Github user ankurdave commented on a diff in the pull request:
https://github.com/apache/spark/pull/497#discussion_r12453694
--- Diff: graphx/src/main/scala/org/apache/spark/graphx/VertexRDD.scala ---
@@ -276,14 +286,31 @@ class VertexRDD[@specialized VD: ClassTag](
*/
def aggregateUsingIndex[VD2: ClassTag](
messages: RDD[(VertexId, VD2)], reduceFunc: (VD2, VD2) => VD2):
VertexRDD[VD2] = {
- val shuffled = MsgRDDFunctions.partitionForAggregation(messages,
this.partitioner.get)
+ val shuffled = messages.copartitionWithVertices(this.partitioner.get)
val parts = partitionsRDD.zipPartitions(shuffled, true) { (thisIter,
msgIter) =>
- val vertexPartition: VertexPartition[VD] = thisIter.next()
- Iterator(vertexPartition.aggregateUsingIndex(msgIter, reduceFunc))
+ thisIter.map(_.aggregateUsingIndex(msgIter, reduceFunc))
}
new VertexRDD[VD2](parts)
}
+ /**
+ * Returns a new `VertexRDD` reflecting a reversal of all edge
directions in the corresponding
+ * [[EdgeRDD]].
+ */
+ def reverseRoutingTables(): VertexRDD[VD] =
+ this.mapVertexPartitions(vPart =>
vPart.withRoutingTable(vPart.routingTable.reverse))
+
+ /** Generates an RDD of vertex attributes suitable for shipping to the
edge partitions. */
+ private[graphx] def shipVertexAttributes(
--- End diff --
Should partitionBy before returning
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