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Posted to common-dev@hadoop.apache.org by "Arun C Murthy (JIRA)" <ji...@apache.org> on 2007/09/03 05:51:19 UTC

[jira] Commented: (HADOOP-1815) Separate client and server jars

    [ https://issues.apache.org/jira/browse/HADOOP-1815?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#action_12524426 ] 

Arun C Murthy commented on HADOOP-1815:
---------------------------------------

bq. Ah. I think one could make a case for a hadoop-user jar, that includes standard, supported stuff, like distcp, aggregate, etc.

Essentially they are standard, supported tools/utilities for users... do we have a case for *hadoop-tools.jar* then?
One other nice tool would be one which converts a bunch on input formats (text, compressed text etc.) to sequence files (say txt2seq for now). We could encourage users to contribute more of these utils.

Along similar lines, it would nice to encourage people to contribute their actual mapper/reducer implementations and build up a comprehensive {{org.apache.hadoop.mapred.lib}}, clearly with riders about IP etc. I'm not clear whether it would help to have a hadoop-mapred-lib.jar though. What do others think, should I file a jira?


> Separate client and server jars
> -------------------------------
>
>                 Key: HADOOP-1815
>                 URL: https://issues.apache.org/jira/browse/HADOOP-1815
>             Project: Hadoop
>          Issue Type: Bug
>          Components: build
>    Affects Versions: 0.14.0
>         Environment: All
>            Reporter: Milind Bhandarkar
>             Fix For: 0.15.0
>
>
> For the ease of deployment, one should not have to change the server jars, and restart clusters, when minor features on the client side are changed. This requireds separating client and server jars for hadoop. Version numbers appended to hadoop jars can reflect the compatibility. e.g. the server jar could be at 0.13.1, and the client jar could be at 0.13.2. In short, we can treat the part following 0. as the "major" version number for now.
> This allows major client frameworks such as streaming and Pig happy. To my knowledge, Pig uses hadoop's default jobclient. Whereas streaming uses its own jobclient. I would love to change streaming to use the default hadoop jobclient, if I can make modifications to it (e.g. to print more stats that are available from TaskReport, for example), if I do not have to deploy the new version of the whole jar to the backend and restart the mapreduce cluster.
> (I thought there was already a bug filed for separating the client and server jar, but I could not find it. Hence the new Jira. Sorry about duplication, if any.)

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