Learning Concurrent Programming in Scala

Learning Concurrent Programming in Scala
Learning Concurrent Programming in Scala is published by in November 2014. This book has 366 pages in English, ISBN-13 978-1783281411.

This book will give you an insight into the best practices necessary to build concurrent programs in Scala using modern, high-level concurrency libraries. It 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. It then walks you through different high-level concurrency abstractions, each tailored toward a specific class of programming tasks. Finally, the book presents an overview of when to use which concurrency library and demonstrates how they all work together.

Who This Book Is For

This book is a must-have tutorial for software developers aiming to write concurrent programs in Scala, or broaden their existing knowledge of concurrency.

This book is intended for Scala programmers that have no prior knowledge about concurrent programming, as well as those seeking to broaden their existing knowledge about concurrency. Basic knowledge of the Scala programming language will be helpful. Readers with a solid knowledge in another programming language, such as Java, should find this book easily accessible.

What You Will Learn

  • Get to grips with the fundamentals of concurrent programming on modern multiprocessor systems, with a particular focus on the JVM concurrency model
  • Build high-performance concurrent systems from simple, low-level concurrency primitives
  • Express asynchrony in concurrent computations with futures and promises
  • Seamlessly accelerate sequential programs by using data-parallel collections
  • Implement reactive and event-based programs declaratively with Rx-style event streams
  • Design safe, scalable, and easy-to-comprehend in-memory transactional data models
  • Transparently create distributed applications that scale across multiple machines
  • Choose the correct concurrency abstraction and integrate different concurrency frameworks together in large applications

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