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From "Min Zhou (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAPREDUCE-2425) Distributed simulator for stressing JobTracker and NameNode
Date Fri, 08 Apr 2011 04:43:05 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-2425?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13017273#comment-13017273

Min Zhou commented on MAPREDUCE-2425:


This simulator is developed  majorly for stressing JT and NN. It can also verify JT's runtime
behavior as mumak does. Actually, we use v0.19.1 where rumen and mumak havenot been introduced
at that time, so I developed this tool independent from them.  Now that I am planning to merge
my code into mumak. But before that, I must do 2 things list below 

1. Mumak uses a simulated JT for telling TT some informations of a task-attempt reproduced
by rumen through heartbeat. I perfer using the real JT when stressing it. 
2. I should uses new MR API before merging into mumak.

> Distributed simulator for stressing JobTracker and NameNode
> -----------------------------------------------------------
>                 Key: MAPREDUCE-2425
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-2425
>             Project: Hadoop Map/Reduce
>          Issue Type: New Feature
>          Components: benchmarks
>            Reporter: Min Zhou
>              Labels: benchmark, hadoop
>             Fix For: 0.22.0
>         Attachments: .jpg, screenshot-1.jpg
> Hadoop need a tool for stressing JobTracker and NameNode. Mumak introduced a simulated
JobTracker, whose behavior doesn't exactly like that of the real JobTracker. Even more, mumak
can't simulate a large cluster with quite a lot of jobs run on it. On the other hand, Gridmix
v3 need hundreds of physical nodes to replay job stories. 
> You can think this tool a complementation of mumak and gridmix v3. We successfully used
this tool to simulate a 12000 nodes cluster through 4 real machines. 
> I've talk to Hong Tang and Scott Chen offline, they suggested me contributing this tool
to the hadoop community.

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