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Subtitle:

Categorized streams of records in Apache Kafka that organize and store events

Core Idea:

Kafka topics are named feeds or categories of events to which data is published by producers and from which data is read by consumers, functioning as logical channels that separate different streams of events.

Key Principles:

1. Multi-Producer/Multi-Consumer:
   • Topics support multiple producers writing to them and multiple consumers reading from them
2. Partitioned Storage:
   • Topics are divided into partitions distributed across brokers for parallel processing
3. Retention Policy:
   • Each topic can have a configurable retention period determining how long events are kept
4. Append-Only Log:
   • Events are appended to the topic's partitions in an immutable sequence

Why It Matters:

• Organization:
  • Provides logical separation of different event types or domains
• Scalability:
  • Enables parallel processing through partitioning
• Data Management:
  • Allows for domain-specific retention and compaction policies

How to Implement:

1. Topic Creation:
   • Use kafka-topics.sh command or Admin API to create topics
2. Configure Partitioning:
   • Determine appropriate number of partitions based on throughput needs
3. Set Retention:
   • Configure time-based or size-based retention policies for the topic

Example:

• Scenario:
  • An e-commerce platform tracking various aspects of user activity
• Application:
  • Create separate topics for different event categories:

bin/kafka-topics.sh --create --topic user-signups --partitions 10 --replication-factor 3 --bootstrap-server localhost:9092
bin/kafka-topics.sh --create --topic product-views --partitions 20 --replication-factor 3 --bootstrap-server localhost:9092
bin/kafka-topics.sh --create --topic purchases --partitions 15 --replication-factor 3 --bootstrap-server localhost:9092

• Result:
  • The platform can now handle different types of events with appropriate scaling for each category, making data organization and processing more efficient.

Connections:

• Related Concepts:
  • Kafka Events: The records stored within topics
  • Kafka Partitions: How topics are divided for distributed processing
• Broader Concepts:
  • Message Queues: Traditional predecessor to topic-based messaging
  • Pub/Sub Pattern: The publisher-subscriber pattern implemented by Kafka topics

References:

1. Primary Source:
   • Apache Kafka documentation on topics
2. Additional Resources:
   • "Kafka: The Definitive Guide" (Chapter on Topics and Partitions)

Tags:

#kafka #topics #event-organization #messaging #pub-sub

Connections:

Sources:

• From: Apache Kafka Getting Started