Book Image

Learning Concurrent Programming in Scala - Second Edition

By : Aleksandar Prokopec
Book Image

Learning Concurrent Programming in Scala - Second Edition

By: Aleksandar Prokopec

Overview of this book

Scala is a modern, multiparadigm programming language designed to express common programming patterns in a concise, elegant, and type-safe way. Scala smoothly integrates the features of object-oriented and functional languages. In this second edition, you will find updated coverage of the Scala 2.12 platform. The Scala 2.12 series targets Java 8 and requires it for execution. The book starts by introducing you to the foundations of concurrent programming on the JVM, outlining the basics of the Java Memory Model, and then shows some of the classic building blocks of concurrency, such as the atomic variables, thread pools, and concurrent data structures, along with the caveats of traditional concurrency. The book then walks you through different high-level concurrency abstractions, each tailored toward a specific class of programming tasks, while touching on the latest advancements of async programming capabilities of Scala. It also covers some useful patterns and idioms to use with the techniques described. Finally, the book presents an overview of when to use which concurrency library and demonstrates how they all work together, and then presents new exciting approaches to building concurrent and distributed systems. Who this book is written for If you are a Scala programmer with no prior knowledge of concurrent programming, or seeking to broaden your existing knowledge about concurrency, this book is for you. Basic knowledge of the Scala programming language will be helpful.
Table of Contents (19 chapters)
Learning Concurrent Programming in Scala - Second Edition
About the Author
About the Reviewers
Customer Feedback

Reactor system services

In the earlier sections, we learned that reactors delimit concurrent executions, and that event streams allow routing events within each reactor. This is already a powerful set of abstractions, and we can use reactors and event streams to write all kinds of distributed programs. However, such a model is restricted to reactor computations only. We cannot, for example, start blocking I/O operations, read from a temperature sensor implemented in hardware, wait until a GPU computation completes, or react to temporal events. In some cases, we need to interact with the native capabilities of the OS, or tap into a rich ecosystem of existing libraries. For this purpose, every reactor system has a set of services: protocols that relate event streams to the outside world.

In this section, we will take a closer look at various services that are available by default, and also show how to implement custom services and plug them into reactor systems.

The logging service

We start with...