2009/12/23 Chris Douglas (JIRA) <j...@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) > > > 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, M64-4.patch, M64-5.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. > > -- > This message is automatically generated by JIRA. > - > You can reply to this email to add a comment to the issue online. > >
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