Mastering Concurrency Programming with Java 9, 2nd Edition

Mastering Concurrency Programming with Java 9 – Second Edition: Fast, reactive and parallel application development

Master the principles to make applications robust, scalable and responsive

About This Book

• Implement concurrent applications using the Java 9 Concurrency API and its new components
• Improve the performance of your applications and process more data at the same time, taking advantage of all of your resources
• Construct real-world examples related to machine learning, data mining, natural language processing, and more

Who This Book Is For

This book is for competent Java developers who have basic understanding of concurrency, but knowledge of effective implementation of concurrent programs or usage of streams for making processes more efficient is not required

What You Will Learn

• Master the principles that every concurrent application must follow
• See how to parallelize a sequential algorithm to obtain better performance without data inconsistencies and deadlocks
• Get the most from the Java Concurrency API components
• Separate the thread management from the rest of the application with the Executor component
• Execute phased-based tasks in an efficient way with the Phaser components
• Solve problems using a parallelized version of the divide and conquer paradigm with the Fork / Join framework
• Find out how to use parallel Streams and Reactive Streams
• Implement the “map and reduce” and “map and collect” programming models
• Control the concurrent data structures and synchronization mechanisms provided by the Java Concurrency API
• Implement efficient solutions for some actual problems such as data mining, machine

Table of Contents

Chapter 1. The First Step – Concurrency Design Principles
Chapter 2. Working with Basic Elements – Threads and Runnables
Chapter 3. Managing Lots of Threads – Executors
Chapter 4. Getting the Most from Executors
Chapter 5. Getting Data from Tasks – The Callable and Future Interfaces
Chapter 6. Running Tasks Divided into Phases – The Phaser Class
Chapter 7. Optimizing Divide and Conquer Solutions – The Fork/Join Framework
Chapter 8. Processing Massive Datasets with Parallel Streams – The Map and Reduce Model
Chapter 9. Processing Massive Datasets with Parallel Streams – The Map and Collect Model
Chapter 10. Asynchronous Stream Processing – Reactive Streams
Chapter 11. Diving into Concurrent Data Structures and Synchronization Utilities
Chapter 12. Testing and Monitoring Concurrent Applications
Chapter 13. Concurrency in JVM – Clojure and Groovy with the Gpars Library and Scala