
Small Summaries for Big Data
Cambridge University Press
Published on 12. November 2020
Book
Hardback
278 pages
978-1-108-47744-4 (ISBN)
Description
The massive volume of data generated in modern applications can overwhelm our ability to conveniently transmit, store, and index it. For many scenarios, building a compact summary of a dataset that is vastly smaller enables flexibility and efficiency in a range of queries over the data, in exchange for some approximation. This comprehensive introduction to data summarization, aimed at practitioners and students, showcases the algorithms, their behavior, and the mathematical underpinnings of their operation. The coverage starts with simple sums and approximate counts, building to more advanced probabilistic structures such as the Bloom Filter, distinct value summaries, sketches, and quantile summaries. Summaries are described for specific types of data, such as geometric data, graphs, and vectors and matrices. The authors offer detailed descriptions of and pseudocode for key algorithms that have been incorporated in systems from companies such as Google, Apple, Microsoft, Netflix and Twitter.
Reviews / Votes
'A very thorough compendium of sketching and streaming algorithms, and an excellent resource for anyone interested in learning about them, understanding how they work and deploying them in applications. Good job!' Piotr Indyk, Massachusetts Institute of TechnologyMore details
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Illustrations
Worked examples or Exercises
Dimensions
Height: 234 mm
Width: 159 mm
Thickness: 19 mm
Weight
520 gr
ISBN-13
978-1-108-47744-4 (9781108477444)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Graham Cormode
Small Summaries for Big Data
E-Book
11/2020
Cambridge University Press
€41.99
Available for download

Graham Cormode | Ke Yi
Small Summaries for Big Data
E-Book
11/2020
Cambridge University Press
€44.99
Available for download
Persons
Graham Cormode is a Professor in Computer Science at the University of Warwick, doing research in data management, privacy and big data analysis. Previously, he was a principal member of technical staff at AT&T Labs-Research. His work has attracted more than 14,000 citations and has appeared in more than 100 conference papers, 40 journal papers, and been awarded 30 US Patents. Cormode is the co-recipient of the 2017 Adams Prize for Mathematics for his work on Statistical Analysis of Big Data. He has edited two books on applications of algorithms and co-authored a third.
Content
1. Introduction; 2. Summaries for sets; 3. Summaries for multisets; 4. Summaries for ordered data; 5. Geometric summaries; 6. Graph summaries; 7. Vector, matrix and linear algebraic summaries; 8. Summaries over distributed data; 9. Other uses of summaries; 10. Lower bounds for summaries.