Example for a custom Kafka Streams processor with punctuations

This is the demo code for the article Kafka Streams - Working with Time (medium.com)

When we use time-based operations in a Kafka Streams application, then time is usually extracted from records in a stream. This event-time differs from processing-time (wallclock-time).

In this sample application we use a custom transformation to suppress event emission of windowed operations based on wallclock time, while still working with event-time in our windowing operation.

Sample Use Case

Our Spring Boot App has a producer bean which creates random page ratings (1-5) in a fixed interval. We aggregate these ratings per PageId in time windows. A custom processor is used to suppress updates as long as new ratings arrive for a time window.

Running the app

• Start docker compose with docker-compose up -d
• Test build with ./mvnw clean package
• Then start the app using the main function in PageRatingAplication.kt