Book Image

Mastering Concurrency Programming with Java 8

By : Javier Fernández González
Book Image

Mastering Concurrency Programming with Java 8

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. All the sub-tasks are combined together once the required results are achieved; they are then merged to get the final output. The whole process is very complex. This process goes from the design of concurrent algorithms to the testing phase where concurrent applications need extra attention. Java includes a comprehensive API with a lot of ready-to-use components to implement powerful concurrency applications in an easy way, but with a high flexibility to adapt these components to your needs. The book starts with a full description of design principles of concurrent applications and how to parallelize a sequential algorithm. We'll show you how to use all the components of the Java Concurrency API from basics to the most advanced techniques to implement them in powerful concurrency applications in Java. You will be using real-world examples of complex algorithms related to machine learning, data mining, natural language processing, image processing in client / server environments. Next, you will learn how to use the most important components of the Java 8 Concurrency API: the Executor framework to execute multiple tasks in your applications, the phaser class to implement concurrent tasks divided into phases, and the Fork/Join framework to implement concurrent tasks that can be split into smaller problems (using the divide and conquer technique). Toward the end, we will cover the new inclusions in Java 8 API, the Map and Reduce model, and the Map and Collect model. The book will also teach you about the data structures and synchronization utilities to avoid data-race conditions and other critical problems. Finally, the book ends with a detailed description of the tools and techniques that you can use to test a Java concurrent application.
Table of Contents (18 chapters)
Mastering Concurrency Programming with Java 8
About the Author
About the Reviewers

The first example – the k-means clustering algorithm

The k-means clustering algorithm is a clustering algorithm to group a set of items not previously classified into a predefined number of k clusters. It's very popular within the data mining and machine learning world to organize and classify data in an unsupervised way.

Each item is normally defined by a vector of characteristics or attributes. All the items have the same number of attributes. Each cluster is also defined by a vector with the same number of attributes that represents all the items classified into that cluster. This vector is named the centroid. For example, if the items are defined by numeric vectors, the clusters are defined by the mean of the items classified into that cluster.

Basically, the algorithm has four steps:

  1. Initialization: In the first step, you have to create the initial vectors that represent the K clusters. Normally, you will initialize those vectors randomly.

  2. Assignment: Then, you classify each item into...