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From "Greg Roelofs (JIRA)" <j...@apache.org>
Subject [jira] Updated: (MAPREDUCE-1220) Implement an in-cluster LocalJobRunner
Date Tue, 08 Mar 2011 16:20:01 GMT

     [ https://issues.apache.org/jira/browse/MAPREDUCE-1220?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Greg Roelofs updated MAPREDUCE-1220:
------------------------------------

    Attachment: MR-1220.v13.ytrunk-hadoop-mapreduce.delta.patch.txt

Part 6/8: MR-1220.v13.ytrunk-hadoop-mapreduce.delta.patch.txt

add support for compressed map outputs

> Implement an in-cluster LocalJobRunner
> --------------------------------------
>
>                 Key: MAPREDUCE-1220
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1220
>             Project: Hadoop Map/Reduce
>          Issue Type: New Feature
>          Components: client, jobtracker
>            Reporter: Arun C Murthy
>            Assignee: Greg Roelofs
>         Attachments: MAPREDUCE-1220_yhadoop20.patch, MR-1220.v1.trunk-hadoop-common.Progress-dumper.patch.txt,
MR-1220.v10e-v11c-v12b.ytrunk-hadoop-mapreduce.delta.patch.txt, MR-1220.v13.ytrunk-hadoop-mapreduce.delta.patch.txt,
MR-1220.v2.trunk-hadoop-mapreduce.patch.txt, MR-1220.v2.trunk-hadoop-mapreduce.patch.txt,
MR-1220.v6.ytrunk-hadoop-mapreduce.patch.txt, MR-1220.v7.ytrunk-hadoop-mapreduce.delta.patch.txt,
MR-1220.v8b.ytrunk-hadoop-mapreduce.delta.patch.txt, MR-1220.v9c.ytrunk-hadoop-mapreduce.delta.patch.txt
>
>
> Currently very small map-reduce jobs suffer from latency issues due to overheads in Hadoop
Map-Reduce such as scheduling, jvm startup etc. We've periodically tried to optimize all parts
of framework to achieve lower latencies.
> I'd like to turn the problem around a little bit. I propose we allow very small jobs
to run as a single task job with multiple maps and reduces i.e. similar to our current implementation
of the LocalJobRunner. Thus, under certain conditions (maybe user-set configuration, or if
input data is small i.e. less a DFS blocksize) we could launch a special task which will run
all maps in a serial manner, followed by the reduces. This would really help small jobs achieve
significantly smaller latencies, thanks to lesser scheduling overhead, jvm startup, lack of
shuffle over the network etc. 
> This would be a huge benefit, especially on large clusters, to small Hive/Pig queries.
> Thoughts?

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