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Mastering Reactive JavaScript

You're reading from   Mastering Reactive JavaScript Building asynchronous and high performing web apps with RxJS

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781786463388
Length 310 pages
Edition 1st Edition
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Author (1):
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Erich de Souza Oliveira Erich de Souza Oliveira
Author Profile Icon Erich de Souza Oliveira
Erich de Souza Oliveira
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Table of Contents (12) Chapters Close

Preface 1. What Does Being Reactive Mean? FREE CHAPTER 2. Reacting for the First Time 3. A World Full of Changes - Reactive Extensions to the Rescue 4. Transforming Data - Map, Filter, and Reduce 5. The World Changes Too Fast - Operators to Deal with Backpressure 6. Too Many Sources - Combining Observables 7. Something is Wrong - Testing and Dealing with Errors 8. More about Operators 9. Composition 10. A Real-Time Server 11. A Real-Time Client

What is backpressure?

When using functional reactive programming, we model our problems using streams of data or events (called observables), which can be transformed (using operators) and eventually will cause some effect (through an observer). Now imagine that we have an observable which emits data faster than our observer can process; this will lead to a problem called backpressure.

This problem can also happen when we want to keep an observable running at a certain pace. Imagine that you want to log in to the console all the tweets from a certain hashtag, but you want to log at most one each for a few seconds to make sure the user can read the tweets. This also can lead to backpressure if the hashtags have more tweets per second than a human is capable of reading.

Using RxJS, we have two possible strategies to deal with this problem.

We can discard some data. You might not be interested in all the movements...

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