Are you using YARN client mode ? See https://spark.apache.org/docs/latest/running-on-yarn.html
In cluster mode, spark.yarn.am.memory is not effective. For Spark 2.0, akka is moved out of the picture. FYI On Sat, May 7, 2016 at 8:24 PM, Nirav Patel <npa...@xactlycorp.com> wrote: > I have 20 executors, 6 cores each. Total 5 stages. It fails on 5th one. > All of them have 6474 tasks. 5th task is a count operations and it also > performs aggregateByKey as a part of it lazy evaluation. > I am setting: > spark.driver.memory=10G, spark.yarn.am.memory=2G and > spark.driver.maxResultSize=9G > > > On a side note, could it be something to do with java serialization > library, ByteArrayOutputStream using byte array? Can it be replaced by > some better serializing library? > > https://bugs.openjdk.java.net/browse/JDK-8055949 > https://bugs.openjdk.java.net/browse/JDK-8136527 > > Thanks > > On Sat, May 7, 2016 at 4:51 PM, Ashish Dubey <ashish....@gmail.com> wrote: > >> Driver maintains the complete metadata of application ( scheduling of >> executor and maintaining the messaging to control the execution ) >> This code seems to be failing in that code path only. With that said >> there is Jvm overhead based on num of executors , stages and tasks in your >> app. Do you know your driver heap size and application structure ( num of >> stages and tasks ) >> >> Ashish >> >> On Saturday, May 7, 2016, Nirav Patel <npa...@xactlycorp.com> wrote: >> >>> Right but this logs from spark driver and spark driver seems to use Akka. >>> >>> ERROR [sparkDriver-akka.actor.default-dispatcher-17] >>> akka.actor.ActorSystemImpl: Uncaught fatal error from thread >>> [sparkDriver-akka.remote.default-remote-dispatcher-5] shutting down >>> ActorSystem [sparkDriver] >>> >>> I saw following logs before above happened. >>> >>> 2016-05-06 09:49:17,813 INFO >>> [sparkDriver-akka.actor.default-dispatcher-17] >>> org.apache.spark.MapOutputTrackerMasterEndpoint: Asked to send map output >>> locations for shuffle 1 to hdn6.xactlycorporation.local:44503 >>> >>> >>> As far as I know driver is just driving shuffle operation but not >>> actually doing anything within its own system that will cause memory issue. >>> Can you explain in what circumstances I could see this error in driver >>> logs? I don't do any collect or any other driver operation that would cause >>> this. It fails when doing aggregateByKey operation but that should happen >>> in executor JVM NOT in driver JVM. >>> >>> >>> Thanks >>> >>> On Sat, May 7, 2016 at 11:58 AM, Ted Yu <yuzhih...@gmail.com> wrote: >>> >>>> bq. at akka.serialization.JavaSerializer.toBinary( >>>> Serializer.scala:129) >>>> >>>> It was Akka which uses JavaSerializer >>>> >>>> Cheers >>>> >>>> On Sat, May 7, 2016 at 11:13 AM, Nirav Patel <npa...@xactlycorp.com> >>>> wrote: >>>> >>>>> Hi, >>>>> >>>>> I thought I was using kryo serializer for shuffle. I could verify it >>>>> from spark UI - Environment tab that >>>>> spark.serializer org.apache.spark.serializer.KryoSerializer >>>>> spark.kryo.registrator >>>>> com.myapp.spark.jobs.conf.SparkSerializerRegistrator >>>>> >>>>> >>>>> But when I see following error in Driver logs it looks like spark is >>>>> using JavaSerializer >>>>> >>>>> 2016-05-06 09:49:26,490 ERROR >>>>> [sparkDriver-akka.actor.default-dispatcher-17] akka.actor.ActorSystemImpl: >>>>> Uncaught fatal error from thread >>>>> [sparkDriver-akka.remote.default-remote-dispatcher-6] shutting down >>>>> ActorSystem [sparkDriver] >>>>> >>>>> java.lang.OutOfMemoryError: Java heap space >>>>> >>>>> at java.util.Arrays.copyOf(Arrays.java:2271) >>>>> >>>>> at >>>>> java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:113) >>>>> >>>>> at >>>>> java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93) >>>>> >>>>> at >>>>> java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:140) >>>>> >>>>> at >>>>> java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1876) >>>>> >>>>> at >>>>> java.io.ObjectOutputStream$BlockDataOutputStream.setBlockDataMode(ObjectOutputStream.java:1785) >>>>> >>>>> at >>>>> java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1188) >>>>> >>>>> at >>>>> java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:347) >>>>> >>>>> at >>>>> akka.serialization.JavaSerializer$$anonfun$toBinary$1.apply$mcV$sp(Serializer.scala:129) >>>>> >>>>> at >>>>> akka.serialization.JavaSerializer$$anonfun$toBinary$1.apply(Serializer.scala:129) >>>>> >>>>> at >>>>> akka.serialization.JavaSerializer$$anonfun$toBinary$1.apply(Serializer.scala:129) >>>>> >>>>> at >>>>> scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) >>>>> >>>>> at >>>>> akka.serialization.JavaSerializer.toBinary(Serializer.scala:129) >>>>> >>>>> at >>>>> akka.remote.MessageSerializer$.serialize(MessageSerializer.scala:36) >>>>> >>>>> at >>>>> akka.remote.EndpointWriter$$anonfun$serializeMessage$1.apply(Endpoint.scala:843) >>>>> >>>>> at >>>>> akka.remote.EndpointWriter$$anonfun$serializeMessage$1.apply(Endpoint.scala:843) >>>>> >>>>> at >>>>> scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) >>>>> >>>>> at >>>>> akka.remote.EndpointWriter.serializeMessage(Endpoint.scala:842) >>>>> >>>>> at akka.remote.EndpointWriter.writeSend(Endpoint.scala:743) >>>>> >>>>> at >>>>> akka.remote.EndpointWriter$$anonfun$2.applyOrElse(Endpoint.scala:718) >>>>> >>>>> at akka.actor.Actor$class.aroundReceive(Actor.scala:467) >>>>> >>>>> at akka.remote.EndpointActor.aroundReceive(Endpoint.scala:411) >>>>> >>>>> 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$AkkaForkJoinTask.exec(AbstractDispatcher.scala:397) >>>>> >>>>> at >>>>> scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260) >>>>> >>>>> at >>>>> scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339) >>>>> >>>>> at >>>>> scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979) >>>>> >>>>> at >>>>> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) >>>>> >>>>> >>>>> >>>>> What I am missing here? >>>>> >>>>> Thanks >>>>> >>>>> >>>>> >>>>> [image: What's New with Xactly] >>>>> <http://www.xactlycorp.com/email-click/> >>>>> >>>>> <https://www.nyse.com/quote/XNYS:XTLY> [image: LinkedIn] >>>>> <https://www.linkedin.com/company/xactly-corporation> [image: >>>>> Twitter] <https://twitter.com/Xactly> [image: Facebook] >>>>> <https://www.facebook.com/XactlyCorp> [image: YouTube] >>>>> <http://www.youtube.com/xactlycorporation> >>>> >>>> >>>> >>> >>> >>> >>> [image: What's New with Xactly] <http://www.xactlycorp.com/email-click/> >>> >>> <https://www.nyse.com/quote/XNYS:XTLY> [image: LinkedIn] >>> <https://www.linkedin.com/company/xactly-corporation> [image: Twitter] >>> <https://twitter.com/Xactly> [image: Facebook] >>> <https://www.facebook.com/XactlyCorp> [image: YouTube] >>> <http://www.youtube.com/xactlycorporation> >> >> > > > > [image: What's New with Xactly] <http://www.xactlycorp.com/email-click/> > > <https://www.nyse.com/quote/XNYS:XTLY> [image: LinkedIn] > <https://www.linkedin.com/company/xactly-corporation> [image: Twitter] > <https://twitter.com/Xactly> [image: Facebook] > <https://www.facebook.com/XactlyCorp> [image: YouTube] > <http://www.youtube.com/xactlycorporation> >
