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 <twal...@apache.org> 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 DataStream. > > > > On Thu, Feb 11, 2021 at 9:11 AM Timo Walther <twal...@apache.org > > <mailto:twal...@apache.org>> 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.createTemporaryView("a", env.fromValues(1, 2, 3)); > > env.createTemporaryView("b", env.fromValues(4, 5, 6)); > > env.createTemporaryView("c", env.fromValues(7, 8, 9)); > > > > System.out.println(env.sqlQuery("SELECT * FROM c, b, a").explain()); > > > > So you can reorder the tables in the query if that improves > > performance. > > For interval joins, we currently don't provide additional algorithms > or > > options. > > > > Regards, > > Timo > > > > On 11.02.21 05:04, Dan Hill wrote: > > > 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? > > > >
