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Learning Concurrent Programming in Scala

Learning Concurrent Programming in Scala

By : Prokopec
4.7 (10)
Buy this Book
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Learning Concurrent Programming in Scala

Learning Concurrent Programming in Scala

4.7 (10)
By: Prokopec
Buy this Book

Overview of this book

This book is a must-have tutorial for software developers aiming to write concurrent programs in Scala, or broaden their existing knowledge of concurrency. This book is intended for Scala programmers that have no prior knowledge about concurrent programming, as well as those seeking to broaden their existing knowledge about concurrency. Basic knowledge of the Scala programming language will be helpful. Readers with a solid knowledge in another programming language, such as Java, should find this book easily accessible.
Table of Contents (11 chapters)
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Preface
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Preface
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How this book is organized
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
Lock Free Chapter
1
1. Introduction
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1. Introduction
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Concurrent programming
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The advantages of Scala
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Preliminaries
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Summary
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Exercises
2
2. Concurrency on the JVM and the Java Memory Model
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2. Concurrency on the JVM and the Java Memory Model
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Processes and Threads
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Monitors and synchronization
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Volatile variables
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The Java Memory Model
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Summary
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Exercises
3
3. Traditional Building Blocks of Concurrency
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3. Traditional Building Blocks of Concurrency
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The Executor and ExecutionContext objects
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Atomic primitives
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Lazy values
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Concurrent collections
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Creating and handling processes
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Summary
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Exercises
4
4. Asynchronous Programming with Futures and Promises
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4. Asynchronous Programming with Futures and Promises
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Futures
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Promises
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Futures and blocking
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The Scala Async library
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Alternative Future frameworks
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Summary
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Exercises
5
5. Data-Parallel Collections
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5. Data-Parallel Collections
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Scala collections in a nutshell
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Using parallel collections
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Caveats of parallel collections
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Using parallel and concurrent collections together
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Implementing custom parallel collections
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Alternative data-parallel frameworks
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Summary
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Exercises
6
6. Concurrent Programming with Reactive Extensions
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6. Concurrent Programming with Reactive Extensions
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Creating Observable objects
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Composing Observable objects
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Rx schedulers
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Subjects and top-down reactive programming
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Summary
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Exercises
7
7. Software Transactional Memory
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7. Software Transactional Memory
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The trouble with atomic variables
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Using Software Transactional Memory
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Composing transactions
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Retrying transactions
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Transactional collections
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Summary
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Exercises
8
8. Actors
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8. Actors
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Working with actors
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Communication between actors
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Actor supervision
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Remote actors
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Summary
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Exercises
9
9. Concurrency in Practice
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9. Concurrency in Practice
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Choosing the right tools for the job
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Putting it all together – a remote file browser
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Debugging concurrent programs
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Summary
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Exercises
10
Index
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Index

Caveats of parallel collections

Parallel collections were designed to provide a programming API similar to sequential Scala collections. Every sequential collection has a parallel counterpart and most operations have the same signature in both sequential and parallel collections. Still, there are some caveats when using parallel collections, and we will study them in this section.

Non-parallelizable collections

Parallel collections use splitters, represented with the Splitter[T] type, in order to provide parallel operations. A splitter is a more advanced form of an iterator; in addition to the iterator's next and hasNext methods, splitters define the split method that divides the splitter S into a sequence of splitters that traverse parts of S:

def split: Seq[Splitter[T]]

This method allows separate processors to traverse separate parts of the input collection. The split method must be implemented efficiently, as this method is invoked many times during the execution of a parallel operation...

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Learning Concurrent Programming in Scala
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