Package org.apache.spark.rdd

Class ShuffledRDD<K,V,C>

Object

org.apache.spark.rdd.RDD<scala.Tuple2<K,C>>

org.apache.spark.rdd.ShuffledRDD<K,V,C>

Type Parameters:

K - the key class.

V - the value class.

C - the combiner class.

All Implemented Interfaces:

Serializable, org.apache.spark.internal.Logging

public class ShuffledRDD<K,V,C>
extends RDD<scala.Tuple2<K,C>>

:: DeveloperApi :: The resulting RDD from a shuffle (e.g. repartitioning of data). param: prev the parent RDD. param: part the partitioner used to partition the RDD

See Also:

• Serialized Form

Nested Class Summary

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

org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter

Constructor Summary

Constructors

Constructor	Description
ShuffledRDD(RDD<? extends scala.Product2<K,V>> prev, Partitioner part, scala.reflect.ClassTag<K> evidence$1, scala.reflect.ClassTag<V> evidence$2, scala.reflect.ClassTag<C> evidence$3)

Method Summary

Modifier and Type	Method	Description
void	clearDependencies()
scala.collection.Iterator<scala.Tuple2<K,C>>	compute(Partition split, TaskContext context)	:: DeveloperApi :: Implemented by subclasses to compute a given partition.
scala.collection.immutable.Seq<Dependency<?>>	getDependencies()
Partition[]	getPartitions()
scala.Some<Partitioner>	partitioner()	Optionally overridden by subclasses to specify how they are partitioned.
RDD<? extends scala.Product2<K,V>>	prev()
ShuffledRDD<K,V,C>	setAggregator(Aggregator<K,V,C> aggregator)	Set aggregator for RDD's shuffle.
ShuffledRDD<K,V,C>	setKeyOrdering(scala.math.Ordering<K> keyOrdering)	Set key ordering for RDD's shuffle.
ShuffledRDD<K,V,C>	setMapSideCombine(boolean mapSideCombine)	Set mapSideCombine flag for RDD's shuffle.
ShuffledRDD<K,V,C>	setSerializer(Serializer serializer)	Set a serializer for this RDD's shuffle, or null to use the default (spark.serializer)

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, 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$2, isTraceEnabled, log, logBasedOnLevel, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, MDC, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext

Constructor Details

ShuffledRDD

public ShuffledRDD(RDD<? extends scala.Product2<K,V>> prev,
 Partitioner part,
 scala.reflect.ClassTag<K> evidence$1,
 scala.reflect.ClassTag<V> evidence$2,
 scala.reflect.ClassTag<C> evidence$3)

Method Details

clearDependencies

public void clearDependencies()

compute

public scala.collection.Iterator<scala.Tuple2<K,C>> 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<scala.Tuple2<K,C>>

Parameters:

split - (undocumented)

context - (undocumented)

Returns:

(undocumented)

getDependencies

public scala.collection.immutable.Seq<Dependency<?>> getDependencies()

getPartitions

public Partition[] getPartitions()

partitioner

public scala.Some<Partitioner> partitioner()

Description copied from class: RDD

Optionally overridden by subclasses to specify how they are partitioned.

Overrides:

partitioner in class RDD<scala.Tuple2<K,C>>

prev

public RDD<? extends scala.Product2<K,V>> prev()

setAggregator

public ShuffledRDD<K,V,C> setAggregator(Aggregator<K,V,C> aggregator)

Set aggregator for RDD's shuffle.

setKeyOrdering

public ShuffledRDD<K,V,C> setKeyOrdering(scala.math.Ordering<K> keyOrdering)

Set key ordering for RDD's shuffle.

setMapSideCombine

public ShuffledRDD<K,V,C> setMapSideCombine(boolean mapSideCombine)

Set mapSideCombine flag for RDD's shuffle.

setSerializer

public ShuffledRDD<K,V,C> setSerializer(Serializer serializer)

Set a serializer for this RDD's shuffle, or null to use the default (spark.serializer)