Hi!
The "feedback loop" sounds like a solution, yes. Actually, that works well
with the CoMap / CoFlatMap - one input to the CoMap would be the original
value, the other input the feedback value.
https://ci.apache.org/projects/flink/flink-docs-master/apis/streaming/index.html#datastream-transform
Another approach I'm considering, which feels pretty kludgy, but I think
should be acceptable for my current use:
Only one stateful op, keyed on the same field, but with a flag field
indicating the actual operation to be performed. The results of this op
are output to a kafka (or whatever) queue,
Thanks for the quick response!
I've been wondering about Connected streams and CoFlatMap, but either I
don't see all the ways they can be used, or they don't solve my problem.
Do you know of any examples outside of the documentation? My searches for
"flink comap example" and similar haven't turne
Hi!
This is a tricky one. State access and changes are not shared across
operators in Flink.
We chose that design because it makes it possible to work on "local" state
in each operator
- state automatically shards with the computation
- no locking / concurrency implications
- asynchronous pe
I'm trying to do something that seems like it should be possible, but my
implementation doesn't behave as expected, and I'm not sure how else to
express it.
Let's say the stream is composed of tuples like this: (Alice, Bob, 1) and I
want to keyBy(1), flatMap with state associated with Alice, then
