Is that all you have in the executor logs? I suspect some of those jobs are having a hard time managing the memory.
Thanks Best Regards On Sun, Nov 1, 2015 at 9:38 PM, Romi Kuntsman <r...@totango.com> wrote: > [adding dev list since it's probably a bug, but i'm not sure how to > reproduce so I can open a bug about it] > > Hi, > > I have a standalone Spark 1.4.0 cluster with 100s of applications running > every day. > > From time to time, the applications crash with the following error (see > below) > But at the same time (and also after that), other applications are > running, so I can safely assume the master and workers are working. > > 1. why is there a NullPointerException? (i can't track the scala stack > trace to the code, but anyway NPE is usually a obvious bug even if there's > actually a network error...) > 2. why can't it connect to the master? (if it's a network timeout, how to > increase it? i see the values are hardcoded inside AppClient) > 3. how to recover from this error? > > > ERROR 01-11 15:32:54,991 SparkDeploySchedulerBackend - Application > has been killed. Reason: All masters are unresponsive! Giving up. ERROR > ERROR 01-11 15:32:55,087 OneForOneStrategy - ERROR > logs/error.log > java.lang.NullPointerException NullPointerException > at > org.apache.spark.deploy.client.AppClient$ClientActor$$anonfun$receiveWithLogging$1.applyOrElse(AppClient.scala:160) > at > scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33) > at > scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33) > at > scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25) > at > org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:59) > at > org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:42) > at scala.PartialFunction$class.applyOrElse(PartialFunction.scala:118) > at > org.apache.spark.util.ActorLogReceive$$anon$1.applyOrElse(ActorLogReceive.scala:42) > at akka.actor.Actor$class.aroundReceive(Actor.scala:465) > at > org.apache.spark.deploy.client.AppClient$ClientActor.aroundReceive(AppClient.scala:61) > at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516) > at akka.actor.ActorCell.invoke(ActorCell.scala:487) > at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238) > at akka.dispatch.Mailbox.run(Mailbox.scala:220) > at > akka.dispatch.ForkJoinExecutorConfigurator$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) > ERROR 01-11 15:32:55,603 SparkContext - Error > initializing SparkContext. ERROR > java.lang.IllegalStateException: Cannot call methods on a stopped > SparkContext > at org.apache.spark.SparkContext.org > $apache$spark$SparkContext$$assertNotStopped(SparkContext.scala:103) > at > org.apache.spark.SparkContext.getSchedulingMode(SparkContext.scala:1501) > at > org.apache.spark.SparkContext.postEnvironmentUpdate(SparkContext.scala:2005) > at org.apache.spark.SparkContext.<init>(SparkContext.scala:543) > at > org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:61) > > > Thanks! > > *Romi Kuntsman*, *Big Data Engineer* > http://www.totango.com >
