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MapReduce >> mail # user >> Some jobs seem to run forever

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Re: Some jobs seem to run forever
As I said in the original message bad partitioning was my original theory I
have had issues with it in the past and am careful with my partitioner. It
 was the first thing I looked for but I do not see any evidence that the
slower jobs have significantly more data than the faster ones and certainly
not enough to justify a radically different running time.
On Thu, Aug 29, 2013 at 9:29 AM, Charles Baker <[EMAIL PROTECTED]> wrote:

>  Hi Steve. Sounds like a classic case of uneven data distribution among
> the reducers. Most of your data is probably going to those 10 reducers that
> are taking many hours. You may want to adjust your key and/or partitioning
> strategy to better distribute the data amongst the reducers. If you’re
> using a hashing type of partitioning strategy, think about using a prime
> number of reducers. Primes are proven to have a more even distribution with
> a hash type strategy and this alone may get you pretty far. I have no idea
> what your workflow or cluster configuration is like but 300 reducers for
> 300 mappers doesn’t sound right. Try using a (prime) number of reducers
> that’s roughly  equal to 95% of the total reducer slots allocated on the
> cluster and go from there. Usually, the cluster should be configured for
> less reducers than mappers. If you have 12 cores per node (HT off), try 8
> mappers and 3 reducers per node.****
> ** **
> Good luck!****
> ** **
> Chuck****
> ** **
> ** **
> *From:* Steve Lewis [mailto:[EMAIL PROTECTED]]
> *Sent:* Wednesday, August 28, 2013 7:48 PM
> *To:* mapreduce-user
> *Subject:* Some jobs seem to run forever****
> ** **
> I have an issue that I am running a hadoop job on a 40 node cluster with
> about 300 Map tasks and about 300 reduce tasks. Most tasks complete within
> 20 minutes but a few, typically less than 10 run for many hours. ****
> If they complete I see nothing to suggest that the number of bytes read or
> written or the number of records read or written is significantly different
> from tasks that run much faster. I sometimes see multiple attempts -
> usually only two and the cluster is doing nothing else.****
> ** **
> Any suggested tuning?
> ****
> ** **
>  ****
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Steven M. Lewis PhD
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