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https://issues.apache.org/jira/browse/MAPREDUCE-5785?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14225462#comment-14225462
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Jian He commented on MAPREDUCE-5785:
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After this patch, job somehow fails due to not able to launch task container
{{Error: Could not find or load main class null}}. (might be my own setup
problem)
> Derive heap size or mapreduce.*.memory.mb automatically
> -------------------------------------------------------
>
> Key: MAPREDUCE-5785
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-5785
> Project: Hadoop Map/Reduce
> Issue Type: New Feature
> Components: mr-am, task
> Reporter: Gera Shegalov
> Assignee: Gera Shegalov
> Fix For: 3.0.0
>
> Attachments: MAPREDUCE-5785.v01.patch, MAPREDUCE-5785.v02.patch,
> MAPREDUCE-5785.v03.patch, mr-5785-4.patch, mr-5785-5.patch, mr-5785-6.patch
>
>
> Currently users have to set 2 memory-related configs per Job / per task type.
> One first chooses some container size map reduce.\*.memory.mb and then a
> corresponding maximum Java heap size Xmx < map reduce.\*.memory.mb. This
> makes sure that the JVM's C-heap (native memory + Java heap) does not exceed
> this mapreduce.*.memory.mb. If one forgets to tune Xmx, MR-AM might be
> - allocating big containers whereas the JVM will only use the default
> -Xmx200m.
> - allocating small containers that will OOM because Xmx is too high.
> With this JIRA, we propose to set Xmx automatically based on an empirical
> ratio that can be adjusted. Xmx is not changed automatically if provided by
> the user.
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