On Thu, Oct 17, 2013 at 4:41 PM, Chandan Biswas <[email protected]>wrote:
> Yeah, I agree with Micah that it will not eliminate the reduce phase > entirely. But the dummy object of U suggested by Josh (or converting to U > type in map for every record) will not improve performance because same > amounts of records will be sorted and aggregated in the reduce phase. I don't think that's true-- the records of type U will be combined on the map-side, which would reduce the amount of data that is pushed over the network and improve performance. Can you give any additional details about what T and U are in this scenario? :) > But > my point is, can we improve it by applying a combiner where the combineFn > provides output as different type. If we have same type, we can use the > combiner to do some aggregation in map side which improves performance. > But, can we have some mechanism by which the same advantage can be achieved > when combineFn emits different type. I think, emitting same type by > CombineFn has restricted its use. Can we have new CombineFn that allows us > to output different type not only same type as input? > > > On Thu, Oct 17, 2013 at 5:05 PM, Josh Wills <[email protected]> wrote: > > > Yeah, my experience in these kinds of situations is that you need to come > > up with a "dummy" or singleton version of U for the case where there is > > only a single T and do that conversion on the map side of the job, before > > the combiner runs. I think Chao had an issue like this awhile ago, where > he > > had a PTable<String, Double> and wanted to write a combiner that would > > return a PTable<String, Collection<Double>>. The solution was to convert > > the map-side object to a PTable<String, Collection<Double>>, where the > > value on the map-side was a singleton list containing just that double > > value. Does that sort of trick work here? > > > > > > On Thu, Oct 17, 2013 at 2:57 PM, Micah Whitacre <[email protected]> > wrote: > > > > > Ok so the feature you are trying to achieve is the proactive > combination > > of > > > data before performing the GBK like the javadoc describes. Essentially > > in > > > that situation the CombineFn is being used as a Combiner[1] to combine > > the > > > data local to that mapper before doing the GBK and then further > combining > > > the data in the reduce operation. It will not necessarily eliminate > the > > > need for all processing in the reduce. > > > > > > If you want to use this functionality you will need to do the > following: > > > > > > PTable<S, T> map to PTable<S, U> > > > PTable<S, U> gbk to PGT<S, U> > > > PGT<S, U> combine PTable<S, U> > > > > > > This will take advantage of any optimization provided by the CombineFn. > > > > > > [1] - http://wiki.apache.org/hadoop/HadoopMapReduce > > > > > > > > > > > > On Thu, Oct 17, 2013 at 4:30 PM, Chandan Biswas <[email protected] > > > >wrote: > > > > > > > Hello Micah, > > > > Yes we are using MapFn now. That aggregation and computation is being > > > done > > > > in reduce phase. As CombineFn after GBK runs into map side, then > those > > > most > > > > computations can be done in map side which are now running in reduce > > > phase. > > > > Some smaller aggregations and computations can be done on reduce > phase. > > > > My point was to do some aggregation (and create a new object) in map > > > phase > > > > instead of in reduce phase. > > > > > > > > Thanks, > > > > Chandan > > > > > > > > > > > > On Thu, Oct 17, 2013 at 3:48 PM, Micah Whitacre <[email protected]> > > > wrote: > > > > > > > > > Chandan, > > > > > I think what you are wanting will just be a simple MapFn instead > > of > > > a > > > > > CombineFn. The doc of the CombineFn[1] sounds like what you want > > with > > > > the > > > > > statement "A special > > > > > DoFn< > > > http://crunch.apache.org/apidocs/0.7.0/org/apache/crunch/DoFn.html> > > > > > implementation > > > > > that converts an > > > > > Iterable< > > > > > > > > > > > > > > > http://download.oracle.com/javase/6/docs/api/java/lang/Iterable.html?is-external=true > > > > > > > > > > > of > > > > > values into a single value" but it is expecting the value to be of > > the > > > > same > > > > > time. Since you are wanting to combine the values into a different > > > form > > > > it > > > > > should be fairly trivial to write a MapFn that converts the > > Iterable<T> > > > > -> > > > > > U. > > > > > > > > > > [1] - > > > > > > > > > http://crunch.apache.org/apidocs/0.7.0/org/apache/crunch/CombineFn.html > > > > > > > > > > > > > > > On Thu, Oct 17, 2013 at 3:30 PM, Chandan Biswas < > > [email protected] > > > > > >wrote: > > > > > > > > > > > I was trying to refactoring some stuffs and trying to use > > combineFn. > > > > > > But when I went into deeper, found that I can't do it as Crunch > > > doesn't > > > > > > allow it the functionality I needed. For example, I have a > > > > > > PGroupedTable<S,T>. I wanted to apply CombineFn<S,T> on it and > > wanted > > > > to > > > > > > get PCollection<S,U> instead of T. Right now, CombineFn allows > only > > > > same > > > > > > type as return value. The use case of this need is that there > will > > be > > > > > some > > > > > > time saving in sorting. It's natural that when aggregating some > > > objects > > > > > at > > > > > > map side can create a new different type object. > > > > > > > > > > > > Any thought on it? Am I missing any thing? If this can be written > > in > > > > > > different way using existing way please let me know. > > > > > > > > > > > > Thanks > > > > > > Chandan > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > Director of Data Science > > Cloudera <http://www.cloudera.com> > > Twitter: @josh_wills <http://twitter.com/josh_wills> > > > -- Director of Data Science Cloudera <http://www.cloudera.com> Twitter: @josh_wills <http://twitter.com/josh_wills>
