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https://issues.apache.org/jira/browse/MAPREDUCE-2037?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12910397#action_12910397
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Dick King commented on MAPREDUCE-2037:
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Worker tasks seldom have multiple threads. Streaming and its friends spawn a
task, and of course users can write whatever code they want, but most tasks
burn their CPU time in their sole thread.
Of course, when we do have streaming we need to capture the info from the slave
task...
> Capturing interim progress times, CPU usage, and memory usage, when tasks
> reach certain progress thresholds
> -----------------------------------------------------------------------------------------------------------
>
> Key: MAPREDUCE-2037
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-2037
> Project: Hadoop Map/Reduce
> Issue Type: New Feature
> Reporter: Dick King
> Assignee: Dick King
> Fix For: 0.22.0
>
>
> We would like to capture the following information at certain progress
> thresholds as a task runs:
> * Time taken so far
> * CPU load [either at the time the data are taken, or exponentially
> smoothed]
> * Memory load [also either at the time the data are taken, or
> exponentially smoothed]
> This would be taken at intervals that depend on the task progress plateaus.
> For example, reducers have three progress ranges -- [0-1/3], (1/3-2/3], and
> (2/3-3/3] -- where fundamentally different activities happen. Mappers have
> different boundaries, I understand, that are not symmetrically placed. Data
> capture boundaries should coincide with activity boundaries. For the state
> information capture [CPU and memory] we should average over the covered
> interval.
> This data would flow in with the heartbeats. It would be placed in the job
> history as part of the task attempt completion event, so it could be
> processed by rumen or some similar tool and could drive a benchmark engine.
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