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Kafka Streams Store Window Timestamped

This module demonstrates the following:

  • The two strategies for creating timestamped Window stores and attaching them to the topology.
  • The usage of the Processor API, including process() and addStateStore().
  • Unit testing using Topology Test Driver.

In this module, records of type <String, KafkaPerson> are streamed from a topic named PERSON_TOPIC. The following tasks are performed:

  1. Create a first stream that pushes records to a timestamped Window store named PERSON_TIMESTAMPED_WINDOW_STORE.
  2. Create a second stream that pushes records to another timestamped Window store named PERSON_TIMESTAMPED_WINDOW_SUPPLIER_STORE.

topology.png

Requirements

To compile and run this demo, you will need the following:

  • Java 21
  • Maven
  • Docker

Running the Application

To run the application manually, please follow the steps below:

  • Start a Confluent Platform in a Docker environment.
  • Produce records of type <String, KafkaPerson> to a topic named PERSON_TOPIC. You can use the producer person to do this.
  • Start the Kafka Streams.

To run the application in Docker, please use the following command:

docker-compose up -d

This command will start the following services in Docker:

  • 1 Kafka broker KRaft
  • 1 Schema registry
  • 1 Control Center
  • 1 producer Person
  • 1 Kafka Streams Store Timestamped Window