public class EdgeRDDImpl<ED,VD> extends EdgeRDD<ED>
Modifier and Type | Method and Description |
---|---|
EdgeRDDImpl<ED,VD> |
cache()
Persists the edge partitions using `targetStorageLevel`, which defaults to MEMORY_ONLY.
|
void |
checkpoint()
Mark this RDD for checkpointing.
|
Edge<ED>[] |
collect()
Return an array that contains all of the elements in this RDD.
|
long |
count()
The number of edges in the RDD.
|
EdgeRDDImpl<ED,VD> |
filter(scala.Function1<EdgeTriplet<VD,ED>,Object> epred,
scala.Function2<Object,VD,Object> vpred) |
scala.Option<String> |
getCheckpointFile()
Gets the name of the file to which this RDD was checkpointed
|
StorageLevel |
getStorageLevel()
Get the RDD's current storage level, or StorageLevel.NONE if none is set.
|
<ED2,ED3> EdgeRDDImpl<ED3,VD> |
innerJoin(EdgeRDD<ED2> other,
scala.Function4<Object,Object,ED,ED2,ED3> f,
scala.reflect.ClassTag<ED2> evidence$4,
scala.reflect.ClassTag<ED3> evidence$5)
Inner joins this EdgeRDD with another EdgeRDD, assuming both are partitioned using the same
PartitionStrategy . |
boolean |
isCheckpointed()
Return whether this RDD has been checkpointed or not
|
<ED2,VD2> EdgeRDDImpl<ED2,VD2> |
mapEdgePartitions(scala.Function2<Object,org.apache.spark.graphx.impl.EdgePartition<ED,VD>,org.apache.spark.graphx.impl.EdgePartition<ED2,VD2>> f,
scala.reflect.ClassTag<ED2> evidence$6,
scala.reflect.ClassTag<VD2> evidence$7) |
<ED2> EdgeRDDImpl<ED2,VD> |
mapValues(scala.Function1<Edge<ED>,ED2> f,
scala.reflect.ClassTag<ED2> evidence$3)
Map the values in an edge partitioning preserving the structure but changing the values.
|
scala.Option<Partitioner> |
partitioner()
If
partitionsRDD already has a partitioner, use it. |
RDD<scala.Tuple2<Object,org.apache.spark.graphx.impl.EdgePartition<ED,VD>>> |
partitionsRDD() |
EdgeRDDImpl<ED,VD> |
persist(StorageLevel newLevel)
Persists the edge partitions at the specified storage level, ignoring any existing target
storage level.
|
EdgeRDDImpl<ED,VD> |
reverse()
Reverse all the edges in this RDD.
|
EdgeRDDImpl<ED,VD> |
setName(String _name)
Assign a name to this RDD
|
StorageLevel |
targetStorageLevel() |
EdgeRDDImpl<ED,VD> |
unpersist(boolean blocking)
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
|
aggregate, cartesian, checkpointData, coalesce, collect, context, countApprox, countApproxDistinct, countApproxDistinct, countByValue, countByValueApprox, creationSite, dependencies, distinct, distinct, doubleRDDToDoubleRDDFunctions, filter, filterWith, first, flatMap, flatMapWith, fold, foreach, foreachPartition, foreachWith, glom, groupBy, groupBy, groupBy, id, intersection, intersection, intersection, isEmpty, iterator, keyBy, map, mapPartitions, mapPartitionsWithContext, mapPartitionsWithIndex, mapPartitionsWithSplit, mapWith, max, min, name, numericRDDToDoubleRDDFunctions, partitions, persist, pipe, pipe, pipe, preferredLocations, randomSplit, rddToAsyncRDDActions, rddToOrderedRDDFunctions, rddToPairRDDFunctions, rddToSequenceFileRDDFunctions, reduce, repartition, sample, saveAsObjectFile, saveAsTextFile, saveAsTextFile, scope, sortBy, sparkContext, subtract, subtract, subtract, take, takeOrdered, takeSample, toArray, toDebugString, toJavaRDD, toLocalIterator, top, toString, treeAggregate, treeReduce, union, 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 RDD<scala.Tuple2<Object,org.apache.spark.graphx.impl.EdgePartition<ED,VD>>> partitionsRDD()
public StorageLevel targetStorageLevel()
public EdgeRDDImpl<ED,VD> setName(String _name)
RDD
public scala.Option<Partitioner> partitioner()
partitionsRDD
already has a partitioner, use it. Otherwise assume that the
PartitionID
s in partitionsRDD
correspond to the actual partitions and create a new
partitioner that allows co-partitioning with partitionsRDD
.partitioner
in class RDD<Edge<ED>>
public Edge<ED>[] collect()
RDD
public EdgeRDDImpl<ED,VD> persist(StorageLevel newLevel)
public EdgeRDDImpl<ED,VD> unpersist(boolean blocking)
RDD
public EdgeRDDImpl<ED,VD> cache()
public StorageLevel getStorageLevel()
RDD
getStorageLevel
in class RDD<Edge<ED>>
public void checkpoint()
RDD
checkpoint
in class RDD<Edge<ED>>
public boolean isCheckpointed()
RDD
isCheckpointed
in class RDD<Edge<ED>>
public scala.Option<String> getCheckpointFile()
RDD
getCheckpointFile
in class RDD<Edge<ED>>
public long count()
public <ED2> EdgeRDDImpl<ED2,VD> mapValues(scala.Function1<Edge<ED>,ED2> f, scala.reflect.ClassTag<ED2> evidence$3)
EdgeRDD
public EdgeRDDImpl<ED,VD> reverse()
EdgeRDD
public EdgeRDDImpl<ED,VD> filter(scala.Function1<EdgeTriplet<VD,ED>,Object> epred, scala.Function2<Object,VD,Object> vpred)
public <ED2,ED3> EdgeRDDImpl<ED3,VD> innerJoin(EdgeRDD<ED2> other, scala.Function4<Object,Object,ED,ED2,ED3> f, scala.reflect.ClassTag<ED2> evidence$4, scala.reflect.ClassTag<ED3> evidence$5)
EdgeRDD
PartitionStrategy
.
innerJoin
in class EdgeRDD<ED>
other
- the EdgeRDD to join withf
- the join function applied to corresponding values of this
and other
evidence$4
- (undocumented)evidence$5
- (undocumented)this
and other
,
with values supplied by f
public <ED2,VD2> EdgeRDDImpl<ED2,VD2> mapEdgePartitions(scala.Function2<Object,org.apache.spark.graphx.impl.EdgePartition<ED,VD>,org.apache.spark.graphx.impl.EdgePartition<ED2,VD2>> f, scala.reflect.ClassTag<ED2> evidence$6, scala.reflect.ClassTag<VD2> evidence$7)