A technical book about popular space-efficient data structures and fast algorithms that are extremely useful in modern Big Data applications. The purpose of this book is to introduce technology practitioners, including software architects and developers, as well as technology decision makers to probabilistic data structures and algorithms. Reading this book, you will get a theoretical and practical understanding of probabilistic data structures and learn about their common uses.

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The purpose of this book is to introduce technology practitioners which includes software architects and developers, as well as technology decision makers to probabilistic data structures and algorithms.

While it is impossible to cover all the existing amazing solutions, this book is to highlight their common ideas and important areas of application, including membership querying, counting, stream mining, and similarity estimation.

This is not a book for scientists only, but to gain the most out of it you will need to have basic mathematical knowledge and an understanding of the general theory of data structures and algorithms.

Writing this book was an incredible experience! I hope it lets you a better understanding of Big Data applications and inspires to explore other problems and develop new amazing solutions.

"About this title" may belong to another edition of this title.

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Probabilistic Data Structures and Algorithms for Big Data Applications

Gakhov, Andrii

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