Dear Fabian,
Can you have a look into this issue. What actions will be required to
resolve this one?
https://issues.apache.org/jira/browse/FLINK-1725
Regards,
Anis
On Wed, Feb 15, 2017 at 6:36 PM, Fabian Hueske wrote:
> Hi Anis,
>
> Flink uses regular hash-partitioning to shuffle records an
Hi Anis,
Flink uses regular hash-partitioning to shuffle records and does not have a
mechanism to counter data skew (other than scaling out).
Heterogeneous hardware can (to some extend) be addressed by adapting the
number of processing slots (or task managers) per machine, i.e., configure
fewer sl
Dear All,
I have few use cases for Flink streaming where the cluster consist of
heterogenous machines.
Additionally, there is skew present in both the input distribution (e.g.,
each tuple is drawn from a zipf distribution) and the service time (e.g.,
service time required for each tuple comes fro
