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From Arun C Murthy <...@hortonworks.com>
Subject Re: is there a way to just abandon a map task?
Date Mon, 21 Nov 2011 00:43:27 GMT
Mat,

 Take a look at mapred.max.(map|reduce).failures.percent.

 See: 
 http://hadoop.apache.org/common/docs/r0.20.205.0/api/org/apache/hadoop/mapred/JobConf.html#setMaxMapTaskFailuresPercent(int)

 http://hadoop.apache.org/common/docs/r0.20.205.0/api/org/apache/hadoop/mapred/JobConf.html#setMaxReduceTaskFailuresPercent(int)

hth,
Arun

On Nov 20, 2011, at 1:31 PM, Mat Kelcey wrote:

> Hi,
> 
> I have a largish job running that, due to the quirks of the third
> party input format I'm using, has 280,000 map tasks. ( I know this is
> far from ideal but it's it'll do for me )
> 
> I'm passing this data (the common crawl web crawl dataset) through a
> visible-text-from-html extraction library (boilerpipe) which is
> struggling with _1_ particular task. It's hits a sequence of records
> that are _insanely_ slow to parse for some reason. Rather than a few
> minutes per split it's took 7+ hrs before I started explicitly trying
> to fail the task (hadoop job -fail-task). Since I'm running with bad
> record skipping I was hoping I could issue -fail-task a few times and
> ride over the bad records but it looks like there's quite a few there.
> Since it's only 1 of the 280,000 I'm actually happy to just give up on
> the entire split.
> 
> Now if I was running a map only job I'd just kill the job since I'd
> have the output of the other 279,999. This job has a no-op reduce step
> though since I wanted to take the chance to compact the output into a
> much smaller number of sequence files ( I regret that decision now) As
> such I can't just kill the job since I'd lose the rest of the
> processed data (if I understand correctly?)
> 
> So does anyone know a way to just abandon the entire split?
> 
> Cheers,
> Mat


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