You are viewing a plain text version of this content. The canonical link for it is here.
Posted to mapreduce-dev@hadoop.apache.org by "Ramkumar Vadali (JIRA)" <ji...@apache.org> on 2010/05/12 00:51:41 UTC
[jira] Created: (MAPREDUCE-1783) Task Initialization should be
delayed till when a job can be run
Task Initialization should be delayed till when a job can be run
----------------------------------------------------------------
Key: MAPREDUCE-1783
URL: https://issues.apache.org/jira/browse/MAPREDUCE-1783
Project: Hadoop Map/Reduce
Issue Type: Improvement
Components: contrib/fair-share
Affects Versions: 0.20.1
Reporter: Ramkumar Vadali
The FairScheduler task scheduler uses PoolManager to impose limits on the number of jobs that can be running at a given time. However, jobs that are submitted are initiaiized immediately by EagerTaskInitializationListener by calling JobInProgress.initTasks. This causes the job split file to be read into memory. The split information is not needed until the number of running jobs is less than the maximum specified. If the amount of split information is large, this leads to unnecessary memory pressure on the Job Tracker.
To ease memory pressure, FairScheduler can use another implementation of JobInProgressListener that is aware of PoolManager limits and can delay task initialization until the number of running jobs is below the maximum.
--
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.