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  • Book Overview & Buying Mastering Concurrency Programming with Java 9, Second Edition
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Mastering Concurrency Programming with Java 9, Second Edition

Mastering Concurrency Programming with Java 9, Second Edition

By : Javier Fernández González
3.8 (4)
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Mastering Concurrency Programming with Java 9, Second Edition

Mastering Concurrency Programming with Java 9, Second Edition

3.8 (4)
By: Javier Fernández González

Overview of this book

Concurrency programming allows several large tasks to be divided into smaller sub-tasks, which are further processed as individual tasks that run in parallel. Java 9 includes a comprehensive API with lots of ready-to-use components for easily implementing powerful concurrency applications, but with high flexibility so you can adapt these components to your needs. The book starts with a full description of the design principles of concurrent applications and explains how to parallelize a sequential algorithm. You will then be introduced to Threads and Runnables, which are an integral part of Java 9's concurrency API. You will see how to use all the components of the Java concurrency API, from the basics to the most advanced techniques, and will implement them in powerful real-world concurrency applications. The book ends with a detailed description of the tools and techniques you can use to test a concurrent Java application, along with a brief insight into other concurrency mechanisms in JVM.
Table of Contents (21 chapters)
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Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface

The second example - a data filtering algorithm


Suppose that you have a lot of data that describes a list of items. For example, say that you have a lot of attributes (name, surname, address, phone number, and so on) of a lot of people. It's a common need to obtain the data that meets certain criteria. For example, you might want to obtain the details of people who live in a certain street or with a certain name.

In this section, you will implement one of those filtering programs. We have used the Census-Income KDD dataset from the UCI (you can download it from https://archive.ics.uci.edu/ml/datasets/Census-Income+%28KDD%29), which contains weighted census data extracted from the 1994 and 1995 current population surveys conducted by the U.S. Census Bureau.

In the concurrent version of this example, you will learn how to cancel tasks that are running in the fork/join pool and how to manage unchecked exceptions that can be thrown in a task.

Common features

We have implemented some classes to read...

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