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Optimal Update Policies for Distributed Materialized Views

Author

Listed:
  • Arie Segev

    (Walter A. Haas School of Business, University of California at Berkeley, Berkeley, California 94720 and Information & Computing Sciences Division, Lawrence Berkeley Laboratory, Berkeley, California 94720)

  • Weiping Fang

    (Industrial Engineering & Operations Research Department, University of California at Berkeley, Berkeley, California 94720 and Information & Computing Sciences Division, Lawrence Berkeley Laboratory, Berkeley, California 94720)

Abstract

In this paper we present an analysis of the problem of determining optimal policies for updating distributed materialized views. We demonstrate the general application of materialized views, and define the concept of materialized view currency and allow a query to specify its currency requirement. We also allow a materialized view to be updated from either a base relation or another materialized view. This flexibility provides an opportunity for further reduction in the cost of maintaining distributed materialized views. We model the problem of optimal update policies to capture currency and policy constraints, replicated data, and various view update policies. The optimization incorporates a minimum-cost objective function as well as user's response time constraints.

Suggested Citation

  • Arie Segev & Weiping Fang, 1991. "Optimal Update Policies for Distributed Materialized Views," Management Science, INFORMS, vol. 37(7), pages 851-870, July.
    • Handle: RePEc:inm:ormnsc:v:37:y:1991:i:7:p:851-870
    DOI: 10.1287/mnsc.37.7.851
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    Cited by:

    1. Xiao Fang & Olivia R. Liu Sheng & Paulo Goes, 2013. "When Is the Right Time to Refresh Knowledge Discovered from Data?," Operations Research, INFORMS, vol. 61(1), pages 32-44, February.
    2. Anindya Datta & Igor R. Viguier, 2000. "Handling Sensor Data in Rapidly Changing Environments to Support Soft Real-Time Requirements," INFORMS Journal on Computing, INFORMS, vol. 12(2), pages 84-103, May.

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