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From Josh Wills <jwi...@cloudera.com>
Subject Re: Concerning the use of the Iterable parameter to CombineFn
Date Sat, 06 Apr 2013 18:28:49 GMT
We could also try caching/spilling the contents of the Iterable so that it
could actually be used more than once. I'm wondering if we could detect
that multiple clients were calling the same groupByKey() output and
automatically swap out the Iterable for one that cached the results.


On Fri, Apr 5, 2013 at 12:40 PM, Gabriel Reid <gabriel.reid@gmail.com>wrote:

> Hi Chad,
>
> Good point -- I know that this has tripped people up in the past. I think
> that definitely documenting this and possibly enforcing it sounds like a
> good idea -- I've logged a ticket in JIRA (with the content of your mail),
> see https://issues.apache.org/jira/browse/CRUNCH-192
>
> - Gabriel
>
>
> On 05 Apr 2013, at 21:30, Chad Urso McDaniel <chadum@gmail.com> wrote:
>
> > BLUF: The Iterable parameter to CombineFn.process implies you can
> iterate multiple times when you cannot and this leads to surprising
> behavior.
> >
> > As many of you probably know, the signature of CombineFn.process is
> > ---
> > process(Pair<K, Iterable<V>> input, Emitter<Pair<K, V>>
emitter)
> > ---
> >
> > The corresponding Hadoop Reducer signature is
> > ---
> > reduce(K2 key, Iterator<V2> values, OutputCollector<K3,V3> output,
> Reporter reporter)
> > ---
> >
> > I assume the Crunch use of Iterable is for convenient use in "for" loops.
> >
> > Unfortunately, the behavior of this Iterable seems to return the same
> Iterator object each time Iterable.iterator() is called.
> >
> > This makes sense to me based on the underlying hadoop mapreduce, but
> violates what I think most expect from the Iterable interface.
> >
> > I understand that it's too late to change the interface, but could we at
> least have an javadoc or an exception thrown if the Iterable is used more
> than once?
>
>


-- 
Director of Data Science
Cloudera <http://www.cloudera.com>
Twitter: @josh_wills <http://twitter.com/josh_wills>

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