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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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Exercises

In the following exercises, you are expected to define several reactor protocols. In some cases, the task is to first investigate a specific algorithm online on your own, and then implement it using the Reactors framework. The exercises are ordered by their difficulty, and range from simple tasks to more complex ones.

  1. Define a method called twice, which takes a target channel, and returns a channel that forwards every event twice to the target.
            def twice[T](target: Channel[T]): Channel[T] 
    
  2. Define a method called throttle, which throttles the rate at which events are forwarded to the target channel.
            def throttle[T](target: Channel[T]): Channel[T] 
    

    Hint: you will have to use the Clock service and the functional event stream composition.

  3. The Shutdown service shown in this chapter can run out of memory if there are a lot of reactors subscribing to it. This is because the current implementation never removes entries from the service's subscribers map. Modify the custom...

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