[jira] Commented: (HADOOP-2919) Create fewer copies of buffer data during sort/spill

["Owen O'Malley (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/HADOOP-2919?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12583911#action_12583911 ] 

Owen O'Malley commented on HADOOP-2919:
---------------------------------------

I was concerned that TestMiniMRDFSSort was failing on Hudson with this patch, even though it was working on "real" machines. It looks like it was primarily resource starvation on the zones machines. I filed HADOOP-3142 and HADOOP-3143 to address the problems.

> Create fewer copies of buffer data during sort/spill
> ----------------------------------------------------
>
>                 Key: HADOOP-2919
>                 URL: https://issues.apache.org/jira/browse/HADOOP-2919
>             Project: Hadoop Core
>          Issue Type: Improvement
>          Components: mapred
>            Reporter: Chris Douglas
>            Assignee: Chris Douglas
>            Priority: Blocker
>             Fix For: 0.17.0
>
>         Attachments: 2919-0.patch, 2919-1.patch, 2919-2.patch, 2919-3.patch, 2919-4.patch, 2919-5.patch, 2919-6.patch, 2919-7.patch
>
>
> Currently, the sort/spill works as follows:
> Let r be the number of partitions
> For each call to collect(K,V) from map:
> * If buffers do not exist, allocate a new DataOutputBuffer to collect K,V bytes, allocate r buffers for collecting K,V offsets
> * Write K,V into buffer, noting offsets
> * Register offsets with associated partition buffer, allocating/copying accounting buffers if nesc
> * Calculate the total mem usage for buffer and all partition collectors by iterating over the collectors
> * If total mem usage is greater than half of io.sort.mb, then start a new thread to spill, blocking if another spill is in progress
> For each spill (assuming no combiner):
> * Save references to our K,V byte buffer and accounting data, setting the former to null (will be recreated on the next call to collect(K,V))
> * Open a SequenceFile.Writer for this partition
> * Sort each partition separately (the current version of sort reuses, but still requires wrapping, indices in IntWritable objects)
> * Build a RawKeyValueIterator of sorted data for the partition
> * Deserialize each key and value and call SequenceFile::append(K,V) on the writer for this partition
> There are a number of opportunities for reducing the number of copies, creations, and operations we perform in this stage, particularly since growing many of the buffers involved requires that we copy the existing data to the newly sized allocation.

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