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From "Owen O'Malley (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-5299) Reducer inputs should be spilled to HDFS rather than local disk.
Date Mon, 23 Feb 2009 15:46:02 GMT

    [ https://issues.apache.org/jira/browse/HADOOP-5299?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12675952#action_12675952
] 

Owen O'Malley commented on HADOOP-5299:
---------------------------------------

I really don't think map/reduce should use an internal evolving api of hdfs. That would completely
break the possibility of upgrading hdfs and map/reduce independently.

Writing intermediates to hdfs, as you know, is not and can't be a performance gain. Clearly
the goal is to remove the task tracker's attempts at managing local store. So, I agree with
Eric that this jira isn't very motivated without the map outputs too. Unlike Eric, I don't
think *either* is a good idea.

> Reducer inputs should be spilled to HDFS rather than local disk.
> ----------------------------------------------------------------
>
>                 Key: HADOOP-5299
>                 URL: https://issues.apache.org/jira/browse/HADOOP-5299
>             Project: Hadoop Core
>          Issue Type: Improvement
>          Components: mapred
>    Affects Versions: 0.19.0
>         Environment: All
>            Reporter: Milind Bhandarkar
>
> Currently, both map outputs and reduce inputs are stored on local disks of tasktrackers.
(Un) Availability of local disk space for intermediate data is seen as a major factor in job
failures. 
> The suggested solution is to store these intermediate data on HDFS (maybe with replication
factor of 1). However, the main blocker issue with that solution is that lots of temporary
names (proportional to total number of maps), can overwhelm the namenode, especially since
the map outputs are typically small (most produce one block output).
> Also, as we see in many applications, the map outputs can be estimated more accurately,
and thus users can plan accordingly, based on available local disk space.
> However, the reduce input sizes can vary a lot, especially for skewed data (or because
of bad partitioning.)
> So, I suggest that it makes more sense to keep map outputs on local disks, but the reduce
inputs (when spilled from reducer memory) should go to HDFS.
> Adding a configuration variable to indicate the filesystem to be used for reduce-side
spills would let us experiment and compare the efficiency of this new scheme.

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