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From "Junjie Liang (JIRA)" <j...@apache.org>
Subject [jira] Updated: (MAPREDUCE-1901) Jobs should not submit the same jar files over and over again
Date Fri, 05 Nov 2010 23:44:48 GMT

     [ https://issues.apache.org/jira/browse/MAPREDUCE-1901?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Junjie Liang updated MAPREDUCE-1901:
------------------------------------

    Attachment: 1901.PATCH

This patch depends on HADOOP-7022 for a small tweak to the MD5Hash function, where we keep
track of the file size when we calculate the hash of a file. It is also a (combied) fix for
MAPREDUCE-1902.

> 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, 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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