Dear Nica, Yes, forward partitioning means that if subsequent operators share parallelism then the output of an upstream operator is sent to exactly one downstream operator. This makes sense for operators working on individual records, e.g. a typical map-filter pair, because as a consequence Flink may be able to collocate these operator pairs on the same physical machine.
Best, Marton On Tue, Aug 11, 2015 at 11:41 PM, Nicaz <walte...@students.uni-marburg.de> wrote: > Hello, > > I have a question about forward partitioning in Flink. > > If Operator A and Operator B have the same parallelism set and forward > partitioning is used for events coming from instances of A and going to > instances of B: > > Will each instance of A send events to _exactly one_ instance of B? > > That is, will all events coming from a specific instance of A go to the > _same_ specific instance of B, and will _all_ instances of B be used? > Or are there any situations where an instance of A will distribute events > to > several different instances of B, or where two instances of A will send > events to the same instance of B (possibly leaving some other instance of B > unused)? > > I'd be very happy if someone were able to shed some light on this issue. > :-) > > Thanks in advance > Nica > > > > -- > View this message in context: > http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/Forward-Partitioning-same-Parallelism-1-1-communication-tp2373.html > Sent from the Apache Flink User Mailing List archive. mailing list archive > at Nabble.com. >
