[jira] [Reopened] (MAPREDUCE-1220) Implement an in-cluster LocalJobRunner

["Arun C Murthy (Reopened) (JIRA)" <ji...@apache.org>]

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

Arun C Murthy reopened MAPREDUCE-1220:
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> 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
>             Fix For: 0.23.0
>
>         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.v14b.ytrunk-hadoop-mapreduce.delta.patch.txt, MR-1220.v15.ytrunk-hadoop-mapreduce.delta.patch.txt, MR-1220.v1b.sshot-02-jobdetails.jsp.png, MR-1220.v1b.sshot-03-jobdetailshistory.jsp.png, MR-1220.v2.trunk-hadoop-mapreduce.patch.txt, MR-1220.v2.trunk-hadoop-mapreduce.patch.txt, MR-1220.v2b.sshot-01-jobtracker.jsp.png, 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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