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 and Pipelines

This chapter is about two interrelated concurrency constructs: worker pools and pipelines. While a worker pool deals with splitting work among multiple instances of the same computation, a data pipeline deals with splitting work into a sequence of different computations, one after the other.

In this chapter, you will see several working examples of worker pools and data pipelines. These patterns naturally come up as solutions to many problems, and there is no single best solution. I try to separate the concurrency concerns from the computation logic. If you can do the same for your problems, you can iteratively find the best solution for your use case.

The topics that this chapter will cover are as follows:

  • Worker pools, using a file scanner example
  • Data pipelines, using a CSV file processor example