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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Caveats with parallel collections

Parallel collections were designed to provide a programming API similar to sequential Scala collections. Every sequential collection has a parallel counterpart and most operations have the same signature in both sequential and parallel collections. Still, there are some caveats when using parallel collections, and we will study them in this section.

Non-parallelizable collections

Parallel collections use splitters, represented with the Splitter[T] type, in order to provide parallel operations. A splitter is a more advanced form of an iterator; in addition to the iterator's next and hasNext methods, splitters define the split method, which divides the splitter S into a sequence of splitters that traverse parts of the S splitter:

def split: Seq[Splitter[T]] 

This method allows separate processors to traverse separate parts of the input collection. The split method must be implemented efficiently, as this method is invoked many times during the execution...