Kafka Streams in Action, Second Edition

7 Streams and state

This chapter covers

• Adding stateful operations to Kafka Streams
• Using state stores in Kafka Streams
• Enriching event streams with joins
• Learning how timestamps drive Kafka Streams

In the last chapter, we dove headfirst into the Kafka Streams DSL and built a processing topology to handle streaming requirements from purchase activity. Although you created a nontrivial processing topology, it was one-dimensional in that all transformations and operations were stateless. You considered each transaction in isolation, without regard to other events coinciding or within certain time boundaries, either before or after the transaction. Also, you only dealt with individual streams, ignoring any possibility of gaining additional ...