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https://issues.apache.org/jira/browse/MAPREDUCE-3403?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Eric Payne updated MAPREDUCE-3403:
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Summary: Speculative Execution: Put to sleep a reducer when queue is full
and a mapper needs to speculate (was: Speculative Execution: Put to sleep a
reducer when queue is full and a mapper )
> Speculative Execution: Put to sleep a reducer when queue is full and a mapper
> needs to speculate
> ------------------------------------------------------------------------------------------------
>
> Key: MAPREDUCE-3403
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-3403
> Project: Hadoop Map/Reduce
> Issue Type: New Feature
> Components: job submission
> Affects Versions: 0.23.0
> Environment: Hadoop version is: Hadoop 0.23.0.1110031628
> 10 node test cluster
> Reporter: patrick white
>
> When forcing multiple reduce tasks to be launched by applying the
> setNumReduceTasks() method on a Job object, and
> running on input data which has one significantly longer map (and
> consequently reduce) task;
> - a speculative reduce task was not launched, even with a longer running
> reducer only 4 reduce tasks were launched
> - the spec launch of map tasks was inhibited by the setNumReduceTasks()
> method applied, so even with
> -Dmapreduce.job.maps.speculative.execution=true we only had 4 map tasks
> launched. The exact same code with the
> setNumReduceTasks() method taken out, and on the same input data set,
> consistently launched 5 mappers as expected.
> Testing info:
> 3. modified WordCount to force 4 reducers being launched, by adding:
> job.setNumReduceTasks(4); // hardwire 4 reducers for now
> System.out.println("\nTESTDEBUG: using 4 reduce tasks for now\n\n");
> to the Job object. This causes 4 reduce tasks to be launched, oddly though it
> inhibits the map task from speculative
> launch. So the same job code, without the setNumReduceTasks() method, will
> launch 5 mappers as described in case #2.
> When this method is added, that same job will only launch 4 mappers, as well
> as 4 reducers, otherwise the job
> successfully completes.
> output snippet with setNumReduceTasks():
> org.apache.hadoop.mapreduce.JobCounter
> TOTAL_LAUNCHED_MAPS=4
> TOTAL_LAUNCHED_REDUCES=4
> RACK_LOCAL_MAPS=4
> SLOTS_MILLIS_MAPS=190787
> SLOTS_MILLIS_REDUCES=572554
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