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Posted to mapreduce-issues@hadoop.apache.org by "Harsh J (JIRA)" <ji...@apache.org> on 2012/04/21 19:28:35 UTC
[jira] [Updated] (MAPREDUCE-3812) Lower default allocation sizes,
fix allocation configurations and document them
[ https://issues.apache.org/jira/browse/MAPREDUCE-3812?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Harsh J updated MAPREDUCE-3812:
-------------------------------
Description:
After a few performance improvements tracked at MAPREDUCE-3561, like MAPREDUCE-3511 and MAPREDUCE-3567, even a 100K maps job can also run within 1GB vmem. We earlier increased AM slot size from 1 slot to two slots to work around the issues with AM heap. Now that those are fixed, we should go back to 1GB.
This is just a configuration change.
[P.s.]:
- Currently min/max alloc is set at a per-scheduler config level, which makes no sense as there's no way to run multiple schedulers anyway. Switch configs to use a generic RM-config.
- The min/max alloc configs aren't documented and we ought to document it (i.e. MAPREDUCE-4027)
- 1 GB is perhaps too high for a slot's minimum. While job defaults can be left at such values, we should lower the minimum alloc to 128 MB to allow special requests of low memory out of the box itself. Shouldn't impact MR App in any way.
was:
After a few performance improvements tracked at MAPREDUCE-3561, like MAPREDUCE-3511 and MAPREDUCE-3567, even a 100K maps job can also run within 1GB vmem. We earlier increased AM slot size from 1 slot to two slots to work around the issues with AM heap. Now that those are fixed, we should go back to 1GB.
This is just a configuration change.
Target Version/s: 2.0.0, trunk (was: trunk, 2.0.0)
Summary: Lower default allocation sizes, fix allocation configurations and document them (was: Change default memory slot sizes to be 1.5GB)
Updated title and description
> Lower default allocation sizes, fix allocation configurations and document them
> -------------------------------------------------------------------------------
>
> Key: MAPREDUCE-3812
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-3812
> Project: Hadoop Map/Reduce
> Issue Type: Sub-task
> Components: mrv2, performance
> Affects Versions: 0.23.0
> Reporter: Vinod Kumar Vavilapalli
> Assignee: Harsh J
> Attachments: MAPREDUCE-3812-20120205.txt, MAPREDUCE-3812-20120206.1.txt, MAPREDUCE-3812-20120206.txt, MAPREDUCE-3812.patch, MAPREDUCE-3812.patch
>
>
> After a few performance improvements tracked at MAPREDUCE-3561, like MAPREDUCE-3511 and MAPREDUCE-3567, even a 100K maps job can also run within 1GB vmem. We earlier increased AM slot size from 1 slot to two slots to work around the issues with AM heap. Now that those are fixed, we should go back to 1GB.
> This is just a configuration change.
> [P.s.]:
> - Currently min/max alloc is set at a per-scheduler config level, which makes no sense as there's no way to run multiple schedulers anyway. Switch configs to use a generic RM-config.
> - The min/max alloc configs aren't documented and we ought to document it (i.e. MAPREDUCE-4027)
> - 1 GB is perhaps too high for a slot's minimum. While job defaults can be left at such values, we should lower the minimum alloc to 128 MB to allow special requests of low memory out of the box itself. Shouldn't impact MR App in any way.
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