partitions.
zipPartitions(RDD<B>, Function2<Iterator<T>, Iterator<B>, Iterator<V>>, ClassTag<B>, ClassTag<V>) - Method in class org.apache.spark.rdd.RDD
 
zipPartitions(RDD<B>, RDD<C>, boolean, Function3<Iterator<T>, Iterator<B>, Iterator<C>, Iterator<V>>, ClassTag<B>, ClassTag<C>, ClassTag<V>) - Method in class org.apache.spark.rdd.RDD
 
zipPartitions(RDD<B>, RDD<C>, Function3<Iterator<T>, Iterator<B>, Iterator<C>, Iterator<V>>, ClassTag<B>, ClassTag<C>, ClassTag<V>) - Method in class org.apache.spark.rdd.RDD
 
zipPartitions(RDD<B>, RDD<C>, RDD<D>, boolean, Function4<Iterator<T>, Iterator<B>, Iterator<C>, Iterator<D>, Iterator<V>>, ClassTag<B>, ClassTag<C>, ClassTag<D>, ClassTag<V>) - Method in class org.apache.spark.rdd.RDD
 
zipPartitions(RDD<B>, RDD<C>, RDD<D>, Function4<Iterator<T>, Iterator<B>, Iterator<C>, Iterator<D>, Iterator<V>>, ClassTag<B>, ClassTag<C>, ClassTag<D>, ClassTag<V>) - Method in class org.apache.spark.rdd.RDD
 
zipWithIndex() - Method in interface org.apache.spark.api.java.JavaRDDLike
Zips this RDD with its element indices.
zipWithIndex() - Method in class org.apache.spark.rdd.RDD
Zips this RDD with its element indices.
zipWithUniqueId() - Method in interface org.apache.spark.api.java.JavaRDDLike
Zips this RDD with generated unique Long ids.
zipWithUniqueId() - Method in class org.apache.spark.rdd.RDD
Zips this RDD with generated unique Long ids.
ZStdCompressionCodec - Class in org.apache.spark.io
:: DeveloperApi :: ZStandard implementation of CompressionCodec.
ZStdCompressionCodec(SparkConf) - Constructor for class org.apache.spark.io.ZStdCompressionCodec
 

_

_1() - Method in class org.apache.spark.util.MutablePair
 
_2() - Method in class org.apache.spark.util.MutablePair
 
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