Github user vchekan commented on the pull request:
https://github.com/apache/spark/pull/961#issuecomment-45125185
Perhaps my initial interpretation of what lead to this exception was wrong.
When JobGenerator generates a job, it calls DStreamGraph, which calls
output streams, which calls DStream.getOrCompute.
https://github.com/apache/spark/blob/master/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala#L290
As you can see, "compute" wont be called if time is not right. For windowed
DStream for example, only those matching window sliding period will be valid
times and those not matching will be ignored.
But ReceiverInputDStream.receivedBlockInfo is updated only when "compute"
is called.
https://github.com/apache/spark/blob/master/streaming/src/main/scala/org/apache/spark/streaming/dstream/ReceiverInputDStream.scala#L67
Thus, receivedBlockInfo may have missing times when window DStream is used.
Next, after graph.generateJobs, JobGenerator calls every
getReceiverInputStreams getReceivedBlockInfo(). It does not check, is the time
valid or not. And
@pwendell could you please advise, if the way I've fixed the bug is the
right one, or it is better to check DStream.isTimeValid before calling receiver
input stream's getReceivedBlockInfo?
And btw, here is full stacktrace of the exception:
java.util.NoSuchElementException: key not found: 1401754908000 ms
at scala.collection.MapLike$class.default(MapLike.scala:228)
at scala.collection.AbstractMap.default(Map.scala:58)
at scala.collection.mutable.HashMap.apply(HashMap.scala:64)
at
org.apache.spark.streaming.dstream.ReceiverInputDStream.getReceivedBlockInfo(ReceiverInputDStream.scala:77)
at
org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$3.apply(JobGenerator.scala:225)
at
org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$3.apply(JobGenerator.scala:223)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at
scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
at
org.apache.spark.streaming.scheduler.JobGenerator.generateJobs(JobGenerator.scala:223)
at
org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:165)
at
org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$start$1$$anon$1$$anonfun$receive$1.applyOrElse(JobGenerator.scala:76)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at
akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at
scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at
scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at
scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
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