anding is that this should not impact other flink jobs. Is that
>> correct?
>>
>>
>>
>> Thanks.
>>
>>
>>
>> Ajay
>>
>>
>>
>> *From: *Andrey Zagrebin
>> *Date: *Thursday, February 14, 2019 at 5:09 AM
>> *To: *Rong Rong
derstanding is that this should not impact other flink jobs. Is that
> correct?
>
>
>
> Thanks.
>
>
>
> Ajay
>
>
>
> *From: *Andrey Zagrebin
> *Date: *Thursday, February 14, 2019 at 5:09 AM
> *To: *Rong Rong
> *Cc: *"Aggarwal, Ajay" , "
link.apache.org"
Subject: Re: Impact of occasional big pauses in stream processing
Hi Ajay,
Technically, it will immediately block the thread of MyKeyedProcessFunction
subtask scheduled to some slot and basically block processing of the key range
assigned to this subtask.
Practically, I agre
Hi Ajay,
Technically, it will immediately block the thread of MyKeyedProcessFunction
subtask scheduled to some slot and basically block processing of the key
range assigned to this subtask.
Practically, I agree with Rong's answer. Depending on the topology of your
inputStream, it can eventually bl
Hi Ajay,
Flink handles "backpressure" in a graceful way so that it doesn't get
affected when your processing pipeline is occasionally slowed down.
I think the following articles will help [1,2].
In your specific case: the "KeyBy" operation will re-hash data so they can
be reshuffled from all inpu
I was wondering what is the impact if one of the stream operator function
occasionally takes too long to process the event. Given the following simple
flink job
inputStream
.KeyBy (“tenantId”)
.process ( new MyKeyedProcessFunction())
, if occasionally MyKeyedProcessF
