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https://issues.apache.org/jira/browse/MAPREDUCE-467?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12726350#action_12726350
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Iyappan Srinivasan commented on MAPREDUCE-467:
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Tested these scenarios and found them to pass:
a) Start a randomwriter job and check if all windows appear properly in the
nodes section.
Total Tasks last hour and succeeded task last hour
Total Tasks last day and succeeded task last day
Total Tasks since start and succeeded task since start
b) Check after a job is run whether all tasks are captured properly in these
windows. The number of tasks should be same. All windows needs to be populated.
c) All windows needs to be refreshed after the time window given.
d) Run simultaneous jobs and check if all windows are populated with proper
values of tasks.
e) Kill some tasks attempts and see if those numbers match.
f) Run different kinds of jobs and see if tasks tracker is still able to get
the number of tasks right.
g) Kill a job in the middle and see how tasks tracker numbers are populated in
these windows.
h) Check even after subsequent execution fo jobs and subsequent passing of
time, still the tasks are able to be captured without any error.
i) Restart job tracker and see if the tasks are captured properly.
> Collect information about number of tasks succeeded / total per time unit for
> a tasktracker.
> ---------------------------------------------------------------------------------------------
>
> Key: MAPREDUCE-467
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-467
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Reporter: Hemanth Yamijala
> Assignee: Sharad Agarwal
> Attachments: 467_v4.patch, 467_v5.patch, 467_v6.patch, 5931_v1.patch,
> 5931_v2.patch, 5931_v3.patch
>
>
> Collecting information of number of tasks succeeded / total per tasktracker
> and being able to see these counts per hour, day and since start time will
> help reason about things like the blacklisting strategy.
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