Topics

Introduction

What is Topics? Topics are named streams of records.

Understanding the topic

What happens — Topics:

• Create a topic with a name and partition count.
• Producers publish to the topic.
• Records land in one partition each.
• Many consumer groups can read the same topic.

Visual explanation

Pipeline view:

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

Step-by-step explanation

1. Create topic — Define partitions, RF, retention.
2. Publish — Producers send keyed records.
3. Store — Brokers append per partition.
4. Subscribe — Consumers join groups and read.

Informative example

Example:

kafka-topics --bootstrap-server localhost:9092 --create --topic topics --partitions 6 --replication-factor 3
kafka-console-producer --bootstrap-server localhost:9092 --topic topics
kafka-console-consumer --bootstrap-server localhost:9092 --topic topics --from-beginning
kafka-consumer-groups --bootstrap-server localhost:9092 --describe --group topics-service

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

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