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Kafka Streams in Action: Event-driven applications and microservices Edition: 2
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Kafka Streams in Action: Event-driven applications and microservices Edition: 2

by Bill Bejeck

Programming

Book Details

Book Title

Kafka Streams in Action: Event-driven applications and microservices Edition: 2

Author

Bill Bejeck

Publisher

Manning

Publication Date

2024

ISBN

9781617298684

Number of Pages

506

Language

English

Format

PDF

File Size

6.83MB

Subject

Computers>Programming: Libraries API

Table of Contents

  • Kafka Streams in Action
  • Praise for the first edition
  • brief contents
  • contents
  • foreword
  • preface
  • acknowledgments
  • about this book
  • about the author
  • about the cover illustration
  • Part 1
  • Chapter 1. Welcome to the Kafka event streaming platform
  • 1.1 Event streaming
  • 1.2 What is an event?
  • 1.3 An event stream example
  • 1.4 Introducing the Apache Kafka event streaming platform
  • 1.5 A concrete example of applying the Kafka event streaming platform
  • Summary
  • Chapter 2. Kafka brokers
  • 2.1 Introducing Kafka brokers
  • 2.2 Produce requests
  • 2.3 Fetch requests
  • 2.4 Topics and partitions
  • 2.5 Sending your first messages
  • 2.6 Segments
  • 2.7 Tiered storage
  • 2.8 Cluster metadata
  • 2.9 Leaders and followers
  • 2.10 Checking for a healthy broker
  • Summary
  • Part 2
  • Chapter 3. Schema Registry
  • 3.1 Objects
  • 3.2 What is a schema, and why do you need one?
  • 3.3 Subject name strategies
  • 3.4 Schema compatibility
  • 3.5 Schema references
  • 3.6 Schema references and multiple events per topic
  • 3.7 Schema Registry (de)serializers
  • 3.8 Serialization without Schema Registry
  • Summary
  • Chapter 4. Kafka clients
  • 4.1 Introducing Kafka clients
  • 4.2 Producing records with the KafkaProducer
  • 4.3 Consuming records with the KafkaConsumer
  • 4.4 Exactly-once delivery in Kafka
  • 4.5 Using the Admin API for programmatic topic management
  • 4.6 Handling multiple event types in a single topic
  • Summary
  • Chapter 5. Kafka Connect
  • 5.1 An introduction to Kafka Connect
  • 5.2 Integrating external applications into Kafka
  • 5.3 Getting started with Kafka Connect
  • 5.4 Applying Single Message Transforms
  • 5.5 Adding a sink connector
  • 5.6 Building and deploying your own connector
  • Summary
  • Part 3
  • Chapter 6. Developing Kafka Streams
  • 6.1 A look at Kafka Streams
  • 6.2 Kafka Streams DSL
  • 6.3 Hello World for Kafka Streams
  • 6.4 Masking credit card numbers and tracking purchase rewards in a retail sales setting
  • 6.5 Interactive development
  • 6.6 Choosing which events to process
  • Summary
  • Chapter 7. Streams and state
  • 7.1 Stateful vs. stateless
  • 7.2 Adding stateful operations to Kafka Streams
  • 7.3 Stream-stream joins
  • 7.4 State stores in Kafka Streams
  • Summary
  • Chapter 8. The KTable API
  • 8.1 KTable: The update stream
  • 8.2 KTables are stateful
  • 8.3 The KTable API
  • 8.4 KTable aggregations
  • 8.5 GlobalKTable
  • 8.6 Table joins
  • Summary
  • Chapter 9. Windowing and timestamps
  • 9.1 Understanding the role of windows and the different types
  • 9.2 Handling out order data with grace—literally
  • 9.3 Final windowed results
  • 9.4 Timestamps in Kafka Streams
  • 9.5 The TimestampExtractor
  • 9.6 Stream time
  • Summary
  • Chapter 10. The Processor API
  • 10.1 Working with sources, processors, and sinks to create a topology
  • 10.2 Digging deeper into the Processor API with a stock analysis processor
  • 10.3 Data-driven aggregation
  • 10.4 Integrating the Processor API and the Kafka Streams API
  • Summary
  • Chapter 11. ksqlDB
  • 11.1 Understanding ksqlDB
  • 11.2 More about streaming queries
  • 11.3 Persistent vs. push vs. pull queries
  • 11.4 Creating Streams and Tables
  • 11.5 Schema Registry integration
  • 11.6 ksqlDB advanced features
  • Summary
  • Chapter 12. Spring Kafka
  • 12.1 Introducing Spring
  • 12.2 Using Spring to build Kafka-enabled applications
  • 12.3 Spring Kafka Streams
  • Summary
  • Chapter 13. Kafka Streams Interactive Queries
  • 13.1 Kafka Streams and information sharing
  • 13.2 Learning about Interactive Queries
  • Summary
  • Chapter 14. Testing
  • 14.1 Understanding the difference between unit and integration testing
  • Summary
  • Appendices
  • Appendix A—Schema compatibility workshop
  • Appendix B—Confluent resources
  • Appendix C—Working with Avro, Protobuf, and JSON Schema
  • Appendix D—Understanding Kafka Streams architecture
  • Index