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From "Karthik Kambatla (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAPREDUCE-4502) Multi-level aggregation with combining the result of maps per node/rack
Date Mon, 10 Sep 2012 00:41:08 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-4502?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13451720#comment-13451720
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Karthik Kambatla commented on MAPREDUCE-4502:
---------------------------------------------

Tsuyoshi, thanks for the design doc. The design seems reasonable for container-level aggregation.

I might have missed something here - could you please comment on the following details for
more clarity.
# Is the local aggregation done asynchronously as the mappers process respective input?
# Will there be one LocalAggregator and one ShuffleHandler per each reducer? Or, is it a single
LocalAggregator/ShuffleHandler daemon with relevant thread(pool)s per container?
# The current design doc seems to be aimed at aggregation per container. The bigger goal being
aggregation and node/rack levels, does the same design extend/apply to the final goal? 
                
> Multi-level aggregation with combining the result of maps per node/rack
> -----------------------------------------------------------------------
>
>                 Key: MAPREDUCE-4502
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-4502
>             Project: Hadoop Map/Reduce
>          Issue Type: Improvement
>          Components: applicationmaster, mrv2
>            Reporter: Tsuyoshi OZAWA
>            Assignee: Tsuyoshi OZAWA
>         Attachments: speculative_draft.pdf
>
>
> The shuffle costs is expensive in Hadoop in spite of the existence of combiner, because
the scope of combining is limited within only one MapTask. To solve this problem, it's a good
way to aggregate the result of maps per node/rack by launch combiner.
> This JIRA is to implement the multi-level aggregation infrastructure, including combining
per container(MAPREDUCE-3902 is related), coordinating containers by application master without
breaking fault tolerance of jobs.

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