Hi Alexandru, you can use the `modify` command `bin/flink modify <JOB_ID> --parallelism <PARALLELISM>` to modify the parallelism of a job. At the moment, it is implemented as first taking a savepoint, stopping the job and then redeploying the job with the changed parallelism and resuming from the savepoint.
Cheers, Till On Mon, Jan 14, 2019 at 4:21 PM Dawid Wysakowicz <dwysakow...@apache.org> wrote: > Hi Alexandru > > As for 2, generally speaking the number of required slots depends on > number of slot sharing groups. By default all operators belong to the > default slot sharing group, that means a job requires as many slots as > maximal parallelism in the job. More on the distributed runtime you can > read here[1] > > As for 1 I cc'ed Gary and Till who might better answer your question. > > [1] > https://ci.apache.org/projects/flink/flink-docs-release-1.7/concepts/runtime.html#task-slots-and-resources > > Best, > > Dawid > On 14/01/2019 15:26, Alexandru Gutan wrote: > > Hi everyone! > > 1. Is there a way to increase the parallelism (e.g. through REST) of some > operators in a job without re-deploying the job? I found this > <https://stackoverflow.com/questions/50719147/apache-flink-guideliness-for-setting-parallelism> > answer which mentions scaling at runtime on Yarn/Mesos. Is it possible? > How? Support for Kubernetes? > 2. What happens when the number of parallel operator instances exceeds the > number of task slots? For example: a job with a source (parallelism 3), a > map (parallelism 8), a sink (parallelism 3), total of *14* operator > instances and a setup with *8* task slots. Will the operators get > chained? What if I disable operator chaining? > > Thank you! > >
