Kafka Streams

Introduction

What is Kafka Streams? Kafka Streams is a Java library for building stateful stream processors directly on Kafka topics.

Understanding the topic

What happens — Kafka Streams:

• Build StreamsBuilder topology.
• Read from input topics.
• Transform: filter, map, join, aggregate.
• Write results to output topics.

Visual explanation

Pipeline view:

Input topic
  ↓
filter/map/join/window
  ↓
state store + changelog
  ↓
output topic

Step-by-step explanation

1. Define topology — builder.stream(), table(), join().
2. Process — Stateful/stateless ops.
3. Write output — to() sink topic.
4. Start — KafkaStreams.start().

Informative example

Example:

StreamsBuilder builder = new StreamsBuilder();
KStream<String, Order> orders = builder.stream("orders");
orders.filter((id, order) -> order.total() > 1000)
      .to("large-orders");

KafkaStreams streams = new KafkaStreams(builder.build(), props);
streams.start();

Execution workflow

Best practices

• Choose keys before joins and aggregations.
• Name internal topics and state stores clearly.
• Test topology with realistic ordering and late events.
• Monitor processing latency, commit rate, and restore time.

Common mistakes

• Unexpected repartition topics from wrong key choices.
• Ignoring late-arriving events in windows.
• Underestimating state-store disk and restore time.

Summary

Kafka Streams — Design topology around keys, state stores, window boundaries, changelog topics, and exactly-once needs.