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From "Arun C Murthy (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAPREDUCE-1901) Jobs should not submit the same jar files over and over again
Date Wed, 30 Jun 2010 20:21:51 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-1901?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12884049#action_12884049
] 

Arun C Murthy commented on MAPREDUCE-1901:
------------------------------------------

+1

A straight-forward way is to use the DistributedCache directly, an easy change is to get the
JobSubmissionProtocol use either a custom jar (as today) or just refer to the jars in the
DistributedCache.

> 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
>
> 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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