Book Image

JavaScript Concurrency

By : Adam Boduch
Book Image

JavaScript Concurrency

By: Adam Boduch

Overview of this book

Concurrent programming may sound abstract and complex, but it helps to deliver a better user experience. With single threaded JavaScript, applications lack dynamism. This means that when JavaScript code is running, nothing else can happen. The DOM can’t update, which means the UI freezes. In a world where users expect speed and responsiveness – in all senses of the word – this is something no developer can afford. Fortunately, JavaScript has evolved to adopt concurrent capabilities – one of the reasons why it is still at the forefront of modern web development. This book helps you dive into concurrent JavaScript, and demonstrates how to apply its core principles and key techniques and tools to a range of complex development challenges. Built around the three core principles of concurrency – parallelism, synchronization, and conservation – you’ll learn everything you need to unlock a more efficient and dynamic JavaScript, to lay the foundations of even better user experiences. Throughout the book you’ll learn how to put these principles into action by using a range of development approaches. Covering everything from JavaScript promises, web workers, generators and functional programming techniques, everything you learn will have a real impact on the performance of your applications. You’ll also learn how to move between client and server, for a more frictionless and fully realized approach to development. With further guidance on concurrent programming with Node.js, JavaScript Concurrency is committed to making you a better web developer. The best developers know that great design is about more than the UI – with concurrency, you can be confident every your project will be expertly designed to guarantee its dynamism and power.
Table of Contents (17 chapters)
JavaScript Concurrency
About the Author
About the Reviewer

Candidate problems

In the previous section, you learned to create a generic function that will decide, on the fly, how to divide and conquer using workers, or whether it's more beneficial to simply call the function in the main thread. Now that we have a generic parallelization mechanism in place, what kind of problems can we solve? In this section, we'll address the most typical concurrency scenarios that will benefit from a solid concurrency architecture.

Embarrassingly parallel

A problem is embarrassingly parallel when it's obvious how the larger task can be broken down into smaller tasks. These smaller tasks don't depend on one another, which makes it even easier to start off a task that takes input and produces output without relying on the state of other workers. This again comes back to the functional programming, and the idea of referential transparency and no side-effects.

These are the types of problems we want to solve with concurrency—at least at first, during the difficult first...