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https://issues.apache.org/jira/browse/MAPREDUCE-1404?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12804048#action_12804048
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Hemanth Yamijala commented on MAPREDUCE-1404:
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Is this the right direction ? cluster_setup.xml contains elaborate steps to 
properly configure an HDFS / mapreduce cluster. Shouldn't the mapreduce parts 
be available under the mapreduce project, in the spirit of project split ? 
Indeed, given that 'common' is just a set of utility libraries, the real crux 
of cluster_setup will be in the HDFS and mapreduce subprojects - like how to 
setup an HDFS cluster and how to setup a mapreduce cluster. 

>From a developer / committer perspective, any patch of HDFS or mapreduce that 
>introduces a change that we think influences cluster setup of the respective 
>component will then generate two JIRAs - one for the code change and another 
>for the documentation. The synchronization of these patches will become an 
>overhead for committers, IMHO.

If we do decide to go with just one version under common, we should make sure 
to merge changes done to the mapreduce parts of cluster_setup.xml with common's 
version. I remember having reviewed changes to cluster_setup.xml (involving 
mapreduce parts) and committing them here. But I'd be more interested to know 
if we can come up with a different organization.

> Hadoop M/R Docs - delete 1 doc file that does not belong under M/R
> ------------------------------------------------------------------
>
>                 Key: MAPREDUCE-1404
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1404
>             Project: Hadoop Map/Reduce
>          Issue Type: Task
>          Components: documentation
>    Affects Versions: 0.21.0
>            Reporter: Corinne Chandel
>            Assignee: Corinne Chandel
>            Priority: Blocker
>             Fix For: 0.21.0
>
>
> Delete this file from Hadoop Mapreduce TRUNK 
> \src\docs\src\documentation\content\xdocs\cluster_setup.xml   (this file 
> already in (and belongs in) Hadoop COMMON TRUNK)

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