Package org.apache.spark.rdd
Class PartitionPruningRDD<T>
Object
org.apache.spark.rdd.RDD<T>
org.apache.spark.rdd.PartitionPruningRDD<T>
- All Implemented Interfaces:
- Serializable,- org.apache.spark.internal.Logging
:: DeveloperApi ::
 An RDD used to prune RDD partitions/partitions so we can avoid launching tasks on
 all partitions. An example use case: If we know the RDD is partitioned by range,
 and the execution DAG has a filter on the key, we can avoid launching tasks
 on partitions that don't have the range covering the key.
- See Also:
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Nested Class SummaryNested classes/interfaces inherited from interface org.apache.spark.internal.Loggingorg.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter
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Constructor SummaryConstructors
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Method SummaryModifier and TypeMethodDescriptionscala.collection.Iterator<T>compute(Partition split, TaskContext context) :: DeveloperApi :: Implemented by subclasses to compute a given partition.static <T> PartitionPruningRDD<T>Create a PartitionPruningRDD.Methods inherited from class org.apache.spark.rdd.RDDaggregate, barrier, cache, cartesian, checkpoint, cleanShuffleDependencies, coalesce, collect, collect, context, count, countApprox, countApproxDistinct, countApproxDistinct, countByValue, countByValueApprox, dependencies, distinct, distinct, doubleRDDToDoubleRDDFunctions, filter, first, flatMap, fold, foreach, foreachPartition, getCheckpointFile, getNumPartitions, getResourceProfile, getStorageLevel, glom, groupBy, groupBy, groupBy, id, intersection, intersection, intersection, isCheckpointed, isEmpty, iterator, keyBy, localCheckpoint, map, mapPartitions, mapPartitionsWithEvaluator, mapPartitionsWithIndex, max, min, name, numericRDDToDoubleRDDFunctions, partitioner, partitions, persist, persist, pipe, pipe, pipe, preferredLocations, randomSplit, rddToAsyncRDDActions, rddToOrderedRDDFunctions, rddToPairRDDFunctions, rddToSequenceFileRDDFunctions, reduce, repartition, sample, saveAsObjectFile, saveAsTextFile, saveAsTextFile, setName, sortBy, sparkContext, subtract, subtract, subtract, take, takeOrdered, takeSample, toDebugString, toJavaRDD, toLocalIterator, top, toString, treeAggregate, treeAggregate, treeReduce, union, unpersist, withResources, zip, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitionsWithEvaluator, zipWithIndex, zipWithUniqueIdMethods inherited from class java.lang.Objectequals, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface org.apache.spark.internal.LogginginitializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logBasedOnLevel, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, MDC, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext
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Constructor Details- 
PartitionPruningRDD
 
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Method Details- 
createpublic static <T> PartitionPruningRDD<T> create(RDD<T> rdd, scala.Function1<Object, Object> partitionFilterFunc) Create a PartitionPruningRDD. This function can be used to create the PartitionPruningRDD when its type T is not known at compile time.- Parameters:
- rdd- (undocumented)
- partitionFilterFunc- (undocumented)
- Returns:
- (undocumented)
 
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computeDescription copied from class:RDD:: DeveloperApi :: Implemented by subclasses to compute a given partition.
 
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