《Mastering Kafka Streams and ksqlDB》PDF电子书下载
《Mastering Kafka Streams and ksqlDB》内容简介
Mitch Seymour / O'Reilly Media, Inc. / 2021-3-9 / USD 39.99 -
Working with unbounded and fast-moving data streams has historically been difficult. But with Kafka Streams and ksqlDB, building stream processing applications is easy and fun. This practical guide explores the world of real-time data systems through the lens of these popular technologies and explains important stream processing concepts against a backdrop of interesting business problems.
Mitch Seymour, senior data systems engineer at Mailchimp, introduces you to both Kafka Streams and ksqlDB so that you can choose the best tool for each unique stream processing project. Non-Java developers will find the ksqlDB path to be an especially gentle introduction to stream processing. In this book, you’ll learn:
Basic and advanced uses of Kafka Streams and ksqlDB
How to transform, enrich, and process event streams
How to build both stateless and stateful stream processing applications
The different notions of time and the role it plays in stream processing
How to to build event-driven microservices on top of continuous event streams
Features, operational characteristics, deployment patterns, and configuration tips for both technologies
Working with unbounded and fast-moving data streams has historically been difficult. But with Kafka Streams and ksqlDB, building stream processing applications is easy and fun. This practical guide explores the world of real-time data systems through the lens of these popular technologies and explains important stream processing concepts against a backdrop of interesting business problems.
Mitch Seymour, senior data systems engineer at Mailchimp, introduces you to both Kafka Streams and ksqlDB so that you can choose the best tool for each unique stream processing project. Non-Java developers will find the ksqlDB path to be an especially gentle introduction to stream processing. In this book, you’ll learn:
Basic and advanced uses of Kafka Streams and ksqlDB
How to transform, enrich, and process event streams
How to build both stateless and stateful stream processing applications
The different notions of time and the role it plays in stream processing
How to to build event-driven microservices on top of continuous event streams
Features, operational characteristics, deployment patterns, and configuration tips for both technologies
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