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https://issues.apache.org/jira/browse/MAPREDUCE-1849?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12877277#action_12877277
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Ted Dunning commented on MAPREDUCE-1849:
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Another sweet trick for this would be to allow multiple modes of execution that
are all efficiently implemented. These should include local threaded,
non-redundant distributed map-reduce (a la Twister) and full-on Hadoop. That
gives highest speed for small jobs, medium speed for medium jobs at the cost of
task failure = job resubmit and full scalability and reliability for the
largest jobs.
Right now, anything but full scale hadoop execution is the red-headed child and
gets no love.
> Implement a FlumeJava-like library for operations over parallel collections
> using Hadoop MapReduce
> --------------------------------------------------------------------------------------------------
>
> Key: MAPREDUCE-1849
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-1849
> Project: Hadoop Map/Reduce
> Issue Type: New Feature
> Reporter: Jeff Hammerbacher
>
> The API used internally at Google is described in great detail at
> http://portal.acm.org/citation.cfm?id=1806596.1806638.
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