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From "Gianmarco De Francisci Morales (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAPREDUCE-2187) map tasks timeout during sorting
Date Tue, 16 Nov 2010 13:42:16 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-2187?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12932462#action_12932462

Gianmarco De Francisci Morales commented on MAPREDUCE-2187:

I forgot I actually do have a combiner.
In the combiner, I call reporter.progress() every 1000 values.

The numbers are a bit high for the number of mappers/reducers I am using, but it was an exploratory

Map input records 	454,219
Map output records 	29,528,547,433
Map output bytes 	        503,179,031,513
Combine output records 	map=56,287,259,615 	red=13,553,888,779
Reduce input records 	 	15,567,573,707
Reduce output records 	2,509,983
Reduce  shuffle bytes 	 	337,876,374,027

The first time I tried with 400 mappers and 100 reducers, and I had the timeouts.
The job manages to end with 2000 mappers and 200 reducers.
I tried with a larger input and I had the same timeouts.

The size of the record shouldn't be that large.
The key is always an int pair.
The value is either an int-float pair (most of them, 29,528,011,793) or an array of long-double
pairs (535,640 records, for a total size of 649,693,592 bytes). I am using MultipleInputs
and GenericWritable to shuffle them together, can this be the culprit?

> map tasks timeout during sorting
> --------------------------------
>                 Key: MAPREDUCE-2187
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-2187
>             Project: Hadoop Map/Reduce
>          Issue Type: Bug
>    Affects Versions: 0.20.2
>            Reporter: Gianmarco De Francisci Morales
> During the execution of a large job, the map tasks timeout:
> {code}
> INFO mapred.JobClient: Task Id : attempt_201010290414_60974_m_000057_1, Status : FAILED
> Task attempt_201010290414_60974_m_000057_1 failed to report status for 609 seconds. Killing!
> {code}
> The bug is in the fact that the mapper has already finished, and, according to the logs,
the timeout occurs during the merge sort phase.
> The intermediate data generated by the map task is quite large. So I think this is the
> The logs show that the merge-sort was running for 10 minutes when the task was killed.
> I think the mapred.Merger should call Reporter.progress() somewhere.

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