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Learning Concurrent Programming in Scala

Learning Concurrent Programming in Scala

By : Prokopec
4.8 (16)
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Learning Concurrent Programming in Scala

Learning Concurrent Programming in Scala

4.8 (16)
By: 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 (11 chapters)
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The Executor and ExecutionContext objects


As discussed in Chapter 2, Concurrency on the JVM and the Java Memory Model, although creating a new thread in a Scala program takes orders of magnitude less computational time compared to creating a new JVM process, thread creation is still much more expensive than allocating a single object, acquiring a monitor lock, or updating an entry in a collection. If an application performs a large number of small concurrent tasks and requires high throughput, we cannot afford to create a fresh thread for each of these tasks. Starting a thread requires us to allocate a memory region for its call stack and a context switch from one thread to another, which can be much more time-consuming than the amount of work in the concurrent task. For this reason, most concurrency frameworks have facilities that maintain a set of threads in a waiting state and start running when concurrently executable work tasks become available. Generally, we call such facilities thread...

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