Bottom-k sketches: Better and more efficient estimation of aggregates

Edith Cohen*, Haim Kaplan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A Bottom-k sketch is a summary of a set of items with nonnegative weights. Each such summary allows us to compute approximate aggregates over the set of items. Bottom-k sketches are obtained by associating with each item in a ground set an independent random rank drawn from a probability distribution that depends on the weight of the item. For each subset of interest, the bottom-k sketch is the set of the k minimum ranked items and their ranks. Bottom-k sketches have numerous applications. We develop and analyze data structures and estimators for bottom-k sketches to facilitate their deployment. We develop novel estimators and algorithms that show that they are a superior alternative to other sketching methods in both efficiency of obtaining the sketches and the accuracy of the estimates derived from the sketches.

Original languageEnglish
Title of host publicationSIGMETRICS'07 - Proceedings of the 2007 International Conference on Measurement and Modeling of Computer Systems
Pages353-354
Number of pages2
Edition1
DOIs
StatePublished - 2007
EventSIGMETRICS'07 - 2007 International Conference on Measurement and Modeling of Computer Systems - San Diego, CA, United States
Duration: 12 Jun 200716 Jun 2007

Publication series

NamePerformance Evaluation Review
Number1
Volume35
ISSN (Print)0163-5999

Conference

ConferenceSIGMETRICS'07 - 2007 International Conference on Measurement and Modeling of Computer Systems
Country/TerritoryUnited States
CitySan Diego, CA
Period12/06/0716/06/07

Keywords

  • Approximate query processing
  • Bottom-k
  • Sketches

Fingerprint

Dive into the research topics of 'Bottom-k sketches: Better and more efficient estimation of aggregates'. Together they form a unique fingerprint.

Cite this