Thanks both for your advice, I will give them a try!
From: Schwalbe Matthias
Sent: 10 October 2022 08:35
To: 仙路尽头谁为峰 ; Qing Lim
Cc: User
Subject: RE: Re:Question about Flink Broadcast State event ordering
Hi Qing again,
Another point to consider: broadcast streams are subject to watermarking
the
time 😊 )
Best regards
Thias
From: 仙路尽头谁为峰
Sent: Wednesday, October 5, 2022 10:13 AM
To: Qing Lim
Cc: User
Subject: [SPAM] 回复: Re:Question about Flink Broadcast State event ordering
⚠EXTERNAL MESSAGE – CAUTION: Think Before You Click ⚠
Hi Qing:
The key point is that the broadcast
Oh, thank you for your explanation!
From: 仙路尽头谁为峰
Sent: 05 October 2022 09:13
To: Qing Lim
Cc: User
Subject: 回复: Re:Question about Flink Broadcast State event ordering
Hi Qing:
The key point is that the broadcast side may have different partitions that
interleaves. If you can make sure
收件人: xljtswf2022
抄送: User
主题: RE: Re:Question about Flink Broadcast State event ordering
Hi, thanks for answering my question.
Is there anyway to make the order reflecting the upstream? I wish to broadcast
messages that has deletion semantic, so ordering matters here.
I guess worst case I can
: 05 October 2022 03:02
To: Qing Lim
Cc: User
Subject: Re:Question about Flink Broadcast State event ordering
Hi Qing:
> I think this is refering to the order between broadcasted element and non
> broadcasted element, right?
No, as broadcast and nonbroadcast stream are different streams
Hi Qing:
> I think this is refering to the order between broadcasted element and non
> broadcasted element, right?
No, as broadcast and nonbroadcast stream are different streams, they will
usually transfer with different tcp connection, we can not control the order of
elements in different con
Hi Flink user group,
I have a question around broadcast.
Reading the docs
https://nightlies.apache.org/flink/flink-docs-master/docs/dev/datastream/fault-tolerance/broadcast_state/#important-considerations,
it says the following:
> Order of events in Broadcast State may differ across tasks: Alt
Hi Christophe,
Flink exposes event-time and watermark not only in windows.
The easiest solution would be to use a ProcessFunction [1] which can access
the timestamp of a record.
I would apply a ProcessFunction on a keyed stream (keyBy(id) [2]) and store
the max timestamp per key in a ValueState [
Hi everyone,
Let's imagine I have a stream of events coming a bit like this:
{ id: "1", value: 1, timestamp: 1 }
{ id: "2", value: 2, timestamp: 1 }
{ id: "1", value: 4, timestamp: 3 }
{ id: "1", value: 5, timestamp: 2 }
{ id: "2", value: 5, timestamp: 3 }
...
As you can see with the non monoto
t through?
>
> More concretely, when the Kafka consumer persists an offset to Zookeeper
> based on receiving a checkpoint trigger, can I trust that all events from
> before that offset are not held in any windowing intermediate state?
>
> Thanks!
>
> Shikhar
>
>
&g
anks!
Shikhar
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