I am a user running beam+flink. Flink runner currently exposes only
the job level parallelism, not at an operator level. This is a really
nice feature if can be supported.
Flink's Datastream api provide that option though.
On 05/16/2018 10:24 PM, Chamikara Jayalath wrote:
Exact mechanism of controlling parallelism is runner specific. Looks
like Flink allows users to to specify the amount of parallelism (per
job) using following option.
I'm not sure if Flink allows more finer grained control.
On Wed, May 16, 2018 at 5:48 PM Harshvardhan Agrawal
How do we control parallelism of a particular step then? Is there
a recommended approach to solve this problem?
On Wed, May 16, 2018 at 20:45 Chamikara Jayalath
<chamik...@google.com <mailto:chamik...@google.com>> wrote:
I don't think this can be specified through Beam API but Flink
runner might have additional configurations that I'm not aware
of. Also, many runners fuse steps to improve the execution
performance. So simply specifying the parallelism of a single
step will not work.
On Tue, May 15, 2018 at 11:21 AM Harshvardhan Agrawal
I am currently in the process of developing a pipeline
using Apache Beam with Flink as an execution engine. As a
part of the process I read data from Kafka and perform a
bunch of transformations that involve joins, aggregations
as well as lookups to an external DB.
The idea is that we want to have higher parallelism with
Flink when we are performing the aggregations but
eventually coalesce the data and have lesser number of
processes writing to the DB so that the target DB can
handle it (for example say I want to have a parallelism of
40 for aggregations but only 10 when writing to target DB).
Is there any way we could do that in Beam?