Github user guowei2 commented on a diff in the pull request:
https://github.com/apache/spark/pull/1291#discussion_r14498644
--- Diff:
streaming/src/main/scala/org/apache/spark/streaming/dstream/ShuffledDStream.scala
---
@@ -39,8 +39,10 @@ class ShuffledDStream[K: ClassTag, V: ClassTag, C:
ClassTag](
override def compute(validTime: Time): Option[RDD[(K,C)]] = {
parent.getOrCompute(validTime) match {
- case Some(rdd) => Some(rdd.combineByKey[C](
- createCombiner, mergeValue, mergeCombiner, partitioner,
mapSideCombine))
+ case Some(rdd) => {
+ Some(if (rdd.partitions.length==0)
rdd.combineByKey(createCombiner, mergeValue, mergeCombiner,0)
--- End diff --
1ãfor example:
u use NetworkInputDStream to receive data to generate BlockRDD. when it
receive no blocks in validtime, then partitions will be 0
NetworkInputDStream's code here
override def compute(validTime: Time): Option[RDD[T]] = {
// If this is called for any time before the start time of the context,
// then this returns an empty RDD. This may happen when recovering from
a
// master failure
if (validTime >= graph.startTime) {
val blockIds = ssc.scheduler.networkInputTracker.getBlockIds(id,
validTime)
Some(new BlockRDD[T](ssc.sc, blockIds))
} else {
Some(new BlockRDD[T](ssc.sc, Array[BlockId]()))
}
}
2. when parent RDD partition num is 0 ,but ShuffledDStream also change
into muti-partitions ,
then emtpy job will be running.
what i do is when this happen ShuffledDStream also out 0 partition
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