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From "Wang Shouyan (JIRA)" <j...@apache.org>
Subject [jira] Created: (MAPREDUCE-1270) Hadoop C++ Extention
Date Mon, 07 Dec 2009 08:10:18 GMT
Hadoop C++ Extention
--------------------

                 Key: MAPREDUCE-1270
                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1270
             Project: Hadoop Map/Reduce
          Issue Type: Improvement
          Components: task
    Affects Versions: 0.20.1
         Environment:  hadoop linux
            Reporter: Wang Shouyan


  Hadoop C++ extension is an internal project in baidu, We start it for these reasons:
   1  To provide C++ API. We mostly use Streaming before, and we also try to use PIPES, but
we do not find PIPES is more efficient than Streaming. So we 

think a new C++ extention is needed for us.
   2  Even using PIPES or Streaming, it is hard to control memory of hadoop map/reduce Child
JVM.
   3  It costs so much to read/write/sort TB/PB data by Java. When using PIPES or Streaming,
pipe or socket is not efficient to carry so huge data.

   What we want to do: 
   1 We do not use map/reduce Child JVM to do any data processing, which just prepares environment,
starts C++ mapper, tells mapper which split it should  deal with, and reads report from mapper
until that finished. The mapper will read record, ivoke user defined map, to do partition,
write spill, combine and merge into file.out. We think these operations can be done by C++
code.
   2 Reducer is similar to mapper, it was started after sort finished, it read from sorted
files, ivoke user difined reduce, and write to user defined record writer.
   3 We also intend to rewrite shuffle and sort with C++, for efficience and memory control.
   at first, 1 and 2, then 3.  

   What's the difference with PIPES:
   1 Yes, We will reuse most PIPES code.
   2 And, We should do it more completely, nothing changed in scheduling and management, but
everything in execution.

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