Hi,
Is joining 2 streams based on Windowed<String> keys supposed to work?
I have 2 KTables:
- KTable<Windowed<String>, T> events: I process events and aggregate events
that have a common criteria using aggregateByKey and UnlimitedWindows as window
(for now)
- KTable<Windowed<String>, S> hourlyStats: I calculate some stats using
aggregateByKey for hourly windows TimeWindows.of(“window name”, hourly)
Since both use aggregateByKey() they are both KTables and both have
Windowed<String> keys.
I need to leftJoin the first one (events) with the second one (hourlyStats) BUT
I need to join event x which occurred at time t0 with hourlyStats of the t0
window. In other words I need to join using
JoinWindows.of("JoinWindow").within(60 * 60 * 1000). Since both are KTables
this is not possible. But if I turn them both into KStream's using toStream()
then I can use the leftJoin() variants which supports JoinWindows. They would
both be KStream<Windowed<String>, ...>.
The problem is the join doesn’t really happen. No hourlyStats is actually found
for any row of events. The TimestampExtractor for both is correct.
So, Is joining 2 streams based on Windowed<String> keys supposed to work? If
not then how can I accomplish the above task?
Thanks,
Ara.
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