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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 FREE CHAPTER 2. Concurrency on the JVM and the Java Memory Model 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

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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