 Название: Algorithms For Big Data
Автор: Moran Feldman
Издательство: World Scientific Publishing
Год: 2020
Страниц: 458
Язык: английский
Формат: pdf (true)
Размер: 19.4 MB
This unique volume is an introduction for computer scientists, including a formal study of theoretical algorithms for Big Data applications, which allows them to work on such algorithms in the future. It also serves as a useful reference guide for the general computer science population, providing a comprehensive overview of the fascinating world of such algorithms.To achieve these goals, the algorithmic results presented have been carefully chosen so that they demonstrate the important techniques and tools used in Big Data algorithms, and yet do not require tedious calculations or a very deep mathematical background.
Contents:
Preface
About the Author
Part I: Data Stream Algorithms
Chapter 1. Introduction to Data Stream Algorithms Chapter 2. Basic Probability and Tail Bounds 15
Chapter 3. Estimation Algorithms 51
Chapter 4. Reservoir Sampling 73
Chapter 5. Pairwise Independent Hashing 93
Chapter 6. Counting Distinct Tokens 109
Chapter 7. Sketches 133
Chapter 8. Graph Data Stream Algorithms 165
Chapter 9. The Sliding Window Model 197
Part II: Sublinear Time Algorithms
Chapter 10. Introduction to Sublinear Time Algorithms 227
Chapter 11. Property Testing 237
Chapter 12. Algorithms for Bounded Degree Graphs 267
Chapter 13. An Algorithm for Dense Graphs 309
Chapter 14. Algorithms for Boolean Functions 331
Part III: Map-Reduce
Chapter 15. Introduction to Map-Reduce 355
Chapter 16. Algorithms for Lists 377
Chapter 17. Graph Algorithms 401
Chapter 18. Locality-Sensitive Hashing 425
Index 443
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