Book Image

Effective Concurrency in Go

By : Burak Serdar
Book Image

Effective Concurrency in Go

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)

Worker pools

Many concurrent Go programs are combinations of variations on worker pools. One reason could be that channels provide a really good mechanism for assigning tasks to waiting goroutines. A worker pool is simply a group of one or more goroutines that performs the same task on multiple instances of inputs. There are several reasons why a worker pool may be more practical than creating goroutines as needed. One reason is that creation of a worker instance in the worker pool could be expensive (not the creation of a goroutine, that’s cheap, but the initialization of a worker goroutine can be expensive), so a fixed number of workers can be created once and then reused. Another reason is that you potentially need an unbounded number of them, so you create a reasonable number once. Regardless of the situation, once you decide you need a worker pool, there are easy-to-repeat patterns that you can use over and over to create high-performing worker pools.

We first saw a...