Details
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Bug
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Status: Resolved
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Critical
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Resolution: Fixed
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1.3.1
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None
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Red Hat Enterprise Linux Server release 7.0 (Maipo)
Spark 1.3.1 Release
Description
I am from IBM Platform Symphony team and we are integrating Spark 1.3.1 with EGO (a resource management product).
In EGO we uses fine-grained dynamic allocation policy, and each Executor will exit after its tasks are all done. When testing spark-shell, we find that when executor of first job exit, it will stop OutputCommitCoordinator, which result in all future jobs failing. Details are as follows:
We got the following error in executor when submitting job in spark-shell the second time (the first job submission is successful):
15/05/11 04:02:31 INFO spark.util.AkkaUtils: Connecting to OutputCommitCoordinator: akka.tcp://sparkDriver@whlspark01:50452/user/OutputCommitCoordinator
Exception in thread "main" akka.actor.ActorNotFound: Actor not found for: ActorSelection[Anchor(akka.tcp://sparkDriver@whlspark01:50452/), Path(/user/OutputCommitCoordinator)]
at akka.actor.ActorSelection$$anonfun$resolveOne$1.apply(ActorSelection.scala:65)
at akka.actor.ActorSelection$$anonfun$resolveOne$1.apply(ActorSelection.scala:63)
at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32)
at akka.dispatch.BatchingExecutor$Batch$$anonfun$run$1.processBatch$1(BatchingExecutor.scala:67)
at akka.dispatch.BatchingExecutor$Batch$$anonfun$run$1.apply$mcV$sp(BatchingExecutor.scala:82)
at akka.dispatch.BatchingExecutor$Batch$$anonfun$run$1.apply(BatchingExecutor.scala:59)
at akka.dispatch.BatchingExecutor$Batch$$anonfun$run$1.apply(BatchingExecutor.scala:59)
at scala.concurrent.BlockContext$.withBlockContext(BlockContext.scala:72)
at akka.dispatch.BatchingExecutor$Batch.run(BatchingExecutor.scala:58)
at akka.dispatch.ExecutionContexts$sameThreadExecutionContext$.unbatchedExecute(Future.scala:74)
at akka.dispatch.BatchingExecutor$class.execute(BatchingExecutor.scala:110)
at akka.dispatch.ExecutionContexts$sameThreadExecutionContext$.execute(Future.scala:73)
at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:40)
at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:248)
at akka.pattern.PromiseActorRef.$bang(AskSupport.scala:267)
at akka.remote.DefaultMessageDispatcher.dispatch(Endpoint.scala:89)
at akka.remote.EndpointReader$$anonfun$receive$2.applyOrElse(Endpoint.scala:937)
at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
at akka.remote.EndpointActor.aroundReceive(Endpoint.scala:415)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
at akka.actor.ActorCell.invoke(ActorCell.scala:487)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
at akka.dispatch.Mailbox.run(Mailbox.scala:220)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
And in driver side, we see a log message telling that the OutputCommitCoordinator is stopped after the first submission:
15/05/11 04:01:23 INFO spark.scheduler.OutputCommitCoordinator$OutputCommitCoordinatorActor: OutputCommitCoordinator stopped!
We examine the code of OutputCommitCoordinator, and find that executor will reuse the ref of driver's OutputCommitCoordinatorActor. So when an executor exits, it will eventually call SparkEnv.stop():
private[spark] def stop() {
isStopped = true
pythonWorkers.foreach { case(key, worker) => worker.stop() }
Option(httpFileServer).foreach(_.stop())
mapOutputTracker.stop()
shuffleManager.stop()
broadcastManager.stop()
blockManager.stop()
blockManager.master.stop()
metricsSystem.stop()
outputCommitCoordinator.stop() <---------------
actorSystem.shutdown()
......
and in OutputCommitCoordinator.stop():
def stop(): Unit = synchronized {
coordinatorActor.foreach(_ ! StopCoordinator)
coordinatorActor = None
authorizedCommittersByStage.clear()
}
We now work this problem around by adding an attribute "isDriver" in OutputCommitCoordinator and judge whether the "stop" command comes from driver or executor:
diff SparkEnv.scala
360c360
< new OutputCommitCoordinator(conf, isDriver)
---
> new OutputCommitCoordinator(conf)
diff OutputCommitCoordinator.scala
43c43
< private[spark] class OutputCommitCoordinator(conf: SparkConf, isDriver: Boolean = false) extends Logging {
---
> private[spark] class OutputCommitCoordinator(conf: SparkConf) extends Logging {
137,141c137,139
< if (isDriver) {
< coordinatorActor.foreach(_ ! StopCoordinator)
< coordinatorActor = None
< authorizedCommittersByStage.clear()
< }
---
> coordinatorActor.foreach(_ ! StopCoordinator)
> coordinatorActor = None
> authorizedCommittersByStage.clear()
We propose to apply this fix in future release since it may affects all spark-shell function of dynamic allocation model.
