An evolutionary approach to materialized views selection in a data warehouse environment

Chuan Zhang*, Xin Yao, Jian Yang

*Corresponding author for this work

Research output: Contribution to journalArticle

109 Citations (Scopus)

Abstract

A data warehouse (DW) contains multiple views accessed by queries. One of the most important decisions in designing a DW is selecting views to materialize for the purpose of efficiently supporting decision making. The search space for possible materialized views is exponentially large. Therefore heuristics have been used to search for a near optimal solution. In this paper, we explore the use of an evolutionary algorithm for materialized view selection based on multiple global processing plans for queries. We apply a hybrid evolutionary algorithm to solve three related problems. The first is to optimize queries. The second is to choose the best global processing plan from multiple global processing plans. The third is to select materialized views from a given global processing plan. Our experiment shows that the hybrid evolutionary algorithm delivers better performance than either the evolutionary algorithm or heuristics used alone in terms of the minimal query and maintenance cost and the evaluation cost to obtain the minimal cost.

Original languageEnglish
Pages (from-to)282-294
Number of pages13
JournalIEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews
Volume31
Issue number3
DOIs
Publication statusPublished - Aug 2001
Externally publishedYes

Keywords

  • Data mining
  • Data warehousing
  • Evolutionary algorithms
  • Materialized view selection

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