Hi everybody,
Shaoxuan, Timo, and I compiled a list of features from the replies to this
thread, features that didn't make it into 1.3, and some additional ones.
We also graded them by importance, tried to assess the effort, and added
links to JIRAs (some existed already others were created) and e
Hi Haohui,
thanks for your input!
Can you describe the semantics of the join you'd like to see in Flink 1.4?
I can think of three types of joins that match your description:
1) `table` is an external table stored in an external database (redis,
cassandra, MySQL, etc) and we join with the current
Hi,
We are interested in building the simplest case of stream-table joins --
essentially calling stream.map(x => (x, table.get(x)). It solves the use
cases of augmenting the streams with the information of the database. The
operation itself can be batched for better performance.
We are happy to c
Hi Fabian,
Thanks for bring up this discuss.
In order to enrich Flink's built-in scalar function, friendly user
experience, I recommend adding as much scalar functions as possible in
version 1.4 release. I have filed the JIRAs(
https://issues.apache.org/jira/browse/FLINK-6810), and try my best to w
Thanks for your response Shaoxuan,
My "Table-table join with retraction" is probably the same as your
"unbounded stream-stream join with retraction".
Basically, a join between two dynamic tables with unique keys (either
because of an upsert stream->table conversion or an unbounded aggregation).
B
Nice timing, Fabian!
Your checklist aligns our plans very well. Here are the things we are
working on & planning to contribute to release 1.4:
1. DDL (with property waterMark config for source-table, and emit config on
result-table)
2. unbounded stream-stream joins (with retraction supported)
3. b
