Hi Jonas, The good news is that your job is completely parallelizable. So if you are running it on a cluster, you can scale it at least to the number of Kafka partitions you have (actually even further, because the Kafka consumers are not the issue).
I don't think that the scala (=akka) worker threads are really the thing that slows everything done. These threads should usually idle. I just tried it with Visualvm (I don't own a Jprofiler license :) ) and you can nicely see what's eating up CPU resources in my job: http://i.imgur.com/nqXeHdi.png On Thu, Jan 26, 2017 at 1:23 PM, Jonas <jo...@huntun.de> wrote: > JProfiler > > > > -- > View this message in context: http://apache-flink-user- > mailing-list-archive.2336050.n4.nabble.com/Improving-Flink- > Performance-tp11248p11311.html > Sent from the Apache Flink User Mailing List archive. mailing list archive > at Nabble.com. >
