Book Image

Mastering Concurrency Programming with Java 9 - Second Edition

By : Javier Fernández González
Book Image

Mastering Concurrency Programming with Java 9 - Second Edition

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)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface

The first example - a numerical summarization application


One of the most common needs when you have a big set of data is to process its elements to measure certain characteristics. For example, if you have a set with the products purchased in a shop, you can count the number of products you have sold, the number of units per product you have sold, or the average amount that each customer spent. We have named that process numerical summarization.

In this chapter, we are going to use streams to obtain some measures of the Online Retail dataset of the UCI Machine Learning Repository, which you can download from http://archive.ics.uci.edu/ml/datasets/Online+Retail. This dataset stores all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.

Unlike other chapters, in this case, we explain the concurrent version using streams and then how to implement a serial equivalent version to verify that concurrency improves performance with streams...