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Counting Distinct Elements in a Data Stream

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Randomization and Approximation Techniques in Computer Science (RANDOM 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2483))

Abstract

We present three algorithms to count the number of distinct elements in a data stream to within a factor of 1 ±ε. Our algorithms improve upon known algorithms for this problem, and offer a spectrum of time/space tradeoffs.

Part of this work was done while the author was visiting IBM Almaden Research Center. Supported by NSF Grant CCR-9820897.

Work supported by a Sloan Research Fellowship and an NSF Career Award.

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Author information

Authors and Affiliations

  1. Computer Science Division, Univ. of California at Berkeley, Berkeley, CA, 94720

    Ziv Bar-Yossef

  2. IBM Almaden Research Center, 650 Harry Road, San Jose, CA, 95120

    T. S. Jayram, Ravi Kumar & D. Sivakumar

  3. Computer Science Division, Univ. of California at Berkeley, Berkeley, CA, 94720

    Luca Trevisan

Authors
  1. Ziv Bar-Yossef
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  2. T. S. Jayram
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  3. Ravi Kumar
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  4. D. Sivakumar
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  5. Luca Trevisan
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Editor information

Editors and Affiliations

  1. Centre Universitaire d’Informatique, University of Geneva, 24, Rue Général Dufour, 1211, Genéve 4, Switzerland

    José D. P. Rolim

  2. Harvard University, DEAS, Maxwell Dworkin 337, 33 Oxford Street, Cambridge, MA, 02138, USA

    Salil Vadhan

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© 2002 Springer-Verlag Berlin Heidelberg

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Bar-Yossef, Z., Jayram, T.S., Kumar, R., Sivakumar, D., Trevisan, L. (2002). Counting Distinct Elements in a Data Stream. In: Rolim, J.D.P., Vadhan, S. (eds) Randomization and Approximation Techniques in Computer Science. RANDOM 2002. Lecture Notes in Computer Science, vol 2483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45726-7_1

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  • DOI: https://doi.org/10.1007/3-540-45726-7_1

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44147-2

  • Online ISBN: 978-3-540-45726-8

  • eBook Packages: Springer Book Archive

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