In systems that handle big data, streaming data, or fast data, it's important to get your data pipelines right. Apache Kafka is a wicked-fast distributed streaming platform that operates as more than just a persistent log or a flexible message queue. With Kafka, you can build the powerful real-time data processing pipelines required by modern distributed systems. Kafka in Action is a fast-paced introduction to every aspect of working with Kafka you need to really reap its benefits.
about the technology
Apache Kafka is a distributed streaming platform for logging and streaming data between services or applications. With Kafka, it's easy to build applications that can act on or react to data streams as they flow through your system. Operational data monitoring, large scale message processing, website activity tracking, log aggregation, and more are all possible with Kafka. Open-source, easily scalable, durable when demand gets heavy, and fast - Kafka is perfect for developers who need total control of the data flowing into and through their applications. The demand for Kafka developers is at an all-time high, as companies like LinkedIn, The New York Times, and Netflix, are relying on Kafka where fast data is essential.
about the book
Kafka in Action is a practical, hands-on guide to building Kafka-based data pipelines. Filled with real-world use cases and scenarios, this book probes Kafka's most common use cases, ranging from simple logging through managing streaming data systems for message routing, analytics, and more. Starting with an overview of Kafka's core concepts, you'll immediately learn how to set up and execute basic data movement tasks and how to record and consume streaming data. As you move through the examples in this book, you'll learn the skills you need to work in a Kafka focused team with the ability to handle both developer and admin based tasks. At the end of this book, you'll be more than ready to dig into even more advanced Kafka topics on your own, and happily able to use Kafka in your day-to-day workflow.
Understanding Kafka's concepts
Implementing Kafka as a message queue
Setting up and executing basic ETL tasks
Recording and consuming streaming data
Working with Kafka producers and consumers from Java applications
Using Kafka as part of a large data project team
Performing Kafka developer and admin tasks
about the reader
Written for intermediate Java developers or data engineers. No prior knowledge of Kafka is required.
about the author
Dylan Scott is a software developer with over ten years of experience in Java and Perl. His experience includes implementing Kafka as a messaging system for a large data migration, and he uses Kafka in his work in the insurance industry. Viktor Gamov is a developer advocate at Confluent. Dave Klein is a developer advocate at Confluent, with over 28 years of experience in the technology industry.
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