Stateless Processing Introduction
Explore how to design and implement stateless Kafka Streams topologies. This lesson introduces essential stateless operators such as filter, map, flatMap, split, and merge, guiding you through a practical project analyzing music streaming data to understand user emotions based on track metadata and lyrics.
We'll cover the following...
In this chapter, we’ll learn how to choose and use stateless operators. We will do so by designing, building, and running a complete end-to-end Kafka Streams stateless topology. To refresh our memory, when we talk about stateless operators, we refer to stream processors, which do not require knowledge of past records, i.e., each record is processed independently of previous records. In particular, we will be using the following Kafka Stream’s high-level domain-specific language (DSL) stateless operators:
filter: This is an operator used to select which records should be further processed.map: ...