kafka-streams-store-window-timestamped

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 use of the Processor API, including process() and addStateStore().
• Unit testing using Topology Test Driver.

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

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

Prerequisites

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

• Java 21
• Maven
• Docker

Running the Application

To run the application manually:

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

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

docker-compose up -d

This command will start the following services in Docker:

• 1 Kafka broker (KRaft mode)
• 1 Schema registry
• 1 Control Center
• 1 producer User
• 1 Kafka Streams Store Timestamped Window