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From "Chris Schneider (JIRA)" <j...@apache.org>
Subject [jira] Created: (HADOOP-465) Jobtracker doesn't always spread reduce tasks evenly if (mapred.tasktracker.tasks.maximum > 1)
Date Sat, 19 Aug 2006 06:09:13 GMT
Jobtracker doesn't always spread reduce tasks evenly if (mapred.tasktracker.tasks.maximum >

                 Key: HADOOP-465
                 URL: http://issues.apache.org/jira/browse/HADOOP-465
             Project: Hadoop
          Issue Type: Bug
          Components: mapred
            Reporter: Chris Schneider
            Priority: Minor

I note that (at least for Nutch 0.8 Generator.Selector.reduce) if mapred.reduce.tasks is the
same as the number of tasktrackers, and mapred.tasktracker.tasks.maximum is left at the default
of 2, I typically have no reduce tasks running on a few of my tasktrackers, and two reduce
tasks running on the same number of other tasktrackers.

It seems like the jobtracker should assign reduce tasks to tasktrackers in a round robin fashion,
so that the distribution will be spread as evenly as possible. The current implementation
would seem to waste at least some time if one or more slave machines have to execute two reduce
tasks simultaneously while other tasktrackers sit idle, with the amount of wasted time depending
on how dependent the reduce tasks were on the slave machine's resources.

I first thought that perhaps the jobtracker was "overloading" the tasktrackers that had already
finished their map tasks (and avoiding those that were still mapping). However, as I understand
it, the reduce tasks are all launched at the beginning of the job so that they are all ready
and waiting for map output data when it first appears.

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