You cannot add a `Processor`. You can only use `aggregate() / reduce() /
count()` (which of course will add a pre-defined processor).
`groupByKey()` is really just a "meta operation" that checks if the key
was changes upstream, and to insert a repartition/shuffle step if necessary.
Thus, if you don't change the upstream key, you can just add a processor
to `someStream` (groupByKey() would be a no-op anyway).
If you did change the key upstream, you can do
`someStream.repartition().transform()` to repartition explicitly.
HTH.
On 1/13/24 3:14 AM, Igor Maznitsa wrote:
Thanks a lot for explanation but could you provide a bit more details
about KGroupedStream? It is just interface and not extends KStream so
how I can add processor in the case below?
/
KStream someStream = ..../
/ someStream /
/ .groupByKey()
/ */how to add processor for resulted grouped stream here ???/*
On 2024-Jan-13 01:22, Matthias J. Sax wrote:
`KGroupedStream` is just an "intermediate representation" to get a
better flow in the DSL. It's not a "top level" abstraction like
KStream/KTable.
For `KTable` there is `transformValue()` -- there is no `transform()`
because keying must be preserved -- if you want to change the keying
you need to use `KTable#groupBy()` (data needs to be repartitioned if
you change the key).
HTH.
-Matthias
On 1/12/24 11:47 AM, Igor Maznitsa wrote:
Hello
Is there any way in Kafka Streams API to define processors for KTable
and KGroupedStream like KStream#transform? How to provide a custom
processor for KTable or KGroupedStream which could for instance
provide way to not downstream selected events?
