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From Márton Balassi <balassi.mar...@gmail.com>
Subject Re: Forward Partitioning & same Parallelism: 1:1 communication?
Date Wed, 12 Aug 2015 08:39:12 GMT
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 <Walteran@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
>
>
>
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