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From Till Rohrmann <trohrm...@apache.org>
Subject Re: One Kafka consumer operator subtask sending many more bytes than the others
Date Fri, 17 Feb 2017 09:43:26 GMT
Hi Bruno,

do you resume from the savepoints with a changed parallelism? Which version
of Flink are you running? Which Kafka version are you using (+ which Kafka
consumer version).

The partitions should be distributed among all 6 parallel subtasks which
means that every subtask should read from 100 partitions. You can check in
the logs how many partitions each consumer has been assigned by searching
for "Got x partitions from these topics" or "Consumer is going to read the
following topics". If you don't see 100 partitions assigned to each
consumer, then something is clearly going wrong.


On Thu, Feb 16, 2017 at 1:42 PM, Bruno Aranda <baranda@apache.org> wrote:

> Hi,
> I am trying to understand this issue in one of my Flink jobs with a Kafka
> source. At the moment I am using parallelism 6. The operator subtask just
> read the Kafka records (from a topic with 600 partitions), applies a keyBy
> and sends them to the next operator after the hashing.
> What I can see is that one of the subtasks is sending much more data than
> the others. The kafka partitions are well-balanced, as in they roughly
> contain the same number of records.
> I attach a screenshot. One subtask has sent 429 MB and the others around
> 4.88 KB.
> Could this be related that I originally created this stream with just
> parallelism one and I increased it later at some point. This is from a
> performance test suite where I am increasing parallelism between runs to
> check the performance, in a highly available cluster setup with zookeeper
> and checkpoints in S3.
> I am not cancelling the job with savepoints.
> Any ideas or things I can look for?
> Thanks!
> Bruno
> [image: Screen Shot 2017-02-16 at 12.36.29.png]

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