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From "Dong Yang (JIRA)" <j...@apache.org>
Subject [jira] Updated: (MAPREDUCE-1270) Hadoop C++ Extention
Date Mon, 15 Mar 2010 03:59:30 GMT

     [ https://issues.apache.org/jira/browse/MAPREDUCE-1270?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Dong Yang updated MAPREDUCE-1270:
---------------------------------

    Attachment: Overall Design of Hadoop C++ Extension.doc

Hadoop C++ Extension (HCE for short) is a framework for making mapreduce more stable and faster.
Here is the overall design of HCE, welcome to give your viewpoints on its practical implementation.

> 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
>         Attachments: Overall Design of Hadoop C++ Extension.doc
>
>
>   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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