I agree with Max.
Within the same Flink release you can perform savepoints and sometimes
also change parts of the query. But the latter depends on a case-by-case
basis and needs to be tested.
Regards,
Timo
On 30.01.21 11:43, Maximilian Michels wrote:
It is true that there are no strict upgr
It is true that there are no strict upgrade guarantees.
However, looking at the code, it appears RowSerializer supports adding
new fields to Row - as long as no fields are modified or deleted.
Haven't tried this out but it looks like the code would only restore
existing fields and incorporate
I went through a few of the recent Flink Forward videos and didn't see
solutions to this problem. It sounds like some companies have solutions
but they didn't talk about them in enough detail to do something similar.
On Thu, Jan 28, 2021 at 11:45 PM Dan Hill wrote:
> Is this savepoint recovery
Is this savepoint recovery issue also true with the Flink Table API? I'd
assume so. Just doublechecking.
On Mon, Jan 18, 2021 at 1:58 AM Timo Walther wrote:
> I would check the past Flink Forward conference talks and blog posts. A
> couple of companies have developed connectors or modified exi
I would check the past Flink Forward conference talks and blog posts. A
couple of companies have developed connectors or modified existing
connectors to make this work. Usually, based on event timestamps or some
external control stream (DataStream API around the actual SQL pipeline
for handling
Thanks Timo!
The reason makes sense.
Do any of the techniques make it easy to support exactly once?
I'm inferring what is meant by dry out. Are there any documented patterns
for it? E.g. sending data to new kafka topics between releases?
On Mon, Jan 18, 2021, 01:04 Timo Walther wrote:
>
Hi Dan,
currently, we cannot provide any savepoint guarantees between releases.
Because of the nature of SQL that abstracts away runtime operators, it
might be that a future execution plan will look completely different and
thus we cannot map state anymore. This is not avoidable because the
o
How well does Flink SQL work with checkpoints and savepoints? I tried to
find documentation for it in v1.11 but couldn't find it.
E.g. what happens if the Flink SQL is modified between releases? New
columns? Change columns? Adding joins?
