Finding frequent items in data streams

Moses Charikar, Martin Farach-Colton

Research output: Chapter in Book/Report/Conference proceedingConference contribution

421 Scopus citations

Abstract

We present a 1-pass algorithm for estimating the most frequent items in a data stream using very limited storage space. Our method relies on a novel data structure called a count sketch, which allows us to estimate the frequencies of all the items in the stream. Our algorithm achieves better space bounds than the previous best known algorithms for this problem for many natural distributions on the item frequencies. In addition, our algorithm leads directly to a 2-pass algorithm for the problem of estimating the items with the largest (absolute) change in frequency between two data streams. To our knowledge, this problem has not been previously studied in the literature.

Original languageAmerican English
Title of host publicationAutomata, Languages and Programming - 29th International Colloquium, ICALP 2002, Proceedings
EditorsPeter Widmayer, Stephan Eidenbenz, Francisco Triguero, Rafael Morales, Ricardo Conejo, Matthew Hennessy
PublisherSpringer Verlag
Pages693-703
Number of pages11
ISBN (Print)3540438645, 9783540438649
DOIs
StatePublished - 2002
Externally publishedYes
Event29th International Colloquium on Automata, Languages, and Programming, ICALP 2002 - Malaga, Spain
Duration: Jul 8 2002Jul 13 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2380 LNCS

Other

Other29th International Colloquium on Automata, Languages, and Programming, ICALP 2002
Country/TerritorySpain
CityMalaga
Period7/8/027/13/02

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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