One of the option when reading from topics with a small number of partitions 
could be to do a Reshuffle right after read transform to parallelize better 
other pipeline steps.

We had a discussion in this Jira about that a while ago:
https://issues.apache.org/jira/browse/BEAM-8121 
<https://issues.apache.org/jira/browse/BEAM-8121>

> On 30 Apr 2020, at 03:56, Eleanore Jin <[email protected]> wrote:
> 
> Thanks all for the information! 
> 
> Eleanore 
> 
> On Wed, Apr 29, 2020 at 6:36 PM Ankur Goenka <[email protected] 
> <mailto:[email protected]>> wrote:
> Beam does support parallelism for the job which applies to all the transforms 
> in the job when executing on Flink using the "--parallelism" flag.
> 
> From the usecase you mentioned, Kafka read operations will be over 
> parallelised but it should be ok as they will only have a small amount of 
> memory impact in loading some state for kafka client etc.
> Also flink can run multiple operations for the same Job in a single task slot 
> so having higher parallelism for lightweight operations should not be a 
> problem.
> 
> On Wed, Apr 29, 2020 at 6:28 PM Luke Cwik <[email protected] 
> <mailto:[email protected]>> wrote:
> Beam doesn't expose such a thing directly but the FlinkRunner may be able to 
> take some pipeline options to configure this.
> 
> On Wed, Apr 29, 2020 at 5:51 PM Eleanore Jin <[email protected] 
> <mailto:[email protected]>> wrote:
> Hi Kyle, 
> 
> I am using Flink Runner (v1.8.2)
> 
> Thanks!
> Eleanore
> 
> On Wed, Apr 29, 2020 at 10:33 AM Kyle Weaver <[email protected] 
> <mailto:[email protected]>> wrote:
> Which runner are you using?
> 
> On Wed, Apr 29, 2020 at 1:32 PM Eleanore Jin <[email protected] 
> <mailto:[email protected]>> wrote:
> Hi all, 
> 
> I just wonder can Beam allow to set parallelism for each operator 
> (PTransform) separately? Flink provides such feature. 
> 
> The usecase I have is the source is kafka topics, which has less partitions, 
> while we have heavy PTransform and would like to scale it with more 
> parallelism. 
> 
> Thanks a lot!
> Eleanore

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