Mailing-List: contact mapreduce-issues-help@hadoop.apache.org; run by ezmlm
Precedence: bulk
Reply-To: mapreduce-issues@hadoop.apache.org
Message-ID: <6367426.322831281675803989.JavaMail.jira@thor>
Date: Fri, 13 Aug 2010 01:03:23 -0400 (EDT)
From: "Joydeep Sen Sarma (JIRA)" <jira@apache.org>
To: mapreduce-issues@hadoop.apache.org
Subject: [jira] Commented: (MAPREDUCE-1901) Jobs should not submit the same
 jar files over and over again
In-Reply-To: <16939351.139651277925770477.JavaMail.jira@thor>
MIME-Version: 1.0
Content-Type: text/plain; charset=utf-8
Content-Transfer-Encoding: 7bit


    [ https://issues.apache.org/jira/browse/MAPREDUCE-1901?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12898082#action_12898082 ] 

Joydeep Sen Sarma commented on MAPREDUCE-1901:
----------------------------------------------

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.

-- 
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.