hadoop-mapreduce-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Owen O'Malley (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAPREDUCE-2168) We should implement limits on shuffle connections to TaskTracker per job
Date Mon, 01 Nov 2010 16:03:27 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-2168?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12927024#action_12927024

Owen O'Malley commented on MAPREDUCE-2168:

I misread your problem. A single reduce won't slam a single node, but the entire set of reduces
will. The new shuffle does a better job of backing off from the shuffle, but the fundamental
problem is that in order to know which map a given connection is looking for you, the code
needs to accept it. Once it has accepted it, it is better to service the request rather than
put it back on the queue.

You might try upgrading the version of Jetty. The version of jetty that we are currently using
has some over aggressive locking that leads to under-utilization. See HADOOP-6882.

> We should  implement limits on shuffle connections to TaskTracker per job
> -------------------------------------------------------------------------
>                 Key: MAPREDUCE-2168
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-2168
>             Project: Hadoop Map/Reduce
>          Issue Type: Improvement
>            Reporter: Liyin Liang
> As trailing map tasks will be attacked by all reduces simultaneously, all the worker
threads that for the http server of a TaskTracker may be occupied  by one job's reduce tasks
to fetch map outputs. Then this tasktracker's iowait and load will be very high (100+ in our
cluster, we set tasktracker.http.threads with 100). What's more, other job's reduces have
to wait some time (may be several minutes) to connect to the TaskTracker to fetch there map's
> So I think we should implement limits on shuffle connections:
> 1. limit the worker threads' number maybe percent  occupied  the same job's reduces ;
> 2. limit the worker threads' number serving the same map output simultaneously.
> Thoughts? 
> ps: we are using hadoop 0.19.

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

View raw message