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


In this chapter, we learned how to use parallel collections to improve program performance. We have seen that sequential operations on large collections can be easily parallelized and learned the difference between parallelizable and non-parallelizable collections. We investigated how mutability and side effects impact correctness and determinism of parallel operations and saw the importance of using associative operators for parallel operations. Finally, we studied how to implement our custom parallel collection class.

We also found, however, that tuning program performance is tricky. Effects such as memory contention, garbage collection, and dynamic compilation may impact the performance of the program in ways that are hard to predict by looking at the source code. Throughout this section, we urged you to confirm suspicions and claims about program performance by experimentally validating them. Understanding the performance characteristics of your program is the first step toward...