[infinispan-dev] MapReduce limitations and suggestions.

[Dan Berindei]

Hi Etienne

I was going to suggest using a combiner - the combiner would process the
mapper results from just one node, so you should need at most double the
memory on that node. I guess we could reduce the memory requirements even
more if the combiner could run concurrently with the mapper... Vladimir,
does it sound like a reasonable feature request?

I'm afraid in your situation using a cache store wouldn't help, as the
intermediate values for the same key are stored as a list in a single
entry. So if all cars are red, there would be just one intermediate key in
the intermediate cache, and there would be nothing to evict to the cache
store. Vladimir, do you think we could somehow "chunk" the intermediary
values into multiple entries grouped by the intermediary key, to support
this scenario?

For reference, though, a limited version of what you're asking for is
already available. You can change the configuration of the intermediary
cache by defining a "__tmpMapReduce" cache in your configuration. That
configuration will be used for all M/R tasks, whether they use the shared
intermediate cache or they create their own.

Cheers
Dan



On Mon, Feb 17, 2014 at 10:18 AM, Etienne Riviere
<etienne.riviere at unine.ch>wrote:

> Hi Radim,
>
> I might misunderstand your suggestion but many M/R jobs actually require
> to run the two phases one after the other, and henceforth to store the
> intermediate results somewhere. While some may slightly reduce intermediate
> memory usage by using a combiner function (e.g., the word-count example), I
> don't see how we can avoid intermediate storage altogether.
>
> Thanks,
> Etienne (leads project -- as Evangelos who initiated the thread)
>
> On 17 Feb 2014, at 08:48, Radim Vansa <rvansa at redhat.com> wrote:
>
> > I think that the intermediate cache is not required at all. The M/R
> > algorithm itself can (and should!) run with memory occupied by the
> > result of reduction. The current implementation with Map first and
> > Reduce after that will always have these problems, using a cache for
> > temporary caching the result is only a workaround.
> >
> > The only situation when temporary cache could be useful is when the
> > result grows linearly (or close to that or even more) with the amount of
> > reduced entries. This would be the case for groupBy producing Map<Color,
> > List<Entry>> from all entries in cache. Then the task does not scale and
> > should be redesigned anyway, but flushing the results into cache backed
> > by cache store could help.
> >
> > Radim
> >
> > On 02/14/2014 04:54 PM, Vladimir Blagojevic wrote:
> >> Tristan,
> >>
> >> Actually they are not addressed in this pull request but the feature
> >> where custom output cache is used instead of results being returned is
> >> next in the implementation pipeline.
> >>
> >> Evangelos, indeed, depending on a reducer function all intermediate
> >> KOut/VOut pairs might be moved to a single node. How would custom cache
> >> help in this case?
> >>
> >> Regards,
> >> Vladimir
> >>
> >>
> >> On 2/14/2014, 10:16 AM, Tristan Tarrant wrote:
> >>> Hi Evangelos,
> >>>
> >>> you might be interested in looking into a current pull request which
> >>> addresses some (all?) of these issues
> >>>
> >>> https://github.com/infinispan/infinispan/pull/2300
> >>>
> >>> Tristan
> >>>
> >>> On 14/02/2014 16:10, Evangelos Vazaios wrote:
> >>>> Hello everyone,
> >>>>
> >>>> I started using the MapReduce implementation of Infinispan and I came
> >>>> across some possible limitations. Thus,  I want to make some
> suggestions
> >>>> about the MapReduce (MR) implementation of Infinispan.
> >>>> Depending on the algorithm,  there might be some memory problems,
> >>>> especially for intermediate results.
> >>>> An example of such a case is  group by. Suppose that we have a cluster
> >>>> of 2 nodes with 2 GB  available. Let a distributed cache, where simple
> >>>> car objects (id,brand,colour) are stored and the total size of data is
> >>>> 3.5GB. If all objects have the same colour , then all 3.5 GB would go
> to
> >>>> only one reducer, as a result an OutOfMemoryException will be thrown.
> >>>>
> >>>> To overcome these limitations, I propose to add as parameter the name
> of
> >>>> the intermediate cache to be used. This will enable the creation of a
> >>>> custom configured cache that deals with the memory limitations.
> >>>>
> >>>> Another feature that I would like to have is to set the name of the
> >>>> output cache. The reasoning behind this is similar to the one
> mentioned
> >>>> above.
> >>>>
> >>>> I wait for your thoughts on these two suggestions.
> >>>>
> >>>> Regards,
> >>>> Evangelos
> >>>> _______________________________________________
> >>>> infinispan-dev mailing list
> >>>> infinispan-dev at lists.jboss.org
> >>>> https://lists.jboss.org/mailman/listinfo/infinispan-dev
> >>>>
> >>>>
> >>>
> >>>
> >>> _______________________________________________
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> >> _______________________________________________
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> >
> >
> > --
> > Radim Vansa <rvansa at redhat.com>
> > JBoss DataGrid QA
> >
> > _______________________________________________
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> > infinispan-dev at lists.jboss.org
> > https://lists.jboss.org/mailman/listinfo/infinispan-dev
>
>
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