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https://issues.apache.org/jira/browse/MAPREDUCE-1270?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12840795#action_12840795
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Arun C Murthy commented on MAPREDUCE-1270:
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bq. The bad news is that our design document is written in Chinese. My team
members and I will put some design details step by step in the next few days.
Thanks!
bq. For Q3, we indeed change the interface of Combiner, while the semantics for
Combiner is the same with Java Map-Reduce. It prevents mistaken use of Combiner.
It's a reasonable argument, but I'd recommend we stay compatible with both Java
Map-Reduce and Pipes by having the same interface. FYI: both Java and Pipes
explicitly disallow changing of keys in the combiner in the 'contract'. If the
user does go ahead and change the key the application is not guaranteed to work.
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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.
> 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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