Re: Some spark apps fail with "All masters are unresponsive", while others pass normally

2015-11-09 Thread Akhil Das 
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  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 15:32:54,991SparkDeploySchedulerBackend - 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.(SparkContext.scala:543)
>   at
> org.apache.spark.api.java.JavaSparkContext.(JavaSparkContext.scala:61)
>
>
> Thanks!
>
> *Romi Kuntsman*, *Big Data Engineer*
> http://www.totango.com
>

Re: Some spark apps fail with "All masters are unresponsive", while others pass normally

2015-11-09 Thread Akhil Das 
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  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 
> 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  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 15:32:54,991SparkDeploySchedulerBackend - 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.(SparkContext.scala:543)
>>>   at
>>> org.apache.spark.api.java.JavaSparkContext.(JavaSparkContext.scala:61)
>>>
>>>
>>> Thanks!
>>>
>>> *Romi Kuntsman*, *Big Data Engineer*
>>> http://www.totango.com
>>>
>>
>>
>

Re: Some spark apps fail with "All masters are unresponsive", while others pass normally

2015-11-09 Thread Romi Kuntsman 
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 
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  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 15:32:54,991SparkDeploySchedulerBackend - 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.(SparkContext.scala:543)
>>   at
>> org.apache.spark.api.java.JavaSparkContext.(JavaSparkContext.scala:61)
>>
>>
>> Thanks!
>>
>> *Romi Kuntsman*, *Big Data Engineer*
>> http://www.totango.com
>>
>
>

Some spark apps fail with "All masters are unresponsive", while others pass normally

2015-11-01 Thread Romi Kuntsman 
[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 15:32:54,991SparkDeploySchedulerBackend - 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.(SparkContext.scala:543)
  at
org.apache.spark.api.java.JavaSparkContext.(JavaSparkContext.scala:61)


Thanks!

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