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https://issues.apache.org/jira/browse/MAPREDUCE-1221?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12837974#action_12837974
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Scott Chen commented on MAPREDUCE-1221:
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@Zheng: The failed test is because of MAPREDUCE-1520. It is not related to this
patch.
@Arun: Thank you very much for the comment. It's not late at all:) Using
setrlimit() is good for limiting the RSS memory for one task. But here we want
to limit the total RSS memory on the TT. And we want to kill the task with the
highest memory usage in this case. That is why we do it this way.
> Kill tasks on a node if the free physical memory on that machine falls below
> a configured threshold
> ---------------------------------------------------------------------------------------------------
>
> Key: MAPREDUCE-1221
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-1221
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: tasktracker
> Affects Versions: 0.22.0
> Reporter: dhruba borthakur
> Assignee: Scott Chen
> Fix For: 0.22.0
>
> Attachments: MAPREDUCE-1221-v1.patch, MAPREDUCE-1221-v2.patch,
> MAPREDUCE-1221-v3.patch
>
>
> The TaskTracker currently supports killing tasks if the virtual memory of a
> task exceeds a set of configured thresholds. I would like to extend this
> feature to enable killing tasks if the physical memory used by that task
> exceeds a certain threshold.
> On a certain operating system (guess?), if user space processes start using
> lots of memory, the machine hangs and dies quickly. This means that we would
> like to prevent map-reduce jobs from triggering this condition. From my
> understanding, the killing-based-on-virtual-memory-limits (HADOOP-5883) were
> designed to address this problem. This works well when most map-reduce jobs
> are Java jobs and have well-defined -Xmx parameters that specify the max
> virtual memory for each task. On the other hand, if each task forks off
> mappers/reducers written in other languages (python/php, etc), the total
> virtual memory usage of the process-subtree varies greatly. In these cases,
> it is better to use kill-tasks-using-physical-memory-limits.
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