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From Akhil Das <ak...@sigmoidanalytics.com>
Subject Re: Some spark apps fail with "All masters are unresponsive", while others pass normally
Date Mon, 09 Nov 2015 16:00:15 GMT
Did you find anything regarding the OOM in the executor logs?

Thanks
Best Regards

On Mon, Nov 9, 2015 at 8:44 PM, Romi Kuntsman <romi@totango.com> wrote:

> 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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