Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Concurrency Programming with Java 8

You're reading from   Mastering Concurrency Programming with Java 8 Master the principles and techniques of multithreaded programming with the Java 8 Concurrency API

Arrow left icon
Product type Paperback
Published in Feb 2016
Publisher Packt
ISBN-13 9781785886126
Length 430 pages
Edition 1st Edition
Languages
Concepts
Arrow right icon
Author (1):
Arrow left icon
Javier Fernández González Javier Fernández González
Author Profile Icon Javier Fernández González
Javier Fernández González
Arrow right icon
View More author details
Toc

Table of Contents (13) Chapters Close

Preface 1. The First Step – Concurrency Design Principles FREE CHAPTER 2. Managing Lots of Threads – Executors 3. Getting the Maximum from Executors 4. Getting Data from the Tasks – The Callable and Future Interfaces 5. Running Tasks Divided into Phases – The Phaser Class 6. Optimizing Divide and Conquer Solutions – The Fork/Join Framework 7. Processing Massive Datasets with Parallel Streams – The Map and Reduce Model 8. Processing Massive Datasets with Parallel Streams – The Map and Collect Model 9. Diving into Concurrent Data Structures and Synchronization Utilities 10. Integration of Fragments and Implementation of Alternatives 11. Testing and Monitoring Concurrent Applications Index

Implementation of alternatives with concurrent programming


Most of the examples we have implemented through the chapters of this book can be implemented using other components of the Java concurrency API. In this section, we will describe how to implement some of these alternatives.

The k-nearest neighbors' algorithm

You have implemented the k-nearest neighbors' algorithm in Chapter 2, Managing Lots of Threads – Executors, using an executor. This is a simple machine-learning algorithm used for supervised classification. You have a training set of previous classified examples. To obtain the class of a new example, you calculate the distance from this example to the training set of examples. The majority of classes in the nearest examples are the classes selected for the example. You can also implement this algorithm with one of the following components of the concurrency API:

  • Threads: You can implement this example using Thread objects. You have to execute the tasks executed in the executor...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at AU $24.99/month. Cancel anytime