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From Prabhu Joseph <prabhujose.ga...@gmail.com>
Subject Re: Spark Executor retries infinitely
Date Mon, 01 Feb 2016 16:58:05 GMT
Thanks Ted. My concern is how to avoid these kind of user errors on a
production cluster, it would be better if Spark handles this instead of
creating an Executor for every second and fails and overloading the Spark
Master. Shall i report a Spark JIRA to handle this.


Thanks,
Prabhu Joseph


On Mon, Feb 1, 2016 at 9:09 PM, Ted Yu <yuzhihong@gmail.com> wrote:

> I haven't found config knob for controlling the retry count after brief
> search.
>
> According to
> http://www.oracle.com/technetwork/articles/java/g1gc-1984535.html ,
> default value for -XX:ParallelGCThreads= seems to be 8.
> This seems to explain why you got the VM initialization error.
>
> FYI
>
> On Mon, Feb 1, 2016 at 4:16 AM, Prabhu Joseph <prabhujose.gates@gmail.com>
> wrote:
>
>> Hi All,
>>
>>   When a Spark job (Spark-1.5.2) is submitted with a single executor and
>> if user passes some wrong JVM arguments with
>> spark.executor.extraJavaOptions, the first executor fails. But the job
>> keeps on retrying, creating a new executor and failing every tim*e, *until
>> CTRL-C is pressed*. *Do we have configuration to limit the retry
>> attempts.
>>
>> *Example:*
>>
>> ./spark-submit --class SimpleApp --master "spark://10.10.72.145:7077"
>> --conf "spark.executor.extraJavaOptions=-XX:+PrintGCDetails
>> -XX:+PrintGCTimeStamps -XX:+UseG1GC -XX:InitiatingHeapOccupancyPercent=35
>> -XX:ConcGCThreads=16" /SPARK/SimpleApp.jar
>>
>> Executor fails with
>>
>> Error occurred during initialization of VM
>> Can't have more ConcGCThreads than ParallelGCThreads.
>>
>> But the job does not exit, keeps on creating executors and retrying.
>> ..........
>> 16/02/01 06:54:28 INFO SparkDeploySchedulerBackend: *Granted executor ID
>> app-20160201065319-0014/2846* on hostPort 10.10.72.145:36558 with 12
>> cores, 2.0 GB RAM
>> 16/02/01 06:54:28 INFO AppClient$ClientEndpoint: Executor updated:
>> app-20160201065319-0014/2846 is now LOADING
>> 16/02/01 06:54:28 INFO AppClient$ClientEndpoint: Executor updated:
>> app-20160201065319-0014/2846 is now RUNNING
>> 16/02/01 06:54:28 INFO AppClient$ClientEndpoint: Executor updated:
>> app-20160201065319-0014/2846 is now EXITED (Command exited with code 1)
>> 16/02/01 06:54:28 INFO SparkDeploySchedulerBackend: Executor
>> app-20160201065319-0014/2846 removed: Command exited with code 1
>> 16/02/01 06:54:28 INFO SparkDeploySchedulerBackend: Asked to remove
>> non-existent executor 2846
>> 16/02/01 06:54:28 INFO AppClient$ClientEndpoint: *Executor added:
>> app-20160201065319-0014/2847* on
>> worker-20160131230345-10.10.72.145-36558 (10.10.72.145:36558) with 12
>> cores
>> 16/02/01 06:54:28 INFO SparkDeploySchedulerBackend: Granted executor ID
>> app-20160201065319-0014/2847 on hostPort 10.10.72.145:36558 with 12
>> cores, 2.0 GB RAM
>> 16/02/01 06:54:28 INFO AppClient$ClientEndpoint: Executor updated:
>> app-20160201065319-0014/2847 is now LOADING
>> 16/02/01 06:54:28 INFO AppClient$ClientEndpoint: Executor updated:
>> app-20160201065319-0014/2847 is now EXITED (Command exited with code 1)
>> 16/02/01 06:54:28 INFO SparkDeploySchedulerBackend: Executor
>> app-20160201065319-0014/2847 removed: Command exited with code 1
>> 16/02/01 06:54:28 INFO SparkDeploySchedulerBackend: Asked to remove
>> non-existent executor 2847
>> 16/02/01 06:54:28 INFO AppClient$ClientEndpoint:* Executor added:
>> app-20160201065319-0014/2848* on
>> worker-20160131230345-10.10.72.145-36558 (10.10.72.145:36558) with 12
>> cores
>> 16/02/01 06:54:28 INFO SparkDeploySchedulerBackend: Granted executor ID
>> app-20160201065319-0014/2848 on hostPort 10.10.72.145:36558 with 12
>> cores, 2.0 GB RAM
>> 16/02/01 06:54:28 INFO AppClient$ClientEndpoint: Executor updated:
>> app-20160201065319-0014/2848 is now LOADING
>> 16/02/01 06:54:28 INFO AppClient$ClientEndpoint: Executor updated:
>> app-20160201065319-0014/2848 is now RUNNING
>> ............
>>
>>
>>
>> Thanks,
>> Prabhu Joseph
>>
>>
>>
>

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