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Hands-On JavaScript High Performance

You're reading from   Hands-On JavaScript High Performance Build faster web apps using Node.js, Svelte.js, and WebAssembly

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781838821098
Length 376 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Justin Scherer Justin Scherer
Author Profile Icon Justin Scherer
Justin Scherer
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Table of Contents (15) Chapters Close

Preface 1. Tools for High Performance on the Web 2. Immutability versus Mutability - The Balance between Safety and Speed FREE CHAPTER 3. Vanilla Land - Looking at the Modern Web 4. Practical Example - A Look at Svelte and Being Vanilla 5. Switching Contexts - No DOM, Different Vanilla 6. Message Passing - Learning about the Different Types 7. Streams - Understanding Streams and Non-Blocking I/O 8. Data Formats - Looking at Different Data Types Other Than JSON 9. Practical Example - Building a Static Server 10. Workers - Learning about Dedicated and Shared Workers 11. Service Workers - Caching and Making Things Faster 12. Building and Deploying a Full Web Application 13. WebAssembly - A Brief Look into Native Code on the Web 14. Other Books You May Enjoy

Getting started with streams

Streaming is the act of working on an infinite dataset. This does not mean that it is, but it means that we have the possibility of having an unlimited data source. If we think in the traditional context of processing data, we usually run through three main steps:

  1. Open/get access to a data source.
  2. Process the data source once it is fully loaded in.
  3. Spit out computed data to another location.

We can think of this as the basics of input and output (I/O). Most of our concepts of I/O involve batch processing or working on all or almost all of the data. This means that we know the limits of that data ahead of time. We can make sure that we have enough memory, storage space, computing power, and so on, to deal with the process. Once we are done with the process, we kill the program or queue up the next batch of data.

A simple example of this is seen as...

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