Hi Li,
what you can do is to add the #queries when splitting:
user1 - [query1, query2, query3]
->
[user1, query1, 3] [user1, query2, 3] [user1, query2, 3]
->
Then while collecting the results, you just compare the current number of
records in the window and emit if it reaches the expected number.
Hi Li,
From my view I think it would not be eaily use a countWindow if you have
different number of records for each key (namely user in this case). I think
you may need to user the low level KeyedProcessFunction [1] to keep some state
by yourself. For example, each request might also
Can I get any suggestion? Thanks a lot.
- Li
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Hi Team,
I have a Flink application reading from Kafka. Each payload is a request
sent by a user containing a list of queries. What I would like to do is use
Flink to process the queries parallelly and aggregate results and send back
to the user.
For example, let's say we have two messages in
