Finding an efficient rewriting of OLAP queries using materialized views in data warehouses

  • Authors:

  • Chang-Sup Park;Myoung Ho Kim;Yoon-Joon Lee

  • Affiliations:

  • Department of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology, 373-1 Kusung-dong, Yusung-gu, Taejon, 305-701, South Korea;Department of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology, 373-1 Kusung-dong, Yusung-gu, Taejon, 305-701, South Korea;Department of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology, 373-1 Kusung-dong, Yusung-gu, Taejon, 305-701, South Korea

  • Venue:
  • Decision Support Systems
  • Year:
  • 2002

Quantified Score

Hi-index 0.00

Visualization

Abstract

OLAP queries involve a lot of aggregations on a large amount of data in data warehouses. To process expensive OLAP queries efficiently, we propose a new method to rewrite a given OLAP query using various kinds of materialized views which already exist in data warehouses. We first define the normal forms of OLAP queries and materialized views based on the selection and aggregation granularities, which are derived from the lattice of dimension hierarchies. Conditions for usability of materialized views in rewriting a given query are specified by relationships between the components of their normal forms. We present a rewriting algorithm for OLAP queries that can effectively utilize materialized views having different selection granularities, selection regions, and aggregation granularities together. We also propose an algorithm to find a set of materialized views that results in a rewritten query which can be executed efficiently. We show the effectiveness and performance of the algorithm experimentally.