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)

Atomicity, race, deadlocks, and starvation

To write and analyze concurrent programs successfully, you have to be aware of some key concepts: atomicity, race, deadlocks, and starvation. Atomicity is a property you have to carefully exploit for safe and correct operation. Race is a natural condition related to the timing of events in a concurrent system, and can create irreproducible subtle bugs. You have to avoid deadlocks at all costs. Starvation is usually related to scheduling algorithms, but can also be caused by bugs in the program.

A race condition is a condition in which the outcome of a program depends on the sequence or timing of concurrent executions. A race condition is a bug when at least one of the outcomes is undesirable. Consider the following data type representing a bank account:

type Account struct {
     Balance int
func (acct *Account) Withdraw(amt int) error {
     if acct.Balance < amt {