Is it true that the aggregation and reduction methods of KStream will emit a new output message for each incoming message?
I have an application that's copying a Postgres replication stream to a Kafka topic, and activity tends to be clustered, with many updates to a given primary key happening in quick succession. I'd like to smooth that out by buffering the messages in tumbling windows, allowing the updates to overwrite one another, and emitting output messages only at the end of the window. Does the Kafka Streams API provide any hooks that I could use to achieve this kind of windowed "buffering" or "deduplication" of a stream?
