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
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The following exercises cover the various topics from this chapter. Most of the exercises require implementing new concurrent data structures using atomic variables and the CAS instruction. These data structures can also be solved using the synchronized statement, so it is helpful to contrast the advantages of the two approaches:

  1. Implement a custom ExecutionContext class called PiggybackContext, which executes Runnable objects on the same thread that calls the execute method. Ensure that a Runnable object executing on the PiggybackContext can also call the execute method and that exceptions are properly reported.

  2. Implement a TreiberStack class, which implements a concurrent stack abstraction:

                class TreiberStack[T] { 
                  def push(x: T): Unit = ??? 
                  def pop(): T = ??? 

    Use an atomic reference variable that points to a linked list of nodes that were previously pushed to the stack. Make sure that your implementation...