Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications

From the Preface

What You Will Learn in This Book

This book will teach you everything you need to know about stream processing with Apache Flink. It consists of 11 chapters that hopefully tell a coherent story. While some chapters are descriptive and aim to introduce high-level design concepts, others are more hands-on and contain many code examples.

While we intended for the book to be read in chapter order when we were writing it, readers familiar with a chapter’s content might want to skip it. Others more interested in writing Flink code right away might want to read the practical chapters first. In the following, we briefly describe the contents of each chapter, so you can directly jump to those chapters that interest you most.

• Chapter 1 gives an overview of stateful stream processing, data processing application architectures, application designs, and the benefits of stream processing over traditional approaches. It also gives you a brief look at what it is like to run your first streaming application on a local Flink instance.

• Chapter 2 discusses the fundamental concepts and challenges of stream processing, independent of Flink.

• Chapter 3 describes Flink’s system architecture and internals. It discusses distributed architecture, time and state handling in streaming applications, and Flink’s fault-tolerance mechanisms.

• Chapter 4 explains how to set up an environment to develop and debug Flink applications.

• Chapter 5 introduces you to the basics of the Flink’s DataStream API. You will learn how to implement a DataStream application and which stream transformations, functions, and data types are supported.

• Chapter 6 discusses the time-based operators of the DataStream API. This includes window operators and time-based joins as well as process functions that provide the most flexibility when dealing with time in streaming applications.

• Chapter 7 explains how to implement stateful functions and discusses everything around this topic, such as the performance, robustness, and evolution of stateful functions. It also shows how to use Flink’s queryable state.

• Chapter 8 presents Flink’s most commonly used source and sink connectors. It discusses Flink’s approach to end-to-end application consistency and how to implement custom connectors to ingest data from and emit data to external systems.

• Chapter 9 discusses how to set up and configure Flink clusters in various environments.

• Chapter 10 covers operation, monitoring, and maintenance of streaming applications that run 24/7.

• Finally, Chapter 11 contains resources you can use to ask questions, attend Flink-related events, and learn how Flink is currently being used.