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From "Scott Chen (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAPREDUCE-961) ResourceAwareLoadManager to dynamically decide new tasks based on current CPU/memory load on TaskTracker(s)
Date Mon, 02 Nov 2009 23:30:59 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-961?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12772750#action_12772750
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Scott Chen commented on MAPREDUCE-961:
--------------------------------------

Hi Matei,

Thanks for the comment.

1. I agree. It is good to keep this option.
2. You are right about MemBasedLoadManger.canLaunchTask. I will make the necessary change.
3. I agree. There should still be max slots limit. But we can make it higher since now we
have the resource monitoring.
4.1 There are some per task memory limit configuration (HADOOP-5881). But those are for virtual
memory. We may need something similar but for physical memory.
4.2 I see. So we may need to count the previous continuously launched map tasks in canLauch
task and return a false if there are too many map tasks launched in a row. Is this correct?


You comments are very useful. I will make the necessary changes and upload a new patch soon.
Let me know if you have other suggestions. Thanks!

> ResourceAwareLoadManager to dynamically decide new tasks based on current CPU/memory
load on TaskTracker(s)
> -----------------------------------------------------------------------------------------------------------
>
>                 Key: MAPREDUCE-961
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-961
>             Project: Hadoop Map/Reduce
>          Issue Type: New Feature
>          Components: contrib/fair-share
>            Reporter: dhruba borthakur
>            Assignee: dhruba borthakur
>         Attachments: HIVE-961.patch, MAPREDUCE-961-v2.patch
>
>
> Design and develop a ResouceAwareLoadManager for the FairShare scheduler that dynamically
decides how many maps/reduces to run on a particular machine based on the CPU/Memory/diskIO/network
usage in that machine.  The amount of resources currently used on each task tracker is being
fed into the ResourceAwareLoadManager in real-time via an entity that is external to Hadoop.

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