Can you attach the logs where this is failing? From: Sven Krasser <kras...@gmail.com> Date: Tuesday, January 27, 2015 at 4:50 PM To: Guru Medasani <gdm...@outlook.com> Cc: Sandy Ryza <sandy.r...@cloudera.com>, Antony Mayi <antonym...@yahoo.com>, "user@spark.apache.org" <user@spark.apache.org> Subject: Re: java.lang.OutOfMemoryError: GC overhead limit exceeded
Since it's an executor running OOM it doesn't look like a container being killed by YARN to me. As a starting point, can you repartition your job into smaller tasks? -Sven On Tue, Jan 27, 2015 at 2:34 PM, Guru Medasani <gdm...@outlook.com> wrote: Hi Anthony, What is the setting of the total amount of memory in MB that can be allocated to containers on your NodeManagers? yarn.nodemanager.resource.memory-mb Can you check this above configuration in yarn-site.xml used by the node manager process? -Guru Medasani From: Sandy Ryza <sandy.r...@cloudera.com> Date: Tuesday, January 27, 2015 at 3:33 PM To: Antony Mayi <antonym...@yahoo.com> Cc: "user@spark.apache.org" <user@spark.apache.org> Subject: Re: java.lang.OutOfMemoryError: GC overhead limit exceeded Hi Antony, If you look in the YARN NodeManager logs, do you see that it's killing the executors? Or are they crashing for a different reason? -Sandy On Tue, Jan 27, 2015 at 12:43 PM, Antony Mayi <antonym...@yahoo.com.invalid> wrote: Hi, I am using spark.yarn.executor.memoryOverhead=8192 yet getting executors crashed with this error. does that mean I have genuinely not enough RAM or is this matter of config tuning? other config options used: spark.storage.memoryFraction=0.3 SPARK_EXECUTOR_MEMORY=14G running spark 1.2.0 as yarn-client on cluster of 10 nodes (the workload is ALS trainImplicit on ~15GB dataset) thanks for any ideas, Antony. -- http://sites.google.com/site/krasser/?utm_source=sig
