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Learning Concurrent Programming in Scala

You're reading from   Learning Concurrent Programming in Scala Dive into the Scala framework with this programming guide, created to help you learn Scala and to build intricate, modern, scalable concurrent applications

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Product type Paperback
Published in Nov 2014
Publisher Packt
ISBN-13 9781783281411
Length 366 pages
Edition 1st Edition
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Author (1):
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Aleksandar Prokopec Aleksandar Prokopec
Author Profile Icon Aleksandar Prokopec
Aleksandar Prokopec
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Table of Contents (11) Chapters Close

Preface 1. Introduction 2. Concurrency on the JVM and the Java Memory Model FREE CHAPTER 3. Traditional Building Blocks of Concurrency 4. Asynchronous Programming with Futures and Promises 5. Data-Parallel Collections 6. Concurrent Programming with Reactive Extensions 7. Software Transactional Memory 8. Actors 9. Concurrency in Practice Index

Concurrent collections

As you can conclude from the discussion on 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 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 with 20 different elements, this example arbitrarily prints...

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