Mailing-List: contact core-dev-help@hadoop.apache.org; run by ezmlm
Precedence: bulk
Reply-To: core-dev@hadoop.apache.org
Message-ID: <381030925.1242622905566.JavaMail.jira@brutus>
Date: Sun, 17 May 2009 22:01:45 -0700 (PDT)
From: "dhruba borthakur (JIRA)" <jira@apache.org>
To: core-dev@hadoop.apache.org
Subject: [jira] Commented: (HADOOP-5831) Implement memory-to-memory merge in
 the reduce
In-Reply-To: <1226149630.1242286365736.JavaMail.jira@brutus>
MIME-Version: 1.0
Content-Type: text/plain; charset=utf-8
Content-Transfer-Encoding: 7bit


    [ https://issues.apache.org/jira/browse/HADOOP-5831?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12710271#action_12710271 ] 

dhruba borthakur commented on HADOOP-5831:
------------------------------------------

This looks a really impressive performance gain! awesome.

> Implement memory-to-memory merge in the reduce
> ----------------------------------------------
>
>                 Key: HADOOP-5831
>                 URL: https://issues.apache.org/jira/browse/HADOOP-5831
>             Project: Hadoop Core
>          Issue Type: Improvement
>          Components: mapred
>            Reporter: Arun C Murthy
>            Assignee: Arun C Murthy
>             Fix For: 0.21.0
>
>
> HADOOP-3446 fixed the reduce to not flush the in-memory shuffled map-outputs before feeding to the reduce. However for latency-sensitive applications with lots of memory like the terasort this hurts performance since the fan-in for the final in-memory merge is too large (all 8000 map-outputs very in-memory) resulting in less than optimal performance.
> When I put in an intermediate memory-to-memory merge for the terasort's reduce (there-by avoiding disk i/o) to cut the fan-in from 8000 to <100 the 'reduce' phase (including the local datanode-write) sped-up 250% (from 10s to 4s). 

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