Flink SQL is missing a reliable, commonly-used way of evolving a job (e.g.
savepointing and checkpointing).
The other concepts I heard about are not shared publicly enough to rely on
(e.g. roll off). I wasn't able to find anything useful on this.
On Fri, Feb 12, 2021, 02:05 Timo Walther wrote:
Hi Dan,
thanks for letting us know. Could you give us some feedback what is
missing in SQL for this use case? Are you looking for some broadcast
joining or which kind of algorithm would help you?
Regards,
Timo
On 11.02.21 20:32, Dan Hill wrote:
Hi Timo! I'm moving away from SQL to DataStre
Hi Timo! I'm moving away from SQL to DataStream.
On Thu, Feb 11, 2021 at 9:11 AM Timo Walther wrote:
> Hi Dan,
>
> the order of all joins depends on the order in the SQL query by default.
>
> You can also check the following example (not interval joins though) and
> swap e.g. b and c:
>
> env.c
Hi Dan,
the order of all joins depends on the order in the SQL query by default.
You can also check the following example (not interval joins though) and
swap e.g. b and c:
env.createTemporaryView("a", env.fromValues(1, 2, 3));
env.createTemporaryView("b", env.fromValues(4, 5, 6));
env.create
Hi! I was curious if there are docs on how to optimize Flink joins. I
looked around and on the Flink docs and didn't see much. I see a little on
the Configuration page.
E.g. one of my jobs has an interval join. Does left vs right matter for
interval join?
