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https://issues.apache.org/jira/browse/MAPREDUCE-1221?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12838074#action_12838074
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Arun C Murthy commented on MAPREDUCE-1221:
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Scott, as I said, it is reasonably to track either virtual memory or physical
memory or both.
bq. The other main reason that we want to do this is that per task
virtual-memory-limit is an API change for our users.
A new feature might imply change, no?
OTOH you could get away with simply setting the default values to be reasonable
for a wide-variety of uses so users do not have to do anything.
bq. I think it is may not be that bad that we kill the task.
Like I said, the problem is that there is no predictability. What if a job gets
unlucky and it's 4th attempt gets killed because it happened to run on a node
where a rouge task of some other job ... again, predictability is very
important. Penalizing the right task is equally important.
> 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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