You don't need to own a Kindle device to enjoy Kindle books. Download one of our FREE Kindle apps to start reading Kindle books on all your devices.

  • Apple
  • Android
  • Windows Phone
    Windows Phone
  • Click here to download from Amazon appstore

To get the free app, enter your mobile phone number.


Buying Options

Read this title for $0.00. Learn more
Read for $0.00
Kindle Price: $27.65
includes tax, if applicable

These promotions will be applied to this item:

Some promotions may be combined; others are not eligible to be combined with other offers. For details, please see the Terms & Conditions associated with these promotions.

Deliver to your Kindle or other device

Deliver to your Kindle or other device

Probabilistic Data Structures and Algorithms for Big Data Applications by [Gakhov, Andrii]

Probabilistic Data Structures and Algorithms for Big Data Applications [Print Replica] Kindle Edition

See all 2 formats and editions Hide other formats and editions
Amazon Price
New from Used from

Browse our most popular books based on sales
Find your next great read. Shop best selling books

Product description

Product Description

A technical book about popular space-efficient data structures and fast algorithms that are extremely useful in modern Big Data applications.

Probabilistic data structures is a common name for data structures based mostly on different hashing techniques. Unlike regular (or deterministic) data structures, they always provide approximated answers but with reliable ways to estimate possible errors. Fortunately, the potential losses and errors are fully compensated for by extremely low memory requirements, constant query time, and scaling, the three factors that become essential in Big Data applications.

About the book

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.

What you will learn

Reading the book, you will get a theoretical and practical understanding of probabilistic data structures and learn about their common uses.

  • Learn how to solve practical issues of massive data handling
  • Master the theoretical aspects of probabilistic data structures
  • Identify the right data structures for your particular problems

What's inside?

This book consists of six chapters, each preceded by an introduction and followed by a brief summary and bibliography for further reading relating to that chapter. Every chapter is dedicated to one particular problem in Big Data applications, it starts with an in-depth explanation of the problem and follows by introducing data structures and algorithms that can be used to solve it efficiently.

  1. Hashing
  2. Membership
  3. Cardinality
  4. Frequency
  5. Rank
  6. Similarity

This book on the Web

You can find errata, examples, and additional information at If you have a comment, technical question about the book, would like to report an error you found, or any other issue, send email to

In case you are also interested in Cython implementation that includes many of the data structures and algorithms from this book, please check out our free and open-source Python library called PDSA at Everybody is welcome to contribute at any time.

Product details

  • Format: Kindle Edition
  • File Size: 10712 KB
  • Print Length: 220 pages
  • Simultaneous Device Usage: Unlimited
  • Publisher: gakhov; 1 edition (18 February 2019)
  • Sold by: Amazon Australia Services, Inc.
  • Language: English
  • Text-to-Speech: Not enabled
  • X-Ray:
  • Word Wise: Not Enabled
  • Enhanced Typesetting: Not Enabled
  • Average Customer Review: Be the first to review this item
click to open popover

No customer reviews

Review this product

Share your thoughts with other customers