Learning Concurrent Programming in Scala

Aleksandar Prokopec

• Éditeur: Packt Publishing
• Année: 2014
• ISBN:
  9781783281411
• Édition: 1
• Sujet: Informatica
• Sous-sujet: Sviluppo web

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.

Learning Concurrent Programming in Scala

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Table of Contents

Learning Concurrent Programming in Scala

Credits

Foreword

About the Author

Acknowledgments

About the Reviewers

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Preface

How this book is organized

What this book covers

What you need for this book

Installing the JDK

Installing and using SBT

Using Eclipse, IntelliJ IDEA, or another IDE

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Errata

Piracy

Questions

1. Introduction

Concurrent programming

A brief overview of traditional concurrency

Modern concurrency paradigms

The advantages of Scala

Preliminaries

Execution of a Scala program

A Scala primer

Summary

Exercises

2. Concurrency on the JVM and the Java Memory Model

Processes and Threads

Creating and starting threads

Atomic execution

Reordering

Monitors and synchronization

Deadlocks

Guarded blocks

Interrupting threads and the graceful shutdown

Volatile variables

The Java Memory Model

Immutable objects and final fields

Summary

Exercises

3. Traditional Building Blocks of Concurrency

The Executor and ExecutionContext objects

Atomic primitives

Atomic variables

Lock-free programming

Implementing locks explicitly

The ABA problem

Lazy values

Concurrent collections

Concurrent queues

Concurrent sets and maps

Concurrent traversals

Creating and handling processes

Summary

Exercises

4. Asynchronous Programming with Futures and Promises

Futures

Starting future computations

Future callbacks

Futures and exceptions

Using the Try type

Fatal exceptions

Functional composition on futures

Promises

Converting callback-based APIs

Extending the future API

Cancellation of asynchronous computations

Futures and blocking

Awaiting futures

Blocking in asynchronous computations

The Scala Async library

Alternative Future frameworks

Summary

Exercises

5. Data-Parallel Collections

Scala collections in a nutshell

Using parallel collections

Parallel collection class hierarchy

Configuring the parallelism level

Measuring the performance on the JVM

Caveats of parallel collections

Non-parallelizable collections

Non-parallelizable operations

Side effects in parallel operations

Nondeterministic parallel operations

Commutative and associative operators

Using parallel and concurrent collections together

Weakly consistent iterators

Implementing custom parallel collections

Splitters

Combiners

Alternative data-parallel frameworks

Collections hierarchy in ScalaBlitz

Summary

Exercises

6. Concurrent Programming with Reactive Extensions

Creating Observable objects

Observables and exceptions

The Observable contract

Implementing custom Observable objects

Creating Observables from futures

Subscriptions

Composing Observable objects

Nested observables

Failure handling in observables

Rx schedulers

Using custom schedulers for UI applications

Subjects and top-down reactive programming

Summary

Exercises

7. Software Transactional Memory

The trouble with atomic variables

Using Software Transactional Memory

Transactional references

Using the atomic statement

Composing transactions

The interaction between transactions and side effects

Single-operation transactions

Nesting transactions

Transactions and exceptions

Retrying transactions

Retrying with timeouts

Transactional collections

Transaction-local variables

Transactional arrays

Transactional maps

Summary

Exercises

8. Actors

Working with actors

Creating actor systems and actors

Managing unhandled messages

Actor behavior and state

Akka actor hierarchy

Identifying actors

The actor life cycle

Communication between actors

The ask pattern

The forward pattern

Stopping actors

Actor supervision

Remote actors

Summary

Exercises

9. Concurrency in Practice

Choosing the right tools for the job

Putting it all together – a remote file browser

Modeling the filesystem

The server interface

Client navigation API

The client user interface

Implementing the client logic

Improving the remote file browser

Debugging concurrent programs

Deadlocks and lack of progress

Debugging incorrect program outputs

Performance debugging

Summary

Exercises

Index

Learning Concurrent Programming in Scala

Copyright © 2014 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: November 2014

Production reference: 1211114

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78328-141-1

www.packtpub.com

Credits

Author

Aleksandar Prokopec

Reviewers

Dominik Gruntz

Vladimir Kostyukov

Zhen Li

Lukas Rytz

Michel Schinz

Samira Tasharofi

Commissioning Editor

Kevin Colaco

Acquisition Editor

Kevin Colaco

Content Development Editor

Vaibhav Pawar

Technical Editor

Sebastian Rodrigues

Copy Editors

Rashmi Sawant

Stuti Srivastava

Project Coordinator

Kranti Berde

Proofreaders

Mario Cecere

Martin Diver

Ameesha Green

Indexer

Tejal Soni

Production Coordinator

Aparna Bhagat

Cover Work

Aparna Bhagat

Foreword

Concurrent and parallel programming have progressed from niche disciplines, of interest only to kernel programming and high-performance computing, to something that every competent programmer must know. As parallel and distributed computing systems are now the norm, most applications are concurrent, be it for increasing the performance or for handling asynchronous events.

So far, most developers are unprepared to deal with this revolution. Maybe they have learned the traditional concurrency model, which is based on threads and locks, in school, but this model has become inadequate for dealing with massive concurrency in a reliable manner and with acceptable productivity. Indeed, threads and locks are hard to use and harder to get right. To make progress, one needs to use concurrency abstractions that are at a higher level and composable.

15 years ago, I worked on a predecessor of Scala: "Funnel" was an experimental programming language that had a concurrent semantics at its core. All the programming concepts were explained in this language as syntactic sugar on top of "functional nets", an object-oriented variant of "join calculus". Even though join calculus is a beautiful theory, we realized after some experimentation that the concurrency problem is more multifaceted than what can be comfortably expressed in a single formalism. There is no silver bullet for all concurrency issues; the right solution depends on what one needs to achieve. Do you want to define asynchronous computations that react to events or streams of values? Or have autonomous, isolated entities communicating via messages? Or define trans...