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You're reading from Mastering Concurrency Programming with Java 9, Second Edition Fast, reactive and parallel application development

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781785887949

Length 516 pages

Edition 2nd Edition

Languages

Java

Tools

Construct

Concepts

Application Development

Author (1):

Javier Fernández González

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Table of Contents (14) Chapters

Preface

1. The First Step - Concurrency Design Principles

2. Working with Basic Elements - Threads and Runnables FREE CHAPTER

3. Managing Lots of Threads - Executors

4. Getting the Most from Executors

5. Getting Data from Tasks - The Callable and Future Interfaces

6. Running Tasks Divided into Phases - The Phaser Class

7. Optimizing Divide and Conquer Solutions - The Fork/Join Framework

8. Processing Massive Datasets with Parallel Streams - The Map and Reduce Model

9. Processing Massive Datasets with Parallel Streams - The Map and Collect Model

10. Asynchronous Stream Processing - Reactive Streams

11. Diving into Concurrent Data Structures and Synchronization Utilities

12. Testing and Monitoring Concurrent Applications

13. Concurrency in JVM - Clojure and Groovy with the Gpars Library and Scala

The second example - a recommendation system

A recommendation system recommends a product or a service to a customer based on the products/services he has bought/used and in the products/services bought/used by the users that have bought/used the same services as him.

We have used the example explained in the previous section to implement a recommendation system. Each description of a product includes the reviews of a number of customers to a product. This review includes the score the customer gives to the product.

In this example, you will use these reviews to get a list of the products that may be interesting to a customer. We will obtain the list of the products purchased by a customer. In order to get that list, a list of the users who have purchased those products and the list of products purchased by those users are sorted using the average score given in the reviews. That will be the suggested products for the user.