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https://issues.apache.org/jira/browse/MAPREDUCE-1270?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12841070#action_12841070
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Wang Shouyan commented on MAPREDUCE-1270:
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"In terms of apis, as I previously mentioned I stronly recommend you start
using the Hadoop Pipes apis and enhance it - this will ensure compatibility
between Hadoop Pipes and HCE - again, please consider moving the
sort/shuffle/merge to Hadoop Pipes as I recommended previously."
I do not agree with this opinion, if we need to establish standards of c++
API, I don't think we need to completely compatible with pipes API， because I
don't think pipes API is carefully considerated, may be for compatibility of
some other code, but never been discussed adequately。
If we do need a C++ API , we should consider usability and extensibility more
then compatibility, because I don't realize such compatibility problem is a
problem for most users .
If for usability and extensibility, any suggestion is welcome.
> 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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