How to increase the Xmx of the workers ? *Thanks*, <https://in.linkedin.com/in/ramkumarcs31>
On Mon, Oct 5, 2015 at 3:48 PM, Ramkumar V <ramkumar.c...@gmail.com> wrote: > No. I didn't try to increase xmx. > > *Thanks*, > <https://in.linkedin.com/in/ramkumarcs31> > > > On Mon, Oct 5, 2015 at 1:36 PM, Jean-Baptiste Onofré <j...@nanthrax.net> > wrote: > >> Hi Ramkumar, >> >> did you try to increase Xmx of the workers ? >> >> Regards >> JB >> >> On 10/05/2015 08:56 AM, Ramkumar V wrote: >> >>> Hi, >>> >>> When i submit java spark job in cluster mode, i'm getting following >>> exception. >>> >>> *LOG TRACE :* >>> >>> INFO yarn.ExecutorRunnable: Setting up executor with commands: >>> List({{JAVA_HOME}}/bin/java, -server, -XX:OnOutOfMemoryError='kill >>> %p', -Xms1024m, -Xmx1024m, -Djava.io.tmpdir={{PWD}}/tmp, >>> '-Dspark.ui.port=0', '-Dspark.driver.port=48309', >>> -Dspark.yarn.app.container.log.dir=<LOG >>> _DIR>, org.apache.spark.executor.CoarseGrainedExecutorBackend, >>> --driver-url, akka.tcp://sparkDriver@ip >>> :port/user/CoarseGrainedScheduler, >>> --executor-id, 2, --hostname, hostname , --cores, 1, --app-id, >>> application_1441965028669_9009, --user-class-path, file:$PWD >>> /__app__.jar, --user-class-path, file:$PWD/json-20090211.jar, 1>, >>> <LOG_DIR>/stdout, 2>, <LOG_DIR>/stderr). >>> >>> I have a cluster of 11 machines (9 - 64 GB memory and 2 - 32 GB memory >>> ). my input data of size 128 GB. >>> >>> How to solve this exception ? is it depends on driver.memory and >>> execuitor.memory setting ? >>> >>> >>> *Thanks*, >>> <https://in.linkedin.com/in/ramkumarcs31> >>> >>> >> -- >> Jean-Baptiste Onofré >> jbono...@apache.org >> http://blog.nanthrax.net >> Talend - http://www.talend.com >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> For additional commands, e-mail: user-h...@spark.apache.org >> >> >
