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, scala.Serializable

public class PartitionPruningRDD<T>
extends RDD<T>

:: 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:

• Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

org.apache.spark.internal.Logging.SparkShellLoggingFilter

Constructor Summary

Constructors

Constructor	Description
PartitionPruningRDD(RDD<T> prev, scala.Function1<Object,Object> partitionFilterFunc, scala.reflect.ClassTag<T> evidence$1)

Method Summary

Modifier and Type	Method	Description
scala.collection.Iterator<T>	compute(Partition split, TaskContext context)	:: DeveloperApi :: Implemented by subclasses to compute a given partition.
static <T> PartitionPruningRDD<T>	create(RDD<T> rdd, scala.Function1<Object,Object> partitionFilterFunc)	Create a PartitionPruningRDD.

Methods inherited from class org.apache.spark.rdd.RDD

aggregate, 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, zipWithUniqueId

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.apache.spark.internal.Logging

initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq

Constructor Details

PartitionPruningRDD

public PartitionPruningRDD(RDD<T> prev,
 scala.Function1<Object,Object> partitionFilterFunc,
 scala.reflect.ClassTag<T> evidence$1)

Method Details

create

public 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)

compute

public scala.collection.Iterator<T> compute(Partition split,
 TaskContext context)

Description copied from class: RDD

:: DeveloperApi :: Implemented by subclasses to compute a given partition.

Specified by:

compute in class RDD<T>

Parameters:

split - (undocumented)

context - (undocumented)

Returns:

(undocumented)