- abort(WriterCommitMessage[]) - Method in interface org.apache.spark.sql.sources.v2.writer.DataSourceWriter
-
- 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
-
- 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
-
- Accumulable<R,T> - Class in org.apache.spark
-
- 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
-
- accumulable(T, String, AccumulableParam<T, R>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulable(R, AccumulableParam<R, T>) - Method in class org.apache.spark.SparkContext
-
- accumulable(R, String, AccumulableParam<R, T>) - Method in class org.apache.spark.SparkContext
-
- accumulableCollection(R, Function1<R, Growable<T>>, ClassTag<R>) - Method in class org.apache.spark.SparkContext
-
- 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
-
- 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
-
- accumulator(int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulator(int, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulator(double) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulator(double, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulator(T, AccumulatorParam<T>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulator(T, String, AccumulatorParam<T>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulator(T, AccumulatorParam<T>) - Method in class org.apache.spark.SparkContext
-
- accumulator(T, String, AccumulatorParam<T>) - Method in class org.apache.spark.SparkContext
-
- 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
-
- AccumulatorParam.DoubleAccumulatorParam$ - Class in org.apache.spark
-
- AccumulatorParam.FloatAccumulatorParam$ - Class in org.apache.spark
-
- AccumulatorParam.IntAccumulatorParam$ - Class in org.apache.spark
-
- AccumulatorParam.LongAccumulatorParam$ - Class in org.apache.spark
-
- AccumulatorParam.StringAccumulatorParam$ - Class in org.apache.spark
-
- 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
-
- 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
-
- add(T) - Method in class org.apache.spark.Accumulable
-
Deprecated.
Add more data to this accumulator / accumulable
- add(T) - Static method in class org.apache.spark.Accumulator
-
Deprecated.
- 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(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
-
- 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
.
- 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(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(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 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(L) - Static method in class org.apache.spark.scheduler.AsyncEventQueue
-
- addListener(StreamingQueryListener) - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
-
- 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, org.apache.spark.scheduler.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
-
- 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(org.apache.spark.scheduler.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
-
- addStreamingListener(StreamingListener) - Method in class org.apache.spark.streaming.StreamingContext
-
- addString(StringBuilder, String, String, String) - Static method in class org.apache.spark.sql.types.StructType
-
- addString(StringBuilder, String) - Static method in class org.apache.spark.sql.types.StructType
-
- addString(StringBuilder) - Static method in class org.apache.spark.sql.types.StructType
-
- 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
.
- addSuppressed(Throwable) - Static method in exception org.apache.spark.sql.AnalysisException
-
- 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.
- addTime() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- addTime() - Method in class org.apache.spark.status.LiveExecutor
-
- 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
-
- 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
-
- 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>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- 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>) - Static method in class org.apache.spark.api.r.RRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- 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".
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- aggregate(Function0<B>, Function2<B, A, B>, Function2<B, B, B>) - Static method in class org.apache.spark.sql.types.StructType
-
- 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.
- aggregateMessages(Function1<EdgeContext<VD, ED, A>, BoxedUnit>, Function2<A, A, A>, TripletFields, ClassTag<A>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
- aggregateMessages$default$3() - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
- 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() - Static method in class org.apache.spark.ml.classification.LinearSVC
-
- aggregationDepth() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- aggregationDepth() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- aggregationDepth() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- aggregationDepth() - Method in interface org.apache.spark.ml.param.shared.HasAggregationDepth
-
Param for suggested depth for treeAggregate (>= 2).
- aggregationDepth() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- aggregationDepth() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- aggregationDepth() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- aggregationDepth() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- 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.
- aliases - Variable in class org.apache.spark.util.kvstore.LevelDB.TypeAliases
-
- All - Static variable in class org.apache.spark.graphx.TripletFields
-
Expose all the fields (source, edge, and destination).
- allAttributes() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- allAttributes() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- allAttributes() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- allAttributes() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- 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.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.
- 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.
- analyzed() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- analyzed() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- analyzed() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- 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
-
- andThen(Function1<B, C>) - Static method in class org.apache.spark.sql.types.StructType
-
- 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
-
- 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
-
- appId() - Method in class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- APPLICATION_EXECUTOR_LIMIT() - Static method in class org.apache.spark.ui.ToolTips
-
- 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 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(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(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) - Static 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(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(int, int) - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- apply(int) - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- 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) - Static 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(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(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
-
- apply(long, String, Option<String>, String) - Static method in class org.apache.spark.scheduler.AccumulableInfo
-
- apply(long, String, String) - Static method in class org.apache.spark.scheduler.AccumulableInfo
-
- 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(long, TaskMetrics) - Static method in class org.apache.spark.scheduler.RuntimePercentage
-
- apply(int) - Static method in class org.apache.spark.scheduler.SchedulingMode
-
- 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 Column
s as input arguments.
- apply(Seq<Column>) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
-
Creates a Column
for this UDAF using given Column
s 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(int) - 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(int) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- apply(int) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- apply(int) - 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.RelationConversions
-
- apply(LogicalPlan) - Method in class org.apache.spark.sql.hive.ResolveHiveSerdeTable
-
- 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(String) - Static method in class org.apache.spark.sql.streaming.ProcessingTime
-
- apply(Duration) - Static method in class org.apache.spark.sql.streaming.ProcessingTime
-
- apply(DataType) - Static method in class org.apache.spark.sql.types.ArrayType
-
Construct a
ArrayType
object with the given element type.
- 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(String) - Method in class org.apache.spark.sql.types.StructType
-
- apply(Set<String>) - Method in class org.apache.spark.sql.types.StructType
-
Returns a
StructType
containing
StructField
s of the given names, preserving the
original order of fields.
- apply(int) - Method in class org.apache.spark.sql.types.StructType
-
- 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
-
- apply(ObjectInput) - Static method in class org.apache.spark.storage.BlockManagerId
-
- 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(long) - Static method in class org.apache.spark.streaming.Milliseconds
-
- apply(long) - Static method in class org.apache.spark.streaming.Minutes
-
- apply(int) - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
-
- apply(long) - Static method in class org.apache.spark.streaming.Seconds
-
- 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
-
- applyOrElse(A1, Function1<A1, B1>) - Static method in class org.apache.spark.sql.types.StructType
-
- applySchema(RDD<Row>, StructType) - Method in class org.apache.spark.sql.SQLContext
-
- applySchema(JavaRDD<Row>, StructType) - Method in class org.apache.spark.sql.SQLContext
-
- applySchema(RDD<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
-
- applySchema(JavaRDD<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
-
- 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
-
- approxCountDistinct(String) - Static method in class org.apache.spark.sql.functions
-
- approxCountDistinct(Column, double) - Static method in class org.apache.spark.sql.functions
-
- approxCountDistinct(String, double) - Static method in class org.apache.spark.sql.functions
-
- ApproxHist() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
-
- approxNearestNeighbors(Dataset<?>, Vector, int, String) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- approxNearestNeighbors(Dataset<?>, Vector, int) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- approxNearestNeighbors(Dataset<?>, Vector, int, String) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- approxNearestNeighbors(Dataset<?>, Vector, int) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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.
- approxSimilarityJoin(Dataset<?>, Dataset<?>, double, String) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- approxSimilarityJoin(Dataset<?>, Dataset<?>, double) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- approxSimilarityJoin(Dataset<?>, Dataset<?>, double, String) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- approxSimilarityJoin(Dataset<?>, Dataset<?>, double) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
- argString() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- argString() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- argString() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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.
- asCode() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- asCode() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- asCode() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- asCode() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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
-
- asRDDId() - Static method in class org.apache.spark.storage.BroadcastBlockId
-
- asRDDId() - Static method in class org.apache.spark.storage.RDDBlockId
-
- asRDDId() - Static method in class org.apache.spark.storage.ShuffleBlockId
-
- asRDDId() - Static method in class org.apache.spark.storage.ShuffleDataBlockId
-
- asRDDId() - Static method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- asRDDId() - Static method in class org.apache.spark.storage.StreamBlockId
-
- asRDDId() - Static method in class org.apache.spark.storage.TaskResultBlockId
-
- 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
-
- attemptId() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- 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
-
- 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
- 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() - Static method in class org.apache.spark.api.r.RRDD
-
- 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() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- barrier() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- barrier() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- barrier() - Static method in class org.apache.spark.graphx.VertexRDD
-
- barrier() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- barrier() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- barrier() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- barrier() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- 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.
- barrier() - Static method in class org.apache.spark.rdd.UnionRDD
-
- 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.
- 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.
- 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
-
- BasicBlockReplicationPolicy - Class in org.apache.spark.storage
-
- BasicBlockReplicationPolicy() - Constructor for class org.apache.spark.storage.BasicBlockReplicationPolicy
-
- 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.
- basicWriteJobStatsTracker(Configuration) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- basicWriteJobStatsTracker(Configuration) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- basicWriteJobStatsTracker(Configuration) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- 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() - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- binary() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- 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
-
- 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.
- 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 - 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
-
- 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
-
- 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() - Method in class org.apache.spark.storage.EncryptedManagedBuffer
-
- blockedByLock() - Method in class org.apache.spark.status.api.v1.ThreadStackTrace
-
- blockedByThreadId() - Method in class org.apache.spark.status.api.v1.ThreadStackTrace
-
- 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
-
- 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 an unique identifier for a BlockManager.
- 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() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- 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 - 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
-
- 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
-
- 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 ::
- 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() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
-
- bucketLength() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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$
-
- build(DecisionTreeModel, int) - Method in class org.apache.spark.ml.tree.EnsembleModelReadWrite.EnsembleNodeData$
-
- build() - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
-
Builds and returns all combinations of parameters specified by the param grid.
- build() - Static method in class org.apache.spark.sql.hive.HiveSessionStateBuilder
-
- build() - Method in class org.apache.spark.sql.types.MetadataBuilder
-
- build() - Method in interface org.apache.spark.storage.memory.MemoryEntryBuilder
-
- builder() - Static method in class org.apache.spark.sql.SparkSession
-
- Builder() - Constructor for class org.apache.spark.sql.SparkSession.Builder
-
- buildErrorResponse(Response.Status, String) - Static method in class org.apache.spark.ui.UIUtils
-
- buildReader(SparkSession, StructType, StructType, StructType, Seq<Filter>, Map<String, String>, Configuration) - Method in class org.apache.spark.sql.hive.orc.OrcFileFormat
-
- buildReaderWithPartitionValues(SparkSession, StructType, StructType, StructType, Seq<Filter>, Map<String, String>, Configuration) - Static 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
-
- 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 - Static variable in class org.apache.spark.sql.types.DataTypes
-
Gets the ByteType object.
- 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() - Static method in class org.apache.spark.api.r.RRDD
-
- cache() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- 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() - Static method in class org.apache.spark.graphx.VertexRDD
-
- cache() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
-
Caches the underlying RDD.
- cache() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- cache() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- cache() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- cache() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- cache() - Method in class org.apache.spark.rdd.RDD
-
Persist this RDD with the default storage level (MEMORY_ONLY
).
- cache() - Static method in class org.apache.spark.rdd.UnionRDD
-
- 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() - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- 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() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- cache() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- cache() - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- cache() - Method in class org.apache.spark.streaming.dstream.DStream
-
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
- cacheNodeIds() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- 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 - 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.
- canEqual(Object) - Static method in class org.apache.spark.Aggregator
-
- canEqual(Object) - Static method in class org.apache.spark.CleanAccum
-
- canEqual(Object) - Static method in class org.apache.spark.CleanBroadcast
-
- canEqual(Object) - Static method in class org.apache.spark.CleanCheckpoint
-
- canEqual(Object) - Static method in class org.apache.spark.CleanRDD
-
- canEqual(Object) - Static method in class org.apache.spark.CleanShuffle
-
- canEqual(Object) - Static method in class org.apache.spark.ContextBarrierId
-
- canEqual(Object) - Static method in class org.apache.spark.ExceptionFailure
-
- canEqual(Object) - Static method in class org.apache.spark.ExecutorLostFailure
-
- canEqual(Object) - Static method in class org.apache.spark.ExecutorRegistered
-
- canEqual(Object) - Static method in class org.apache.spark.ExecutorRemoved
-
- canEqual(Object) - Static method in class org.apache.spark.ExpireDeadHosts
-
- canEqual(Object) - Static method in class org.apache.spark.FetchFailed
-
- canEqual(Object) - Static method in class org.apache.spark.graphx.Edge
-
- canEqual(Object) - Static method in class org.apache.spark.ml.clustering.ClusterData
-
- canEqual(Object) - Static method in class org.apache.spark.ml.feature.Dot
-
- canEqual(Object) - Static method in class org.apache.spark.ml.feature.LabeledPoint
-
- canEqual(Object) - Static method in class org.apache.spark.ml.param.ParamPair
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$.Data
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$.Data
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$.Data
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.feature.VocabWord
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.linalg.distributed.IndexedRow
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.linalg.distributed.MatrixEntry
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.linalg.QRDecomposition
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.linalg.SingularValueDecomposition
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.recommendation.Rating
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$.Data
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.regression.LabeledPoint
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.stat.test.BinarySample
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.tree.model.Split
-
- 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.AccumulableInfo
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.AllJobsCancelled
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.BlacklistedExecutor
-
- 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.local.KillTask
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.local.ReviveOffers
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.local.StatusUpdate
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.local.StopExecutor
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.ResubmitFailedStages
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.RuntimePercentage
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerApplicationEnd
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerRemoved
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerBlockUpdated
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerEnvironmentUpdate
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorAdded
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklisted
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorBlacklistedForStage
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorRemoved
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorUnblacklisted
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerJobEnd
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerJobStart
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerLogStart
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerNodeBlacklisted
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerNodeBlacklistedForStage
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerNodeUnblacklisted
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerSpeculativeTaskSubmitted
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerStageCompleted
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerStageSubmitted
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerTaskGettingResult
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerTaskStart
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerUnpersistRDD
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.StopCoordinator
-
- canEqual(Object) - Static method in class org.apache.spark.sql.DatasetHolder
-
- canEqual(Object) - Static method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
- canEqual(Object) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- canEqual(Object) - Static method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- canEqual(Object) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- canEqual(Object) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- canEqual(Object) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- canEqual(Object) - Static method in class org.apache.spark.sql.hive.RelationConversions
-
- canEqual(Object) - Static method in class org.apache.spark.sql.jdbc.JdbcType
-
- 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.sources.And
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.EqualNullSafe
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.EqualTo
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.GreaterThan
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.GreaterThanOrEqual
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.In
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.IsNotNull
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.IsNull
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.LessThan
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.LessThanOrEqual
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.Not
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.Or
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.StringContains
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.StringEndsWith
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.StringStartsWith
-
- canEqual(Object) - Static method in class org.apache.spark.sql.streaming.ProcessingTime
-
Deprecated.
- canEqual(Object) - Static method in class org.apache.spark.sql.types.ArrayType
-
- canEqual(Object) - Static method in class org.apache.spark.sql.types.CharType
-
- canEqual(Object) - Static method in class org.apache.spark.sql.types.DecimalType
-
- canEqual(Object) - Static method in class org.apache.spark.sql.types.MapType
-
- canEqual(Object) - Static method in class org.apache.spark.sql.types.ObjectType
-
- canEqual(Object) - Static method in class org.apache.spark.sql.types.StructField
-
- canEqual(Object) - Static method in class org.apache.spark.sql.types.StructType
-
- canEqual(Object) - Static method in class org.apache.spark.sql.types.VarcharType
-
- canEqual(Object) - Static method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- canEqual(Object) - Static method in class org.apache.spark.status.api.v1.ApplicationInfo
-
- canEqual(Object) - Static method in class org.apache.spark.status.api.v1.StackTrace
-
- canEqual(Object) - Static method in class org.apache.spark.status.api.v1.ThreadStackTrace
-
- canEqual(Object) - Static method in class org.apache.spark.StopMapOutputTracker
-
- canEqual(Object) - Static method in class org.apache.spark.storage.BlockStatus
-
- canEqual(Object) - Static method in class org.apache.spark.storage.BlockUpdatedInfo
-
- canEqual(Object) - Static method in class org.apache.spark.storage.BroadcastBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.storage.memory.DeserializedMemoryEntry
-
- canEqual(Object) - Static method in class org.apache.spark.storage.memory.SerializedMemoryEntry
-
- canEqual(Object) - Static method in class org.apache.spark.storage.RDDBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.storage.ShuffleBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.storage.ShuffleDataBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.storage.StreamBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.storage.TaskResultBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.Duration
-
- 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.BatchInfo
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StopAllReceivers
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchCompleted
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchStarted
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchSubmitted
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationCompleted
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationStarted
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverError
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStopped
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerStreamingStarted
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamInputInfo
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.Time
-
- canEqual(Object) - Static method in class org.apache.spark.Success
-
- canEqual(Object) - Static method in class org.apache.spark.TaskCommitDenied
-
- canEqual(Object) - Static method in class org.apache.spark.TaskKilled
-
- 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) - Static method in class org.apache.spark.util.MethodIdentifier
-
- 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
-
- canonicalized() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- canonicalized() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- canonicalized() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- canonicalized() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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, ?>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- cartesian(JavaRDDLike<U, ?>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- cartesian(JavaRDDLike<U, ?>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- 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>) - Static method in class org.apache.spark.api.r.RRDD
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- 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
.
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- 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() - Static method in class org.apache.spark.sql.types.CharType
-
- 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.DecimalType
-
- 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.HiveStringType
-
- 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.NumericType
-
- catalogString() - Static method in class org.apache.spark.sql.types.ObjectType
-
- 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
-
- catalogString() - Static method in class org.apache.spark.sql.types.VarcharType
-
- 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() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- censorCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- 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.
- 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() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- checkpoint() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- checkpoint() - Static method in class org.apache.spark.api.java.JavaRDD
-
- checkpoint() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Mark this RDD for checkpointing.
- checkpoint() - Static method in class org.apache.spark.api.r.RRDD
-
- checkpoint() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- 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() - Static method in class org.apache.spark.graphx.VertexRDD
-
- checkpoint() - Method in class org.apache.spark.rdd.HadoopRDD
-
- checkpoint() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- checkpoint() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- checkpoint() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- checkpoint() - Method in class org.apache.spark.rdd.RDD
-
Mark this RDD for checkpointing.
- checkpoint() - Static method in class org.apache.spark.rdd.UnionRDD
-
- 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) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- checkpoint(Duration) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Enable periodic checkpointing of RDDs of this DStream.
- checkpoint(Duration) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- checkpoint(Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- checkpoint(Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- checkpoint(Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- checkpoint(Duration) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- 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.
- Checkpointed() - Static method in class org.apache.spark.rdd.CheckpointState
-
- CheckpointingInProgress() - Static method in class org.apache.spark.rdd.CheckpointState
-
- checkpointInterval() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- checkpointInterval() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- checkpointInterval() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- checkpointInterval() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.clustering.LDA
-
- checkpointInterval() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- checkpointInterval() - Method in interface org.apache.spark.ml.param.shared.HasCheckpointInterval
-
Param for set checkpoint interval (>= 1) or disable checkpoint (-1).
- checkpointInterval() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- checkpointInterval() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- checkpointInterval() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- checkpointInterval() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- 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.
- checkState(boolean, Function0<String>) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
- 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.
- children() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- children() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- children() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- children() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- childrenResolved() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- childrenResolved() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- childrenResolved() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- classifier() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- 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() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- classTag() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- 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
-
- 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
-
- 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<?>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.LinearSVC
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.KMeans
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.LDA
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.PowerIterationClustering
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Binarizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.ColumnPruner
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.DCT
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.FeatureHasher
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.HashingTF
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.IDF
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.IDFModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Imputer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.IndexToString
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Interaction
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.MinHashLSH
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.NGram
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
Deprecated.
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.PCA
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.PCAModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.RFormula
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.SQLTransformer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorSizeHint
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- clear(Param<?>) - Method in interface org.apache.spark.ml.param.Params
-
Clears the user-supplied value for the input param.
- clear(Param<?>) - Static method in class org.apache.spark.ml.Pipeline
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.PipelineModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.recommendation.ALS
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- clear() - Method in class org.apache.spark.sql.util.ExecutionListenerManager
-
- clear() - Static method in class org.apache.spark.util.AccumulatorContext
-
- clearActive() - Static method in class org.apache.spark.sql.SQLContext
-
- 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.
- 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.
- 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 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.
- close() - Method in class org.apache.spark.util.kvstore.InMemoryStore
-
- close() - Method in class org.apache.spark.util.kvstore.LevelDB
-
- closeableIterator() - Method in class org.apache.spark.util.kvstore.KVStoreView
-
Returns an iterator for the current configuration.
- 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
-
- 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, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.api.r.RRDD
-
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- 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, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- 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>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- 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, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- 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.
- coalesce$default$2() - Static method in class org.apache.spark.api.r.RRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- coalesce$default$2() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- coalesce$default$2() - Static method in class org.apache.spark.graphx.VertexRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.api.r.RRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- coalesce$default$3() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- coalesce$default$3() - Static method in class org.apache.spark.graphx.VertexRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.rdd.UnionRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.api.r.RRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- CoarseGrainedClusterMessages - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages
-
- CoarseGrainedClusterMessages.AddWebUIFilter - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.AddWebUIFilter$ - 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(JavaPairDStream<K, W>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- cogroup(JavaPairDStream<K, W>, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- cogroup(JavaPairDStream<K, W>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- cogroup(JavaPairDStream<K, W>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- cogroup(JavaPairDStream<K, W>, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- cogroup(JavaPairDStream<K, W>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- 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() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- coldStartStrategy() - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- 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() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- collect() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- collect() - Static method in class org.apache.spark.api.java.JavaRDD
-
- collect() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an array that contains all of the elements in this RDD.
- collect() - Static method in class org.apache.spark.api.r.RRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.api.r.RRDD
-
- collect() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- collect() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- collect() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- collect() - Static method in class org.apache.spark.graphx.VertexRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- collect() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- collect() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- collect() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- collect() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- 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() - Static method in class org.apache.spark.rdd.UnionRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- collect() - Method in class org.apache.spark.sql.Dataset
-
Returns an array that contains all rows in this Dataset.
- collect(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- collect(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- collect(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- collect(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- collect(PartialFunction<A, B>, CanBuildFrom<Repr, B, That>) - Static method in class org.apache.spark.sql.types.StructType
-
- 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() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- collectAsync() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- collectAsync() - Static method in class org.apache.spark.api.java.JavaRDD
-
- 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.
- collectFirst(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- collectFirst(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- collectFirst(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- collectFirst(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- collectFirst(PartialFunction<A, B>) - Static method in class org.apache.spark.sql.types.StructType
-
- 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
-
- 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
-
- collectLeaves() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- collectLeaves() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- collectLeaves() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- collectLeaves() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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[]) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- collectPartitions(int[]) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- collectPartitions(int[]) - Static method in class org.apache.spark.api.java.JavaRDD
-
- 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.
- collectSubModels() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- collectSubModels() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- 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
-
- 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
-
- ColumnarMap(ColumnVector, ColumnVector, int, int) - Constructor for class org.apache.spark.sql.vectorized.ColumnarMap
-
- ColumnarRow - Class in org.apache.spark.sql.vectorized
-
- 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.
- combinations(int) - Static method in class org.apache.spark.sql.types.StructType
-
- 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(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- 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
-
- 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
-
- 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
-
- companion() - Static method in class org.apache.spark.sql.types.StructType
-
- 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(RDDInfo) - Method in class org.apache.spark.storage.RDDInfo
-
- compareTo(A) - Static method in class org.apache.spark.sql.types.Decimal
-
- compareTo(A) - Static 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
-
- compose(Function1<A, T1>) - Static method in class org.apache.spark.sql.types.StructType
-
- compressed() - Static method in class org.apache.spark.ml.linalg.DenseMatrix
-
- compressed() - Static method in class org.apache.spark.ml.linalg.DenseVector
-
- 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() - Static method in class org.apache.spark.ml.linalg.SparseMatrix
-
- compressed() - Static method in class org.apache.spark.ml.linalg.SparseVector
-
- compressed() - Method in interface org.apache.spark.ml.linalg.Vector
-
Returns a vector in either dense or sparse format, whichever uses less storage.
- compressed() - Static method in class org.apache.spark.mllib.linalg.DenseVector
-
- compressed() - Static method in class org.apache.spark.mllib.linalg.SparseVector
-
- compressed() - Method in interface org.apache.spark.mllib.linalg.Vector
-
Returns a vector in either dense or sparse format, whichever uses less storage.
- compressedColMajor() - Static method in class org.apache.spark.ml.linalg.DenseMatrix
-
- compressedColMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Returns a matrix in dense or sparse column major format, whichever uses less storage.
- compressedColMajor() - Static method in class org.apache.spark.ml.linalg.SparseMatrix
-
- 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() - Static method in class org.apache.spark.ml.linalg.DenseMatrix
-
- compressedRowMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Returns a matrix in dense or sparse row major format, whichever uses less storage.
- compressedRowMajor() - Static method in class org.apache.spark.ml.linalg.SparseMatrix
-
- 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) - Static method in class org.apache.spark.api.r.RRDD
-
- compute(Partition, TaskContext) - Method in class org.apache.spark.graphx.EdgeRDD
-
- compute(Partition, TaskContext) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- compute(Partition, TaskContext) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- 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) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- compute(Time) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Method that generates an RDD for the given Duration
- compute(Time) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- compute(Time) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- compute(Time) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- 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
-
- 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>) - 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>) - 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>) - 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
-
- 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.
- 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.
- 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.
- 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 class org.apache.spark.SparkEnv
-
- conf() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- conf() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- conf() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- conf() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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
-
- 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
-
- configTestLog4j(String) - Static method in class org.apache.spark.TestUtils
-
config a log4j properties used for testsuite
- 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
-
- constraints() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- constraints() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- constraints() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- constructIsNotNullConstraints(Set<Expression>, Seq<Attribute>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- constructIsNotNullConstraints(Set<Expression>, Seq<Attribute>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- constructIsNotNullConstraints(Set<Expression>, Seq<Attribute>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- 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.
- contains(A1) - Static method in class org.apache.spark.sql.types.StructType
-
- containsChild() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- containsChild() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- containsChild() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- containsChild() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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
-
- containsSlice(GenSeq<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- contentType() - Method in class org.apache.spark.ui.JettyUtils.ServletParams
-
- context() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- context() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- context() - Static method in class org.apache.spark.api.java.JavaRDD
-
- context() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
- context() - Static method in class org.apache.spark.api.r.RRDD
-
- context() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- context() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- context() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- context() - Static method in class org.apache.spark.graphx.VertexRDD
-
- context() - Method in class org.apache.spark.InterruptibleIterator
-
- context(SQLContext) - Static method in class org.apache.spark.ml.r.RWrappers
-
- 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() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- context() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- context() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- context() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- context() - Method in class org.apache.spark.rdd.RDD
-
- context() - Static method in class org.apache.spark.rdd.UnionRDD
-
- context() - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- context() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
- context() - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- context() - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- context() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- context() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- context() - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- 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
-
- ContinuousInputPartitionReader<T> - Interface in org.apache.spark.sql.sources.v2.reader.streaming
-
- ContinuousReader - Interface in org.apache.spark.sql.sources.v2.reader.streaming
-
- ContinuousReadSupport - Interface in org.apache.spark.sql.sources.v2
-
- 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.
- convertToNetty() - Method in class org.apache.spark.storage.EncryptedManagedBuffer
-
- 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) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- 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) - Static method in class org.apache.spark.ml.feature.DCT
-
- copy(ParamMap) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- 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) - Static method in class org.apache.spark.ml.feature.NGram
-
- copy(ParamMap) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- 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(Kryo, T) - Static method in class org.apache.spark.serializer.JavaIterableWrapperSerializer
-
- 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.
- copyToArray(Object, int) - Static method in class org.apache.spark.sql.types.StructType
-
- copyToArray(Object) - Static method in class org.apache.spark.sql.types.StructType
-
- copyToArray(Object, int, int) - Static method in class org.apache.spark.sql.types.StructType
-
- copyToBuffer(Buffer<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- 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
-
- 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
-
- corresponds(GenSeq<B>, Function2<A, B, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- 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() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- count() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- count() - Static method in class org.apache.spark.api.java.JavaRDD
-
- count() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return the number of elements in the RDD.
- count() - Static method in class org.apache.spark.api.r.RRDD
-
- count() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- 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() - Static method in class org.apache.spark.graphx.VertexRDD
-
- 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() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- count() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- count() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- count() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- count() - Method in class org.apache.spark.rdd.RDD
-
Return the number of elements in the RDD.
- count() - Static method in class org.apache.spark.rdd.UnionRDD
-
- 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(Function1<A, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- count() - Method in class org.apache.spark.status.RDDPartitionSeq
-
- count() - Method in class org.apache.spark.storage.ReadableChannelFileRegion
-
- count() - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- 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() - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- count() - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- count() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- count() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- count() - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- 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(Class<?>) - Method in class org.apache.spark.util.kvstore.InMemoryStore
-
- count(Class<?>, String, Object) - Method in class org.apache.spark.util.kvstore.InMemoryStore
-
- count(Class<?>) - Method in interface org.apache.spark.util.kvstore.KVStore
-
Returns the number of items of the given type currently in the store.
- count(Class<?>, String, Object) - Method in interface org.apache.spark.util.kvstore.KVStore
-
Returns the number of items of the given type which match the given indexed value.
- count(Class<?>) - Method in class org.apache.spark.util.kvstore.LevelDB
-
- count(Class<?>, String, Object) - Method in class org.apache.spark.util.kvstore.LevelDB
-
- 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) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countApprox(long) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countApprox(long) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.api.java.JavaRDD
-
- countApprox(long) - Static method in class org.apache.spark.api.java.JavaRDD
-
- 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) - Static method in class org.apache.spark.api.r.RRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countApprox(long, double) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countApprox(long, double) - Static method in class org.apache.spark.graphx.VertexRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- 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.
- countApprox(long, double) - Static method in class org.apache.spark.rdd.UnionRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.api.r.RRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countApprox$default$2() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countApprox$default$2() - Static method in class org.apache.spark.graphx.VertexRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.api.java.JavaRDD
-
- countApproxDistinct(double) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return approximate number of distinct elements in the RDD.
- countApproxDistinct(int, int) - Static method in class org.apache.spark.api.r.RRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.api.r.RRDD
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countApproxDistinct(double) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countApproxDistinct(double) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.graphx.VertexRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.graphx.VertexRDD
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- 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.
- countApproxDistinct(int, int) - Static method in class org.apache.spark.rdd.UnionRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.rdd.UnionRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.api.r.RRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.graphx.VertexRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.rdd.UnionRDD
-
- 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() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countAsync() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countAsync() - Static method in class org.apache.spark.api.java.JavaRDD
-
- 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() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countByValue() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countByValue() - Static method in class org.apache.spark.api.java.JavaRDD
-
- 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>) - Static method in class org.apache.spark.api.r.RRDD
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- 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(Ordering<T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- countByValue() - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- countByValue(int) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- 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() - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- countByValue(int) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- countByValue() - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- countByValue(int) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- countByValue() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- countByValue(int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- countByValue() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- countByValue(int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- countByValue() - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- countByValue(int) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- 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.
- countByValue$default$1() - Static method in class org.apache.spark.api.r.RRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countByValue$default$1() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countByValue$default$1() - Static method in class org.apache.spark.graphx.VertexRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.rdd.UnionRDD
-
- countByValueAndWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- countByValueAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- 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) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- countByValueAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- countByValueAndWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- countByValueAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- countByValueAndWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- countByValueAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- countByValueAndWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- countByValueAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- countByValueAndWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- countByValueAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- 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) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countByValueApprox(long) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countByValueApprox(long, double) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countByValueApprox(long) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countByValueApprox(long, double) - Static method in class org.apache.spark.api.java.JavaRDD
-
- countByValueApprox(long) - Static method in class org.apache.spark.api.java.JavaRDD
-
- 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>) - Static method in class org.apache.spark.api.r.RRDD
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countByValueApprox(long, double, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Approximate version of countByValue().
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.api.r.RRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.graphx.VertexRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.api.r.RRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.graphx.VertexRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.rdd.UnionRDD
-
- countByWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- 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) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- countByWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- countByWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- countByWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
<