Chapter 14. Kafka Streams and KSQL

When it comes to building event-driven services, the Kafka Streams API provides the most complete toolset for handling a distributed, asynchronous world. Kafka Streams is designed to perform streaming computations. We discussed a simple example of such a use case, where we processed app open/close events emitted from mobile phones in Chapter 2. We also touched on its stateful elements in Chapter 6. This led us to three types of services we can build: event-driven, streaming, and stateful streaming.

In this chapter we look more closely at this unique tool for stateful stream processing, along with its powerful declarative interface: KSQL.

A Simple Email Service Built with Kafka Streams and KSQL

Kafka Streams is the core API for stream processing on the JVM (Java, Scala, Clojure, etc.). It is based on a DSL (domain-specific language) that provides a declaratively styled interface where streams can be joined, filtered, grouped, or aggregated via the DSL itself. It also provides functionally styled mechanisms (map, flatMap, transform, peek, etc.) for adding bespoke processing of messages one at a time. Importantly, you can blend these two approaches together in the services you build, with the declarative interface providing a high-level abstraction for SQL-like operations and the more functional methods adding the freedom to branch out into any arbitrary code you may wish to write.

But what if you’re not running on the JVM? In this case you’d use ...

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