One of the most powerful capabilities of both KSQL and the Kafka Streams library is that they allow us to easily express multiple “types” of join over continuous streams of data, and then have those joins be executed in distributed fashion by a self-organizing group of machines—but how many of us really understand the intrinsic qualities of a LEFT OUTER STREAM-STREAM JOIN, SPAN(5 MINUTES, 2 MINUTES)? And what happens when that data can arrive late or out of order? In this talk, we will explore the available streaming join options, covering common uses and examples for each, how to decide between them and illustrations of what’s really happening under the covers in the face of real-world data.
