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>

All Implemented Interfaces:

java.io.Serializable, 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).

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
ShuffledRDD(RDD<? extends scala.Product2<K,V>> prev, Partitioner part)

Method Summary

Methods

Modifier and Type	Method and Description
void	clearDependencies() Clears the dependencies of this RDD.
scala.collection.Iterator<scala.Tuple2<K,C>>	compute(Partition split, TaskContext context) :: DeveloperApi :: Implemented by subclasses to compute a given partition.
scala.collection.Seq<Dependency<?>>	getDependencies() Implemented by subclasses to return how this RDD depends on parent RDDs.
Partition[]	getPartitions() Implemented by subclasses to return the set of partitions in this RDD.
scala.Some<Partitioner>	partitioner() Optionally overridden by subclasses to specify how they are partitioned.
Object	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, cache, cartesian, checkpoint, checkpointData, coalesce, collect, collect, collectPartitions, computeOrReadCheckpoint, conf, context, count, countApprox, countApproxDistinct, countApproxDistinct, countByValue, countByValueApprox, creationSite, dependencies, distinct, distinct, doCheckpoint, elementClassTag, filter, filterWith, first, flatMap, flatMapWith, fold, foreach, foreachPartition, foreachWith, getCheckpointFile, getCreationSite, getNarrowAncestors, getStorageLevel, glom, groupBy, groupBy, groupBy, id, intersection, intersection, intersection, isCheckpointed, iterator, keyBy, map, mapPartitions, mapPartitionsWithContext, mapPartitionsWithIndex, mapPartitionsWithSplit, mapWith, markCheckpointed, max, min, name, partitions, persist, persist, pipe, pipe, pipe, preferredLocations, randomSplit, reduce, repartition, retag, retag, sample, saveAsObjectFile, saveAsTextFile, saveAsTextFile, setName, sortBy, sparkContext, subtract, subtract, subtract, take, takeOrdered, takeSample, toArray, toDebugString, toJavaRDD, toLocalIterator, top, toString, union, unpersist, zip, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipWithIndex, zipWithUniqueId

Methods inherited from class Object

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

Methods inherited from interface org.apache.spark.Logging

initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Constructor Detail

ShuffledRDD

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

Method Detail

prev

public Object prev()

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)

setKeyOrdering

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

Set key ordering for RDD's shuffle.

setAggregator

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

Set aggregator for RDD's shuffle.

setMapSideCombine

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

Set mapSideCombine flag for RDD's shuffle.

getDependencies

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

Description copied from class: RDD

Implemented by subclasses to return how this RDD depends on parent RDDs. This method will only be called once, so it is safe to implement a time-consuming computation in it.

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>>

getPartitions

public Partition[] getPartitions()

Description copied from class: RDD

Implemented by subclasses to return the set of partitions in this RDD. This method will only be called once, so it is safe to implement a time-consuming computation in it.

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>>

clearDependencies

public void clearDependencies()

Description copied from class: RDD

Clears the dependencies of this RDD. This method must ensure that all references to the original parent RDDs is removed to enable the parent RDDs to be garbage collected. Subclasses of RDD may override this method for implementing their own cleaning logic. See UnionRDD for an example.