Efficient execution of parallel aggregate data cube queries in data warehouse environments

Rebecca Boon-Noi Tan, David Taniar, Guojun Lu

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

    3 Citations (Scopus)

    Abstract

    With the increasing emphasis on data warehouse systems, the efficiency of complex analytical queries in such systems has become an important issue. Such queries posed challenging performance problems that initiated the use of parallel database systems and parallel algorithms in data warehouse environments. Many of these have been proposed in recent years but a review of the literature to our knowledge has not revealed any literature describing parallel methods with detailed cost models for aggregate data cube queries in a data warehouse environment. This paper presents a detailed cost model based on parallel methods for aggregate data cube queries. The detailed cost model enables us to study the behaviour and evaluate the performance of the three methods and thus identify the efficient parallel methods for aggregate data cube queries.
    Original languageEnglish
    Title of host publicationProceedings of the 4th International Conference in Intelligent Data Engineering and Automated Learning (IDEAL 2003)
    EditorsJiming Liu, Yiuming Cheung, Hujun Yin
    Place of PublicationGermany
    PublisherSpringer-Verlag London Ltd.
    Pages709 - 716
    Number of pages8
    Volume2690
    ISBN (Print)0302-9743
    Publication statusPublished - 2003
    EventInternational Conference on Intelligent Data Engineering and Automated Learning - Hong Kong China, New York USA
    Duration: 1 Jan 2003 → …

    Conference

    ConferenceInternational Conference on Intelligent Data Engineering and Automated Learning
    CityNew York USA
    Period1/01/03 → …

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