Il giorno 29/giu/2015, alle ore 18:22, Fabian Hueske <[hidden email]> ha scritto:
Best, FabianYes, if you need outer join semantics you have to go with CoGroup.Some members of the Flink community are working on true outer joins for Flink, but I don't know what the progress is.
2015-06-29 18:05 GMT+02:00 Michele Bertoni <[hidden email]>:
thanks both for answering,that’s what i expected
I was using join at first but sadly i had to move from join to cogroup because I need outer join
the alternative to the cogroup is to “complete” the inner join extracting from the original dataset what did not matched in the cogroup by difference but I don’t think it is convenient
Il giorno 29/giu/2015, alle ore 17:58, Fabian Hueske <[hidden email]> ha scritto:
Best, FabianIf you just want to do the pairwise comparison try join().For CoGroup, there is no other way than collecting one side in memory.
Join is an inner join and will give you all pairs of elements with matching keys.
2015-06-29 17:42 GMT+02:00 Matthias J. Sax <[hidden email]>:
Why do you not use a join? CoGroup seems not to be the right operator.
-Matthias
On 06/29/2015 05:40 PM, Michele Bertoni wrote:
> Hi I have a question on cogroup
>
> when I cogroup two dataset is there a way to compare each element on the left with each element on the right (inside a group) without collecting one side?
>
> right now I am doing
>
> left.cogroup(right).where(0,1,2).equalTo(0,1,2){
> (leftIterator, rightIterator, out) => {
> val lSet = leftIterator.toSet // <———— toSet
> for(r <- rightIterator)
> for(l <- lSet)
> //do something
> }
> }
>
> I would like to avoid the toSet
>
>
> thanks for help
>
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