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.
What You Will 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
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