public class CoGroupedRDD<K> extends RDD<scala.Tuple2<K,scala.collection.Iterable<?>[]>>
param: rdds parent RDDs. param: part partitioner used to partition the shuffle output
| Constructor and Description |
|---|
CoGroupedRDD(scala.collection.Seq<RDD<? extends scala.Product2<K,?>>> rdds,
Partitioner part,
scala.reflect.ClassTag<K> evidence$1) |
| Modifier and Type | Method and Description |
|---|---|
void |
clearDependencies()
Clears the dependencies of this RDD.
|
scala.collection.Iterator<scala.Tuple2<K,scala.collection.Iterable<?>[]>> |
compute(Partition s,
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.
|
scala.collection.Seq<RDD<? extends scala.Product2<K,?>>> |
rdds() |
CoGroupedRDD<K> |
setSerializer(Serializer serializer)
Set a serializer for this RDD's shuffle, or null to use the default (spark.serializer)
|
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, 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, zipWithIndex, zipWithUniqueId$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitializepublic CoGroupedRDD(scala.collection.Seq<RDD<? extends scala.Product2<K,?>>> rdds, Partitioner part, scala.reflect.ClassTag<K> evidence$1)
public void clearDependencies()
RDDUnionRDD for an example.public scala.collection.Iterator<scala.Tuple2<K,scala.collection.Iterable<?>[]>> compute(Partition s, TaskContext context)
RDDpublic scala.collection.Seq<Dependency<?>> getDependencies()
RDDpublic Partition[] getPartitions()
RDD
The partitions in this array must satisfy the following property:
rdd.partitions.zipWithIndex.forall { case (partition, index) => partition.index == index }
public scala.Some<Partitioner> partitioner()
RDDpartitioner in class RDD<scala.Tuple2<K,scala.collection.Iterable<?>[]>>public CoGroupedRDD<K> setSerializer(Serializer serializer)