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https://issues.apache.org/jira/browse/MAPREDUCE-1901?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12892198#action_12892198
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Amareshwari Sriramadasu commented on MAPREDUCE-1901:
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bq. Currently, files loaded through hadoop libjars/files/archives mechanism are
copied onto HDFS and removed on every job.
JobClient copies the files/archives passed through -files, -libjars ad
-archives options if they are in local file system. If they are already in
HDFS, no copying is done. Then, the hdfs paths are added to distributedCache.
Thus, Arun pointed in earlier comment, DistributedCache does not copy any
files to dfs.
I think this issue would involve picking up job jar from a dfs path directly
instead of local fs.
> 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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