[jira] Commented: (MAPREDUCE-1221) Kill tasks on a node if the free physical memory on that machine falls below a configured threshold

["Vinod K V (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/MAPREDUCE-1221?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12779821#action_12779821 ] 

Vinod K V commented on MAPREDUCE-1221:
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bq. 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.
This is not quite right. The TaskMemoryManager indeed looks at the memory usage of all the processes in the task's process-tree irrespective of whether each of them is a java program or otherwise. If one wishes to limit the physical memory usage, the tasks can be configured to be.

In any case, it currently works only on Linux, so if is another OS, it needs to be implemented there.

> 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
>            Reporter: dhruba borthakur
>            Assignee: dhruba borthakur
>
> 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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