Hi Marjtin,
Thank you very much that all clear. I will raise a Vote for this then. ;-)
BR
Bo Zhao
Martijn Visser 于2022年7月24日周日 01:42写道：
> Hi all,
>
> Thanks a lot for clarifying Yikun! I have no more concerns.
>
> Best regards,
>
> Martijn
>
> Op vr 22 jul. 2022 om 10:42 schreef bo zhaobo >:
Hi all,
Thanks a lot for clarifying Yikun! I have no more concerns.
Best regards,
Martijn
Op vr 22 jul. 2022 om 10:42 schreef bo zhaobo :
> Hi All,
>
> Thanks for all feedbacks from you. All of them are helpful and valuable for
> us.
>
> If there is no further comment towards FLIP-250 we intro
Hi All,
Thanks for all feedbacks from you. All of them are helpful and valuable for
us.
If there is no further comment towards FLIP-250 we introduced, we plan to
setup a VOTE thread next Monday.
Thank you all !!
BR
Bo Zhao
bo zhaobo 于2022年7月15日周五 10:02写道：
> Thanks all, @Yang Wang and @Yiku
Thanks all, @Yang Wang and @Yikun Jiang.
Hi Martijn,
We understand your concern. And do the above emails clear your doubts?
"
Thanks for the info! I think I see that you've already updated the FLIP to
reflect how customized schedulers are beneficial for both batch and
streaming jobs.
"
>>>
Yea
> And maybe we also could ping Yikun Jiang who has done similar things in
Spark.
Thanks for @wangyang ping. Yes, I was involved in Spark's customized
scheduler support work and as the main completer.
For customized scheduler support, I can share scheduler's requirement in
here:
1. Help scheduler
I think we could go over the customized scheduler plugin mechanism again
with YuniKorn to make sure that it is common enough.
But the implementation could be deferred.
And maybe we also could ping Yikun Jiang who has done similar things in
Spark.
For the e2e tests, I admit that they could be impr
Hi Bo,
Thanks for the info! I think I see that you've already updated the FLIP to
reflect how customized schedulers are beneficial for both batch and
streaming jobs.
The reason why I'm not too happy that we would only create a reference
implementation for Volcano is that we don't know if the gene
Hi Martijn,
Thank you for your comments. I will answer the questions one by one.
""
* Regarding the motivation, it mentions that the development trend is that
Flink supports both batch and stream processing. I think the vision and
trend is that we have unified batch- and stream processing. What I
Hi all,
Thanks for the FLIP. I have a couple of remarks/questions:
* Regarding the motivation, it mentions that the development trend is that
Flink supports both batch and stream processing. I think the vision and
trend is that we have unified batch- and stream processing. What I'm
missing is the
+1
On 2022/07/07 01:15:13 bo zhaobo wrote:
> Hi, all.
>
> I would like to raise a discussion in Flink dev ML about Support Customized
> Kubernetes Schedulers.
> Currentlly, Kubernetes becomes more and more polular for Flink Cluster
> deployment, and its ability is better, especially, it supports
Thanks zhaobo for the proposal.
We've met with a lot of big data users who are trying to migrate their
business to flink on kubernetes to improve job performance and cluster
utilization.
Unfortunately so far kubernetes lacks batch scheduling capabilities
compared to traditional batch systems like
+1 (non binding)
On Tue, Jul 12, 2022 at 6:50 AM Kelu Tao wrote:
> +1 for this proposal.
>
> Volcano has show its strength in some specified cases, such as ML. And its
> schedule ability will be enhancement for kubernetes default scheduler.
>
> Look forward to see the integration between Volcano
+1 for this proposal.
Volcano has show its strength in some specified cases, such as ML. And its
schedule ability will be enhancement for kubernetes default scheduler.
Look forward to see the integration between Volcano and Flink.
Thanks.
On 2022/07/08 00:25:45 bo zhaobo wrote:
> Thanks Yang
Thanks Yang Wang.
--- >>
A: Yeah, the said separated jar pkg won't be loaded by default. But when
users copy the jar pkg from $FLINK_HOME/opt/flink-kubernetes-*.jar to
plugins directory,
then the customized scheduler will be load and the functionality will
be enabled. That would be helpful t
Thanks zhaobo for starting the discussion and preparing the FLIP.
The customized Kubernetes Schedulers support will be very helpful for the
users who still hesitates to migrate the Flink workloads from YARN to
Kubernetes.
Now leveraging the ability of customized K8s scheduler, many advanced
schedu
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