> > This is something that we need to solve a bit differently. > Maybe by adding optional null-valued field support to Tuple. >
+1 That was just a proof of concept. I agree, for a proper implementation, one would need to differentiate between a regular element and a NULL element. On Thu, Apr 16, 2015 at 3:23 PM, Fabian Hueske <fhue...@gmail.com> wrote: > That solution works if you can define a NULL_ELEMENT but not if you want > to use the full value range of Integer. > > This is something that we need to solve a bit differently. > Maybe by adding optional null-valued field support to Tuple. > > > 2015-04-15 5:59 GMT-05:00 Maximilian Michels <m...@apache.org>: > > Hi Flavio, >> >> Here's an simple example of a Left Outer Join: >> https://gist.github.com/mxm/c2e9c459a9d82c18d789 >> >> As Stephan pointed out, this can be very easily modified to construct a >> Right Outer Join (just exchange leftElements and rightElements in the two >> loops). >> >> Here's an excerpt with the most important part, the coGroup function: >> >> public static class LeftOuterJoin implements CoGroupFunction<Tuple2<Integer, >> String>, Tuple2<Integer, String>, Tuple2<Integer, Integer>> { >> >> @Override >> public void coGroup(Iterable<Tuple2<Integer, String>> leftElements, >> Iterable<Tuple2<Integer, String>> rightElements, >> Collector<Tuple2<Integer, Integer>> out) throws >> Exception { >> >> final int NULL_ELEMENT = -1; >> >> for (Tuple2<Integer, String> leftElem : leftElements) { >> boolean hadElements = false; >> for (Tuple2<Integer, String> rightElem : rightElements) { >> out.collect(new Tuple2<Integer, Integer>(leftElem.f0, >> rightElem.f0)); >> hadElements = true; >> } >> if (!hadElements) { >> out.collect(new Tuple2<Integer, Integer>(leftElem.f0, >> NULL_ELEMENT)); >> } >> } >> >> } >> } >> >> >> >> On Wed, Apr 15, 2015 at 11:01 AM, Stephan Ewen <se...@apache.org> wrote: >> >>> I think this may be a great example to add as a utility function. >>> >>> Or actually add as an function to the DataSet, internally realized as a >>> special case of coGroup. >>> >>> We do not have a ready example of that, but it should be straightforward >>> to realize. Similar as for the join, coGroup on the join keys. Inside the >>> coGroup function, emit the combination of all values from the two >>> iterators. If one of them is empty (the one that is not outer) then emit >>> all values from the outer side. >>> >>> Greetings, >>> Stephan >>> >>> >>> On Wed, Apr 15, 2015 at 10:36 AM, Flavio Pompermaier < >>> pomperma...@okkam.it> wrote: >>> >>>> Do you have an already working example of it? :) >>>> >>>> >>>> On Wed, Apr 15, 2015 at 10:32 AM, Ufuk Celebi <u...@apache.org> wrote: >>>> >>>>> >>>>> On 15 Apr 2015, at 10:30, Flavio Pompermaier <pomperma...@okkam.it> >>>>> wrote: >>>>> >>>>> > >>>>> > Hi to all, >>>>> > I have to join two datasets but I'd like to keep all data in the >>>>> left also if there' no right dataset. >>>>> > How can you achieve that in Flink? maybe I should use coGroup? >>>>> >>>>> Yes, currently you have to implement this manually with a coGroup >>>> >>>> >>>> >>> >> >
