Hi Olivier,

Someone will correct me if I'm wrong, but I believe the max-parallelism
limitation, where you cannot scale up past the previously defined
max-parallelism, applies to all stateful jobs no matter which type of state
you are using.

If you haven't seen it already, I think the Production Readiness checklist
[1] offers a good explanation for this behavior/ best practices for setting
it.

Best,
Austin

[1]:
https://ci.apache.org/projects/flink/flink-docs-master/docs/ops/production_ready/#set-an-explicit-max-parallelism

On Tue, Apr 20, 2021 at 9:33 AM Olivier Nouguier <olivier.nougu...@teads.com>
wrote:

> Hi, thank you all for your reply, by limitation I meant the impossibility
> to resume a job when scaling up because of this max-parallelism.
> To be more precise, in our deployment, the operator (max) parallelism is
> computed from the number of available slots ( ~~ task-manager * core ),
> this approach is probably too naive, at least with keyed state.
>
>
>
> On Tue, Apr 20, 2021 at 10:46 AM Chesnay Schepler <ches...@apache.org>
> wrote:
>
>> @Olivier Could you clarify which limitation you are referring to?
>>
>> On 4/20/2021 5:23 AM, Guowei Ma wrote:
>>
>> Hi, Olivier
>> Yes. The introduction of this concept is to solve the problem of
>> rescaling the keystate.
>> Best,
>> Guowei
>>
>>
>> On Mon, Apr 19, 2021 at 8:56 PM Olivier Nouguier <
>> olivier.nougu...@teads.com> wrote:
>>
>>> Hi,
>>>   May I have the confirmation that the max-parallelism limitation only
>>> occurs when keyed states are used ?
>>>
>>>
>>> --
>>>
>>> Olivier Nouguier
>>>
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>
> --
>
> Olivier Nouguier
>
> SSE
>
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>
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