Flow algorithms for two pipelined filter ordering problems

Anne Condon, Amol Deshpande, Lisa Hellerstein, Ning Wu

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

    Abstract

    Pipelined filter ordering is a central problem in database query optimization, and has received renewed attention recently in the context of environments such as the web, continuous high-speed data streams and sensor networks. We present algorithms for two natural extensions of the classical pipelined filter ordering problem: (1) a distributional type problem where the filters run in parallel and the goal is to maximize throughput, and (2) an adversarial type problem where the goal is to minimize the expected value of multiplicative regret. We show that both problems can be solved using similar flow algorithms, which find an optimal ordering scheme in time O(n2), where n is the number of filters. Our algorithm for (1) improves on an earlier O(n3 log n) algorithm of Kodialam.

    Original languageEnglish (US)
    Title of host publicationProceedings of the Twenty-Fifth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS 2006
    Pages193-202
    Number of pages10
    DOIs
    StatePublished - 2006
    Event25th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS 2006 - Chicago, IL, United States
    Duration: Jun 26 2006Jun 28 2006

    Publication series

    NameProceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems

    Other

    Other25th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS 2006
    Country/TerritoryUnited States
    CityChicago, IL
    Period6/26/066/28/06

    Keywords

    • Flow algorithms
    • Pipelined filter ordering
    • Query optimization
    • Selection ordering

    ASJC Scopus subject areas

    • Software
    • Information Systems
    • Hardware and Architecture

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