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https://issues.apache.org/jira/browse/MAPREDUCE-1901?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12898082#action_12898082
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Joydeep Sen Sarma commented on MAPREDUCE-1901:
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it's _almost_ in production :-) - the patch posted here had some bugs. we have
final patch for 20 available - but have been trying to get the one for trunk
into shape. should post soon.
try running hadoop in debug log4j mode. u would get a trace of all those jars
being uploaded to hdfs. it's ridiculous.
> Jobs should not submit the same jar files over and over again
> -------------------------------------------------------------
>
> Key: MAPREDUCE-1901
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-1901
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Reporter: Joydeep Sen Sarma
> Attachments: 1901.PATCH
>
>
> Currently each Hadoop job uploads the required resources
> (jars/files/archives) to a new location in HDFS. Map-reduce nodes involved in
> executing this job would then download these resources into local disk.
> In an environment where most of the users are using a standard set of jars
> and files (because they are using a framework like Hive/Pig) - the same jars
> keep getting uploaded and downloaded repeatedly. The overhead of this
> protocol (primarily in terms of end-user latency) is significant when:
> - the jobs are small (and conversantly - large in number)
> - Namenode is under load (meaning hdfs latencies are high and made worse, in
> part, by this protocol)
> Hadoop should provide a way for jobs in a cooperative environment to not
> submit the same files over and again. Identifying and caching execution
> resources by a content signature (md5/sha) would be a good alternative to
> have available.
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