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https://issues.apache.org/jira/browse/MAPREDUCE-326?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12834405#action_12834405
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Owen O'Malley commented on MAPREDUCE-326:
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{quote}
If I understand the current proposal correctly, we could have a join where one
mapper class is pulling a big select statement from a DB, another is crunching
some big compressed sequence files, and another is pulling in a bunch of tiny
Hive partitions using CombineFileInput, without them stepping all over each
other and creating "last one wins" configuration conditions.
{quote}
Tom's current proposal doesn't address this at all. Please look at
MAPREDUCE-1183, which actually does.
I implemented the first version of pipes. I know what is required for this kind
of framework. Tom's proposal doesn't help at all. My proposal for a
ByteBuffer-based MapContext write method is necessary and *sufficient*.
> The lowest level map-reduce APIs should be byte oriented
> --------------------------------------------------------
>
> Key: MAPREDUCE-326
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-326
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Reporter: eric baldeschwieler
> Attachments: MAPREDUCE-326-api.patch, MAPREDUCE-326.pdf
>
>
> As discussed here:
> https://issues.apache.org/jira/browse/HADOOP-1986#action_12551237
> The templates, serializers and other complexities that allow map-reduce to
> use arbitrary types complicate the design and lead to lots of object creates
> and other overhead that a byte oriented design would not suffer. I believe
> the lowest level implementation of hadoop map-reduce should have byte string
> oriented APIs (for keys and values). This API would be more performant,
> simpler and more easily cross language.
> The existing API could be maintained as a thin layer on top of the leaner API.
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