Most of the concurrency objects provided by the Java concurrency API include methods to learn their status. This status can include the number of threads that are executing, the number of threads blocked waiting for a condition, the number of tasks executed, and so on. In this section, you will learn the most important methods you can use and the information you can obtain from them. This information can be very useful to detect the cause of an error, especially if it only occurs in very rare conditions.
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Mastering Concurrency Programming with Java 9, Second Edition
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Mastering Concurrency Programming with Java 9, Second Edition
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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. Java 9 includes a comprehensive API with lots of ready-to-use components for easily implementing powerful concurrency applications, but with high flexibility so you can adapt these components to your needs.
The book starts with a full description of the design principles of concurrent applications and explains how to parallelize a sequential algorithm. You will then be introduced to Threads and Runnables, which are an integral part of Java 9's concurrency API. You will see how to use all the components of the Java concurrency API, from the basics to the most advanced techniques, and will implement them in powerful real-world concurrency applications.
The book ends with a detailed description of the tools and techniques you can use to test a concurrent Java application, along with a brief insight into other concurrency mechanisms in JVM.
Table of Contents (14 chapters)
Preface
Free Chapter
The First Step - Concurrency Design Principles
Working with Basic Elements - Threads and Runnables
Managing Lots of Threads - Executors
Getting the Most from Executors
Getting Data from Tasks - The Callable and Future Interfaces
Running Tasks Divided into Phases - The Phaser Class
Optimizing Divide and Conquer Solutions - The Fork/Join Framework
Processing Massive Datasets with Parallel Streams - The Map and Reduce Model
Processing Massive Datasets with Parallel Streams - The Map and Collect Model
Asynchronous Stream Processing - Reactive Streams
Diving into Concurrent Data Structures and Synchronization Utilities
Testing and Monitoring Concurrent Applications
Concurrency in JVM - Clojure and Groovy with the Gpars Library and Scala
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