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Concurrent Patterns and Best Practices

Concurrent Patterns and Best Practices

By : S. Khot
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Concurrent Patterns and Best Practices

Concurrent Patterns and Best Practices

5 (1)
By: S. Khot

Overview of this book

Selecting the correct concurrency architecture has a significant impact on the design and performance of your applications. Concurrent design patterns help you understand the different characteristics of parallel architecture to make your code faster and more efficient. This book will help Java developers take a hands-on approach to building scalable and distributed apps by following step-by-step explanations of essential concepts and practical examples. You’ll begin with basic concurrency concepts and delve into the patterns used for explicit locking, lock-free programming, futures, and actors. You’ll explore coding with multithreading design patterns, including master, slave, leader, follower, and map-reduce, and then move on to solve problems using synchronizer patterns. You'll even discover the rationale for these patterns in distributed and parallel applications, and understand how future composition, immutability, and the monadic flow help you create more robust code. By the end of the book, you’ll be able to use concurrent design patterns to build high performance applications confidently.
Table of Contents (9 chapters)
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Thread Pools

In this chapter, we will be looking at more patterns for staying away from explicit locking and state management. The theme is to let us focus on the business logic and the rest of the boilerplate of explicit thread creation and management handled by a framework.

This set of design patterns yields robust code as we reuse tried and tested, well-proven library code. We start with thread pooling as a major step toward focusing on our business logic as tasks. The pooling patterns give us a facility to run these tasks concurrently. 

Firstly, we will cover the need for thread pools and the notion of a task. A task is a manifestation of the command design pattern, decoupling the task definition from its execution. We then look at ExecutorService, the pooling facility given by Java's threading library. Blocking queues are...

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