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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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Preface
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Free Chapter
1
1. Introduction
1. Introduction
Concurrent programming
The advantages of Scala
Preliminaries
Overview of new features in Scala 2.12
Summary
Exercises
2
2. Concurrency on the JVM and the Java Memory Model
2. Concurrency on the JVM and the Java Memory Model
Processes and threads
Monitors and synchronization
Volatile variables
The Java Memory Model
Summary
Exercises
3
3. Traditional Building Blocks of Concurrency
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3. Traditional Building Blocks of Concurrency
The Executor and ExecutionContext objects
Atomic primitives
Lazy values
Concurrent collections
Custom concurrent data structures
Summary
Exercises
4
4. Asynchronous Programming with Futures and Promises
4. Asynchronous Programming with Futures and Promises
Futures
Promises
Futures and blocking
The Scala Async library
Alternative future frameworks
Summary
Exercises
5
5. Data-Parallel Collections
5. Data-Parallel Collections
Scala collections in a nutshell
Using parallel collections
Caveats with parallel collections
Using parallel and concurrent collections together
Implementing custom parallel collections
Summary
Exercises
6
6. Concurrent Programming with Reactive Extensions
6. Concurrent Programming with Reactive Extensions
Creating Observable objects
Composing Observable objects
Rx schedulers
Subjects and top-down reactive programming
Summary
Exercises
7
7. Software Transactional Memory
7. Software Transactional Memory
The trouble with atomic variables
Using Software Transactional Memory
Composing transactions
Retrying transactions
Transactional collections
Summary
Exercises
8
8. Actors
8. Actors
Working with actors
Communication between actors
Actor supervision
Remote actors
Summary
Exercises
9
9. Concurrency in Practice
9. Concurrency in Practice
Choosing the right tools for the job
Putting it all together - a remote file browser
Debugging concurrent programs
Summary
Exercises
10
10. Reactors
10. Reactors
The need for reactors
Getting started with Reactors
The "Hello World" program
Event streams
Reactors
Schedulers
Reactor lifecycle
Reactor system services
Protocols
Summary
Exercises

Concurrent collections

As you can conclude from the discussion on the Java Memory Model in Chapter 2, Concurrency on the JVM and the Java Memory Model, modifying the Scala standard library collections from different threads can result in arbitrary data corruption. Standard collection implementations do not use any synchronization. Data structures underlying mutable collections can be quite complex; predicting how multiple threads affect the collection state in the absence of synchronization is neither recommended nor possible. We will demonstrate this by letting two threads add numbers to the mutable.ArrayBuffer collection:

import scala.collection._ 
object CollectionsBad extends App { 
  val buffer = mutable.ArrayBuffer[Int]() 
  def asyncAdd(numbers: Seq[Int]) = execute { 
    buffer ++= numbers 
    log(s"buffer = $buffer") 
  } 
  asyncAdd(0 until 10) 
  asyncAdd(10 until 20) 
  Thread.sleep(500) 
}

Instead of printing an array buffer...

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