This book is organized into a sequence of chapters with various topics on concurrent programming. The book covers the fundamental concurrent APIs that are a part of the Scala runtime, introduces more complex concurrency primitives, and gives an extensive overview of high-level concurrency abstractions.

Chapter 1, Introduction, explains the need for concurrent programming and gives some philosophical background. At the same time, it covers the basics of the Scala programming language that are required for understanding the rest of this book.

Chapter 2, Concurrency on the JVM and the Java Memory Model, teaches you the basics of concurrent programming. This chapter will teach you how to use threads and how to protect access to shared memory and introduce the Java Memory Model.

Chapter 3, Traditional Building Blocks of Concurrency, presents classic concurrency utilities, such as thread pools, atomic variables, and concurrent collections, with a particular focus on the interaction with the features of the Scala language. The emphasis in this book is on the modern, high-level concurrent programming frameworks. Consequently, this chapter presents an overview of traditional concurrent programming techniques, but it does not aim to be extensive.

Chapter 4, Asynchronous Programming with Futures and Promises, is the first chapter that deals with a Scala-specific concurrency framework. This chapter presents the futures and promises API and shows how to correctly use them when implementing asynchronous programs.

Chapter 5, Data-Parallel Collections, describes the Scala parallel collections framework. In this chapter, you will learn how to parallelize collection operations, when it is allowed to parallelize them, and how to assess the performance benefits of doing so.

Chapter 6, Concurrent Programming with Reactive Extensions, teaches you how to use the Reactive Extensions framework for event-based and asynchronous programming. You will see how the operations on event streams correspond to collection operations, how to pass events from one thread to another, and how to design a reactive user interface using event streams.

Chapter 7, Software Transactional Memory, introduces the ScalaSTM library for transactional programming, which aims to provide a safer, more intuitive, shared-memory programming model. In this chapter, you will learn how to protect access to shared data using scalable memory transactions and, at the same time, reduce the risk of deadlocks and race conditions.

Chapter 8, Actors, presents the actor programming model and the Akka framework. In this chapter, you will learn how to transparently build message-passing distributed programs that run on multiple machines.

Chapter 9, Concurrency in Practice, summarizes the different concurrency libraries introduced in the earlier chapters. In this chapter, you will learn how to choose the correct concurrency abstraction to solve a given problem, and how to combine different concurrency abstractions together when designing larger concurrent applications.

Chapter 10, Reactors, presents the reactor programming model, whose focus is improved composition in concurrent and distributed programs. This emerging model enables separation of concurrent and distributed programming patterns into modular components called protocols.

While we recommend that you read the chapters in the order in which they appear, this is not strictly necessary. If you are well acquainted with the content in Chapter 2, Concurrency on the JVM and the Java Memory Model, you can study most of the other chapters directly. The only chapters that rely on the content from all the preceding chapters are Chapter 9, Concurrency in Practice, where we present a practical overview of the topics in this book, and Chapter 10, Reactors, for which it is helpful to understand how actors and event streams work.