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Posted to mapreduce-issues@hadoop.apache.org by "Scott Chen (JIRA)" <ji...@apache.org> on 2010/04/14 23:20:52 UTC
[jira] Updated: (MAPREDUCE-1221) Kill tasks on a node if the free
physical memory on that machine falls below a configured threshold
[ https://issues.apache.org/jira/browse/MAPREDUCE-1221?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Scott Chen updated MAPREDUCE-1221:
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Status: Open (was: Patch Available)
> 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, MAPREDUCE-1221-v4.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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