For a KStream-to-KStream join, what are the output type, whether it's windowed, co-partitioning requirement, and the join type?

For a KStream-to-KStream join, what are the output type, whether it's windowed, co-partitioning requirement, and the join type?

• A. Output: KStream; Windowed; Yes; Key and Window Based
• B. Output: KTable; Non-windowed; Yes; Key or Foreign-key Based
• C. Output: KStream; Non-windowed; Yes; Key Based
• D. Output: KStream; Windowed; No; Key or Foreign-key Based

Answer: (C)

In a KStream-to-KStream join, the result is a KStream because you’re producing a new stream of joined records from two input streams. The operation is windowed: you must specify a time window (JoinWindows) that determines how far apart in time records from the two streams can be to be considered a match. This bound is essential to keep state manageable and to define deterministic join behavior. Co-partitioning is required because both input streams must have their records with the same join key routed to the same partition on every processor instance. If the streams aren’t partitioned on the same key, matching records may reside in different instances and the join won’t occur correctly. The join type here is based on the join key: you join records that share the same key, typically combining their values with a ValueJoiner. There isn’t a foreign-key concept in this join—you rely on the stream keys to perform the join. So the correct understanding is: Output is a KStream; the join is windowed; co-partitioning is required; and the join is keyed on the join key (Key Based).

In a KStream-to-KStream join, the result is a KStream because you’re producing a new stream of joined records from two input streams. The operation is windowed: you must specify a time window (JoinWindows) that determines how far apart in time records from the two streams can be to be considered a match. This bound is essential to keep state manageable and to define deterministic join behavior.

Co-partitioning is required because both input streams must have their records with the same join key routed to the same partition on every processor instance. If the streams aren’t partitioned on the same key, matching records may reside in different instances and the join won’t occur correctly.

The join type here is based on the join key: you join records that share the same key, typically combining their values with a ValueJoiner. There isn’t a foreign-key concept in this join—you rely on the stream keys to perform the join.

So the correct understanding is: Output is a KStream; the join is windowed; co-partitioning is required; and the join is keyed on the join key (Key Based).