Re: Forward Partitioning & same Parallelism: 1:1 communication?

Posted by Márton Balassi on
URL: http://deprecated-apache-flink-user-mailing-list-archive.369.s1.nabble.com/Forward-Partitioning-same-Parallelism-1-1-communication-tp2373p2374.html

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 <[hidden email]> 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



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