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.
Epub (Kobo), Epub (Adobe)
Publication Date: 30/09/2020
- ISBN:
- 9781108807043
- 9781108807043
- Category:
- Databases
- Format:
- Epub (Kobo), Epub (Adobe)
- Publication Date:
- 30-09-2020
- Language:
- English
- Publisher:
- Cambridge University Press
This item is delivered digitally
Great!
Click on Save to My Library / Lists
Click on Save to My Library / Lists
Select the List you'd like to categorise as, or add your own
Here you can mark if you have read this book, reading it or want to read
Awesome! You added your first item into your Library
Great! The fun begins.
Click on My Library / My Lists and I will take you there
Click on My Library / My Lists and I will take you there
Reviews
Be the first to review Small Summaries for Big Data.
Share This eBook: