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Mastering Concurrency Programming with Java 9, Second Edition

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

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781785887949
Length 516 pages
Edition 2nd Edition
Languages
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Author (1):
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Javier Fernández González Javier Fernández González
Author Profile Icon Javier Fernández González
Javier Fernández González
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Toc

Table of Contents (14) Chapters Close

Preface 1. The First Step - Concurrency Design Principles FREE CHAPTER 2. Working with Basic Elements - Threads and Runnables 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.

Common classes

We have added two new classes to the ones used in the...

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