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From "Aaron Davidson (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-1769) Executor loss can cause race condition in Pool
Date Sat, 10 May 2014 22:14:20 GMT
Aaron Davidson created SPARK-1769:
-------------------------------------

             Summary: Executor loss can cause race condition in Pool
                 Key: SPARK-1769
                 URL: https://issues.apache.org/jira/browse/SPARK-1769
             Project: Spark
          Issue Type: Bug
          Components: Spark Core
    Affects Versions: 1.0.0
            Reporter: Aaron Davidson


Loss of executors (in this case due to OOMs) exposes a race condition in Pool.scala, evident
from this stack trace:

{code}
14/05/08 22:41:48 ERROR OneForOneStrategy:
java.lang.NullPointerException
        at org.apache.spark.scheduler.Pool$$anonfun$executorLost$1.apply(Pool.scala:87)
        at org.apache.spark.scheduler.Pool$$anonfun$executorLost$1.apply(Pool.scala:87)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
        at org.apache.spark.scheduler.Pool.executorLost(Pool.scala:87)
        at org.apache.spark.scheduler.Pool$$anonfun$executorLost$1.apply(Pool.scala:87)
        at org.apache.spark.scheduler.Pool$$anonfun$executorLost$1.apply(Pool.scala:87)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
        at org.apache.spark.scheduler.Pool.executorLost(Pool.scala:87)
        at org.apache.spark.scheduler.TaskSchedulerImpl.removeExecutor(TaskSchedulerImpl.scala:412)
        at org.apache.spark.scheduler.TaskSchedulerImpl.executorLost(TaskSchedulerImpl.scala:385)
        at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverActor.removeExecutor(CoarseGrainedSchedulerBackend.scala:160)
        at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverActor$$anonfun$receive$1$$anonfun$applyOrElse$5.apply(CoarseGrainedSchedulerBackend.scala:123)
        at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverActor$$anonfun$receive$1$$anonfun$applyOrElse$5.apply(CoarseGrainedSchedulerBackend.scala:123)
        at scala.Option.foreach(Option.scala:236)
        at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverActor$$anonfun$receive$1.applyOrElse(CoarseGrainedSchedulerBackend.scala:123)
        at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
        at akka.actor.ActorCell.invoke(ActorCell.scala:456)
        at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
        at akka.dispatch.Mailbox.run(Mailbox.scala:219)
        at akka.dispatch.ForkJoinExecutorConfigurator$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)
{code}

Note that the line of code that throws this exception is here:
{code}
schedulableQueue.foreach(_.executorLost(executorId, host))
{code}

By the stack trace, it's not schedulableQueue that is null, but an element therein. As far
as I could tell, we never add a null element to this queue. Rather, I could see that there
removeSchedulable() and executorLost() were called at about the same time (via log messages),
and suspect that since this ArrayBuffer is in no way synchronized, that we iterate through
the list while it's in an incomplete state.



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