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From "Dick King (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAPREDUCE-2037) Capturing interim progress times, CPU usage, and memory usage, when tasks reach certain progress thresholds
Date Thu, 16 Sep 2010 23:50:36 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-2037?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12910397#action_12910397
] 

Dick King commented on MAPREDUCE-2037:
--------------------------------------

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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