[jira] Updated: (MAPREDUCE-64) Map-side sort is hampered by io.sort.record.percent

["Chris Douglas (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MAPREDUCE-64?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Chris Douglas updated MAPREDUCE-64:
-----------------------------------

    Status: Open  (was: Patch Available)

The patch no longer applies after HADOOP-1147

> Map-side sort is hampered by io.sort.record.percent
> ---------------------------------------------------
>
>                 Key: MAPREDUCE-64
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-64
>             Project: Hadoop Map/Reduce
>          Issue Type: Bug
>            Reporter: Arun C Murthy
>            Assignee: Chris Douglas
>         Attachments: M64-0.patch, M64-0i.png, M64-1.patch, M64-1i.png, M64-2.patch, M64-2i.png, M64-3.patch
>
>
> Currently io.sort.record.percent is a fairly obscure, per-job configurable, expert-level parameter which controls how much accounting space is available for records in the map-side sort buffer (io.sort.mb). Typically values for io.sort.mb (100) and io.sort.record.percent (0.05) imply that we can store ~350,000 records in the buffer before necessitating a sort/combine/spill.
> However for many applications which deal with small records e.g. the world-famous wordcount and it's family this implies we can only use 5-10% of io.sort.mb i.e. (5-10M) before we spill inspite of having _much_ more memory available in the sort-buffer. The word-count for e.g. results in ~12 spills (given hdfs block size of 64M). The presence of a combiner exacerbates the problem by piling serialization/deserialization of records too...
> Sure, jobs can configure io.sort.record.percent, but it's tedious and obscure; we really can do better by getting the framework to automagically pick it by using all available memory (upto io.sort.mb) for either the data or accounting.

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