ore. In FLIP-6 it can be up to the number of slots more key groups
> on one of the TaskManagers. In order to mitigate this problem I would
> recommend to set the maximum parallelism (== number of key groups) to a
> multiple of your parallelism.
>
> [1] https://issues.apache.org/jira/br
<https://ci.apache.org/projects/flink/flink-docs-release-1.5/ops/config.html#core>
> [2] "taskmanager.network.credit-model:false”
>
> Could you try disabling them out?
>
> Piotrek
>
> > On 28 Oct 2019, at 14:10, Jakub Danilewicz
> > wrote:
> >
> > Thanks for y
Thanks for your replies.
We use Flink from within a standalone Java 8 application (no Hadoop, no
clustering), so it's basically boils down to running a simple code like this:
import java.util.*;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.graph.*;
import
Hi,
I have recently tried to upgrade Flink from 1.2.0 to the newest version and
noticed that starting from the version 1.5 the performance is much worse
when processing fixed graphs in a standalone JVM environment (Java 8).
This affects all the use-cases when a Gelly graph (pre-built from a
