Understanding Compression Data Compression for Modern Developers 1st Edition by Colt McAnlis , Aleks Haecky ISBN 1491961538 978-1491961537

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Product details: 

ISBN 10: 1491961538 

ISBN 13: 978-1491961537

Author: Colt McAnlis , Aleks Haecky

If you want to attract and retain users in the booming mobile services market, you need a quick-loading app that won’t churn through their data plans. The key is to compress multimedia and other data into smaller files, but finding the right method is tricky. This witty book helps you understand how data compression algorithms work—in theory and practice—so you can choose the best solution among all the available compression tools.

With tables, diagrams, games, and as little math as possible, authors Colt McAnlis and Aleks Haecky neatly explain the fundamentals. Learn how compressed files are better, cheaper, and faster to distribute and consume, and how they’ll give you a competitive edge.

• Learn why compression has become crucial as data production continues to skyrocket
• Know your data, circumstances, and algorithm options when choosing compression tools
• Explore variable-length codes, statistical compression, arithmetic numerical coding, dictionary encodings, and context modeling
• Examine tradeoffs between file size and quality when choosing image compressors
• Learn ways to compress client- and server-generated data objects
• Meet the inventors and visionaries who created data compression algorithms

Table of contents: 

1 Let’s Not Be Boring 1

The Five Buckets of Compression Algorithms 1

Claude Shannon Is Infuriating! 2

The Only Thing You Need to Know about Data Compression 3

A World Built on Data Compression 4

2 Do Not Skip This Chapter 9

Understanding Binary 9

Base 10 System 9

Binary Number System 10

Information Theory 13

An Excursion into Binary Search 14

Entropy: The Minimum Bits Needed to Represent a Number 16

Standard Number Lengths 17

3 Breaking Entropy 19

Understanding Entropy 19

What This Entropy Stuff Is Good For 21

Understanding Probability 22

Breaking Entropy 23

Example 1 Delta Coding 24

Example 2 Symbol Grouping 25

Example 3 Permutations 26

4 Variable-Length Codes 33

Morse Code 33

Probability, Entropy, and Codeword Size 36

Variable-Length Codes 38

Using VLCs 38

Creating VLCs 42

A Handful of Example VLCs 44

Finding the Right Code for Your Data Set 51

5 Statistical Encoding 53

Statistically Compressing to Entropy 53

Huffman Coding 55

Building a Huffman Tree 55

Generating Codewords 57

Encoding and Decoding 58

Practical Implementations 58

Arithmetic Coding 60

Finding the Right Number 61

Encoding 62

Picking the Right Output Value 64

Decoding 64

Practical Implementations 69

Asymmetric Numeral Systems 69

Encoding and Decoding Using a Transform Table 70

Creating the Reference Table 71

Using ANS for Compression 74

Decoding Example 75

So Where Does the Compression Come From? 76

Practical Compression: Which Statistical Algorithm Do I Choose? 77

6 Adaptive Statistical Encoding 79

Locality Matters for Entropy 79

Adaptive VLC Encoding 81

Dynamically Building a VLC Table 81

Literals 84

Resets 87

Knowing When to Reset 88

Using This in Practice 89

Adaptive Arithmetic Coding 89

Adaptive Huffman Coding 90

7 Dictionary Transforms 93

A Basic Dictionary Transform 94

Finding the Right “Words” 95

The Lempel-Ziv Algorithm 98

How LZ Works 99

Encoding 104

Decoding 105

Compressing LZ output 106

LZ Variants 107

Collect Them All! 110

8 Contextual Data Transforms 111

Run-Length Encoding 112

Dealing with Short Runs 112

Compressing 114

Delta Coding 116

XOR Delta Coding 118

Frame of Reference Delta Coding 119

Patched Frame of Reference Delta Coding 120

Compressing Delta-Encoded Data 123

Does It Work on Text? 123

Move-to-Front Coding 123

Avoiding Rogue Symbols 125

Compressing MTF 126

Bur rows-Wheeler Transform 126

Ordering Is Important! 128

How BWT Works 128

Inverse BWT 130

Practical Implementations 132

Compressing BWT 133

9 Data Modeling 135

The Chains of Markov 136

Markov and Compression 139

Practical Implementations 145

Prediction by Partial Matching 145

The Search Trie 147

Compressing a Symbol 149

Choosing a Sensible N Value 150

Dealing with Unknown Symbols 150

Context Mixing 150

Types of Models 151

Types of Mixing 153

The Next Big Thing? 154

10 Switching Gears 155

Media-Specific Compression 155

General-Purpose Compression 156

Compression in Practice 157

11 Evaluating Compression 159

Compression Usage Scenarios 159

Compressed Offline, Decompressed On-Client 159

Compressed On-Client, Decompressed In-Cloud 160

Compressed In-Cloud, Decompressed On-Client 160

Compressed On-Client, Decompressed On-Client 161

Compression Need 161

Compression Ratio 162

Compression Performance 163

Decompression Performance 164

Ability to Decode-Stream 164

Comparing Compressors 165

12 Compressing Image Data Types 167

Understanding Quality Versus File Size 167

What Reduces Image Quality? 169

Measuring Image Quality 171

Making This Work 173

Image Dimensions Are Important 173

Choosing the Correct Image Format 175

PNG 175

JPG 176

GIF 177

WebP 177

And Now for Choosing 177

GPU Texture Formats 179

Vector Formats 180

Eyes on the Prize 182

13 Serialized Data 183

Understanding Common Use Cases 184

Dynamically Server-Built Data 184

Statically Built Server-Owned Data 184

Dynamically Client-Built Data 184

Statically Client-Owned Data 184

Issues with Serialized Formats 185

Human-Readable Text 185

Slow Decode Times 186

Smaller Serialized Data 186

Use a Binary Serialization Format 186

Restructure Lists for Better Compression 187

Organize for Efficient Fetching 189

Segment Out Data into the Proper Compression Format 191

14 Lossy Data Compression 193

15 Making the World a Little Smaller 195

Data Compression and You 195

Data Compression and the Bottom Line 195

User Acquisition and Retention 195

Running Costs 196

Planning Ahead 197

Making Your Users’ Lives a Little More Magical and Less Expensive 197

Thinking About What’s Next in Technology 198

The Next Five Billion Users 198

Mobile Networks 198

…Starting Now 199

Glossary of Compression Words 201

Index 209

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Tags: Colt McAnlis, Aleks Haecky, Understanding Compression, Data Compression