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Mastering Concurrency Programming with Java 8

More Information
Learn
  • Design concurrent applications by converting a sequential algorithm into a concurrent one
  • Discover how to avoid all the possible problems you can get in concurrent algorithms
  • Use the Executor framework to manage concurrent tasks without creating threads
  • Extend and modify Executors to adapt their behavior to your needs
  • Solve problems using the divide and conquer technique and the Fork/Join framework
  • Process massive data sets with parallel streams and Map/Reduce implementation
  • Control data-race conditions using concurrent data structures and synchronization mechanisms
  • Test and monitor concurrent applications
About

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.

Features
  • Implement concurrent applications using the Java 8 Concurrency API and its new components
  • Improve the performance of your applications or process more data at the same time, taking advantage of all of your resources.
  • Construct real-world examples related to machine learning, data mining, image processing, and client/server environments
Page Count 430
Course Length 12 hours 54 minutes
ISBN 9781785886126
Date Of Publication 29 Feb 2016
An introduction to executors
First example – the k-nearest neighbors algorithm
The second example – concurrency in a client/server environment
Comparing the two solutions
Other methods of interest
Summary
Advanced characteristics of executors
The first example – an advanced server application
The second example – executing periodic tasks
Additional information about executors
Summary
Introducing the Callable and Future interfaces
First example – a best-matching algorithm for words
The second example – creating an inverted index for a collection of documents
Summary
An introduction to the Phaser class
First example – a keyword extraction algorithm
The second example – a genetic algorithm
Summary
An introduction to the Fork/Join framework
The first example – the k-means clustering algorithm
The second example – a data filtering algorithm
The third example – the merge sort algorithm
Other methods of the Fork/Join framework
Summary
An introduction to streams
The first example – a numerical summarization application
The second example – an information retrieval search tool
Summary
Using streams to collect data
The first example – searching data without an index
The second example – a recommendation system
The third example – common contacts in a social network
Summary

Authors

Javier Fernández González

Javier Fernández González is a software architect with almost 15 years experience in Java technologies. He has worked as a teacher, researcher, programmer, analyst, and writer, and he now works as an architect in all types of projects related to Java, especially J2EE. As a teacher has over 1,000 hours of training in basic Java, J2EE, and the Struts framework.

As a researcher, he has worked in the field of information retrieval, developing applications for processing large amounts of data in Java, and has participated as a co-author in several journal articles and conference presentations.

Recently, he worked on developing J2EE web applications for various clients from different sectors (public administration, insurance, healthcare, transportation, and so on). He has also worked as a software architect. He is the author of the books, Java 7 Concurrency Cookbook and Mastering Concurrency Programming with Java 8 by Packt Publishing.