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
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Each reactor template can be used to start multiple reactor instances, and each reactor instance can be started with a different reactor scheduler. Different schedulers have different characteristics in terms of execution priority, frequency, latency, and throughput. In this section, we take a look at how to use a non-default scheduler, and how to define custom schedulers when necessary.

We start by defining a reactor that logs incoming events, reports every time it gets scheduled, and ends after being scheduled three times. We will use the sysEvents stream of the reactor, which will be explained in the next section. For now, all you need to know is that the system event stream produces events when the reactor gets some execution time (that is, gets scheduled), and pauses its execution (that is, gets pre-empted).

The Logger reactor is shown in the following snippet:

class Logger extends Reactor[String] { 
  var count = 3 
  sysEvents onMatch { 
    case ReactorScheduled =>