public class ShuffledRDD<K,V,C> extends RDD<scala.Tuple2<K,C>>
Constructor and Description |
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ShuffledRDD(RDD<? extends scala.Product2<K,V>> prev,
Partitioner part) |
Modifier and Type | Method and Description |
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void |
clearDependencies()
Clears the dependencies of this RDD.
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scala.collection.Iterator<scala.Tuple2<K,C>> |
compute(Partition split,
TaskContext context)
:: DeveloperApi ::
Implemented by subclasses to compute a given partition.
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scala.collection.Seq<Dependency<?>> |
getDependencies()
Implemented by subclasses to return how this RDD depends on parent RDDs.
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Partition[] |
getPartitions()
Implemented by subclasses to return the set of partitions in this RDD.
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scala.Some<Partitioner> |
partitioner()
Optionally overridden by subclasses to specify how they are partitioned.
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Object |
prev() |
ShuffledRDD<K,V,C> |
setAggregator(Aggregator<K,V,C> aggregator)
Set aggregator for RDD's shuffle.
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ShuffledRDD<K,V,C> |
setKeyOrdering(scala.math.Ordering<K> keyOrdering)
Set key ordering for RDD's shuffle.
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ShuffledRDD<K,V,C> |
setMapSideCombine(boolean mapSideCombine)
Set mapSideCombine flag for RDD's shuffle.
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ShuffledRDD<K,V,C> |
setSerializer(Serializer serializer)
Set a serializer for this RDD's shuffle, or null to use the default (spark.serializer)
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aggregate, cache, cartesian, checkpoint, checkpointData, coalesce, collect, collect, collectPartitions, computeOrReadCheckpoint, conf, context, count, countApprox, countApproxDistinct, countApproxDistinct, countByValue, countByValueApprox, creationSite, dependencies, distinct, distinct, doCheckpoint, doubleRDDToDoubleRDDFunctions, elementClassTag, filter, filterWith, first, flatMap, flatMapWith, fold, foreach, foreachPartition, foreachWith, getCheckpointFile, getCreationSite, getNarrowAncestors, getStorageLevel, glom, groupBy, groupBy, groupBy, id, intersection, intersection, intersection, isCheckpointed, isEmpty, iterator, keyBy, map, mapPartitions, mapPartitionsWithContext, mapPartitionsWithIndex, mapPartitionsWithSplit, mapWith, markCheckpointed, max, min, name, numericRDDToDoubleRDDFunctions, partitions, persist, persist, pipe, pipe, pipe, preferredLocations, randomSplit, rddToAsyncRDDActions, rddToOrderedRDDFunctions, rddToPairRDDFunctions, rddToSequenceFileRDDFunctions, reduce, repartition, retag, retag, sample, saveAsObjectFile, saveAsTextFile, saveAsTextFile, setName, sortBy, sparkContext, subtract, subtract, subtract, take, takeOrdered, takeSample, toArray, toDebugString, toJavaRDD, toLocalIterator, top, toString, treeAggregate, treeReduce, union, unpersist, zip, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipWithIndex, zipWithUniqueId
initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning
public ShuffledRDD(RDD<? extends scala.Product2<K,V>> prev, Partitioner part)
public Object prev()
public ShuffledRDD<K,V,C> setSerializer(Serializer serializer)
public ShuffledRDD<K,V,C> setKeyOrdering(scala.math.Ordering<K> keyOrdering)
public ShuffledRDD<K,V,C> setAggregator(Aggregator<K,V,C> aggregator)
public ShuffledRDD<K,V,C> setMapSideCombine(boolean mapSideCombine)
public scala.collection.Seq<Dependency<?>> getDependencies()
RDD
public scala.Some<Partitioner> partitioner()
RDD
partitioner
in class RDD<scala.Tuple2<K,C>>
public Partition[] getPartitions()
RDD
public scala.collection.Iterator<scala.Tuple2<K,C>> compute(Partition split, TaskContext context)
RDD
public void clearDependencies()
RDD
UnionRDD
for an example.