Automatically classifying database workloads

Said Elnaffar, Pat Martin, Randy Horman

    Research output: Contribution to conferencePaperpeer-review

    35 Citations (Scopus)

    Abstract

    The type of the workload on a database management system (DBMS) is a key consideration in tuning the system. Allocations for resources such as main memory can be very different depending on whether the workload type is Online Transaction Processing (OLTP) or Decision Support System (DSS). In this paper, we present an approach to automatically identifying a DBMS workload as either OLTP or DSS. We build a classification model based on the most significant workload characteristics that differentiate OLTP from DSS, and then use the model to identify any change in the workload type. We construct a workload classifier from the Browsing and Ordering profiles of the TPC-W benchmark. Experiments with an industry-supplied workload show that our classifier accurately identifies the mix of OLTP and DSS work within an application workload.

    Original languageEnglish
    Pages622-624
    Number of pages3
    DOIs
    Publication statusPublished - 2002
    EventProceedings of the Eleventh International Conference on Information and Knowledge Management (CIKM 2002) - McLean, VA, United States
    Duration: Nov 4 2002Nov 9 2002

    Other

    OtherProceedings of the Eleventh International Conference on Information and Knowledge Management (CIKM 2002)
    Country/TerritoryUnited States
    CityMcLean, VA
    Period11/4/0211/9/02

    Keywords

    • Autonomic databases,
    • Classification
    • DSS
    • Data mining
    • OLTP
    • Self-managed DBMSs
    • Workload characterization

    ASJC Scopus subject areas

    • Decision Sciences(all)
    • Business, Management and Accounting(all)

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