Book Image

Effective Concurrency in Go

By : Burak Serdar
5 (1)
Book Image

Effective Concurrency in Go

5 (1)
By: Burak Serdar

Overview of this book

The Go language has been gaining momentum due to its treatment of concurrency as a core language feature, making concurrent programming more accessible than ever. However, concurrency is still an inherently difficult skill to master, since it requires the development of the right mindset to decompose problems into concurrent components correctly. This book will guide you in deepening your understanding of concurrency and show you how to make the most of its advantages. You’ll start by learning what guarantees are offered by the language when running concurrent programs. Through multiple examples, you will see how to use this information to develop concurrent algorithms that run without data races and complete successfully. You’ll also find out all you need to know about multiple common concurrency patterns, such as worker pools, asynchronous pipelines, fan-in/fan-out, scheduling periodic or future tasks, and error and panic handling in goroutines. The central theme of this book is to give you, the developer, an understanding of why concurrent programs behave the way they do, and how they can be used to build correct programs that work the same way in all platforms. By the time you finish the final chapter, you’ll be able to develop, analyze, and troubleshoot concurrent algorithms written in Go.
Table of Contents (13 chapters)

Summary

In this chapter, we studied three well-known concurrency problems that show up consistently when working with non-trivial problems. Producer-consumer implementations have uses in data processing pipelines, crawlers, device interactions, network communications, and more. The dining philosophers problem is a good demonstration of critical sections that require multiple mutexes. Finally, rate-limiting has applications in ensuring the quality of service, limiting resource utilization, and API accounting.

In the next chapter, we will start looking at more realistic examples of concurrent programming, in particular, worker pools, concurrent data pipelines, and fan-in/fan-out.