Windowing in a Kafka streams

published on 2023/02/09

If you’re creating an application with Kafka Streams or ksqlDB, and that application involves aggregations, it’s likely that you’ll use windowing.

Why is that?

Well, aggregations of data accumulate over time, and without a limit, these aggregations won’t stop accumulating. Enter windowing, which defines the amount of data that can accumulate.

Note that windowing takes four forms, depending on whether the window is defined by size and period, or whether the window is event-triggered.