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From "Amareshwari Sriramadasu (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAPREDUCE-1221) Kill tasks on a node if the free physical memory on that machine falls below a configured threshold
Date Wed, 31 Mar 2010 14:53:27 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-1221?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12851891#action_12851891
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Amareshwari Sriramadasu commented on MAPREDUCE-1221:
----------------------------------------------------

bq. First up: Do you agree that we need to fail the task and not just kill it, so that the
job fails fast?
One more thing to add here is  "If a task is failed, JobTracker will try to schedule the task
on different machine. If the task is killed, there are more chances that the task will be
re-executed on the same tracker".  

bq. If the total limit is violated, TaskTracker will kill the task with highest amount of
memory to relief the memory pressure.
So, if we kill a task with highest amount of memory, these are more chances that the task
will be executed on the same machine. Doesn't this trouble the tracker again?


> 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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