ok thanks! then by now i will use it until true outer join is ready
Il giorno 29/giu/2015, alle ore 18:22, Fabian Hueske <fhue...@gmail.com<mailto:fhue...@gmail.com>> ha scritto: Yes, 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. Best, Fabian 2015-06-29 18:05 GMT+02:00 Michele Bertoni <michele1.bert...@mail.polimi.it<mailto:michele1.bert...@mail.polimi.it>>: 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 <fhue...@gmail.com<mailto:fhue...@gmail.com>> ha scritto: If you just want to do the pairwise comparison try join(). Join is an inner join and will give you all pairs of elements with matching keys. For CoGroup, there is no other way than collecting one side in memory. Best, Fabian 2015-06-29 17:42 GMT+02:00 Matthias J. Sax <mj...@informatik.hu-berlin.de<mailto:mj...@informatik.hu-berlin.de>>: 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 >
