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From "Owen O'Malley (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-2990) Ability to thread task execution
Date Mon, 10 Mar 2008 23:32:46 GMT

    [ https://issues.apache.org/jira/browse/HADOOP-2990?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12577250#action_12577250

Owen O'Malley commented on HADOOP-2990:

Have you tried using the java.nio.MappedByteBuffers? That should give you good performance
between multiple jvms. There is also already a mutli-threaded map runner that works well for
mappers. Do you have the problem with reduces, also? I multi-threaded reducer class might
be a good option depending on what is required.

> Ability to thread task execution
> --------------------------------
>                 Key: HADOOP-2990
>                 URL: https://issues.apache.org/jira/browse/HADOOP-2990
>             Project: Hadoop Core
>          Issue Type: Improvement
>          Components: mapred
>         Environment: All
>            Reporter: Holden Robbins
>   Original Estimate: 48h
>  Remaining Estimate: 48h
> Currently Hadoop spawns a single threaded JVM for each task.  While good for many tasks,
this does not maximize resource usage for slaves that have many cores (machines with more
cores are getting more cost effective everyday) _and_ are running jobs that require many gigabytes
of read-only in-memory resources to maximize throughput.  Running in separate JVMs requires
redundantly loading large amounts of data, reducing the possible number of parallel tasks
that can run per a machine even though more cpus are available.
> Adding this ability will give hadoop users the flexibility to balance their need for
maximizing memory usage & throughput and task segmentation.
> Note: This is a blocking bug in porting processes over to hadoop for my own organization.
 I am testing a patch for this now that leaves the existing behavior for single threaded operation
in-tact.  All synchronization is done through wrapper classes and helper methods and should
not add any overhead to non-threaded processes.

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