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From Romi Kuntsman <r...@totango.com>
Subject Re: Some spark apps fail with "All masters are unresponsive", while others pass normally
Date Mon, 09 Nov 2015 15:14:25 GMT
If they have a problem managing memory, wouldn't there should be a OOM?
Why does AppClient throw a NPE?

*Romi Kuntsman*, *Big Data Engineer*
http://www.totango.com

On Mon, Nov 9, 2015 at 4:59 PM, Akhil Das <akhil@sigmoidanalytics.com>
wrote:

> 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 <romi@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
>>
>
>

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