Evolving materialized views in data warehouse

Author

Zhang, Chuan ; Yao, Xin ; Yang, Jian

Author_Institution

Sch. of Comput. Sci., New South Wales Univ., Canberra, ACT, Australia

Volume

2

fYear

1999

fDate

1999

Abstract

A data warehouse contains multiple views accessed by queries. One of the most important decisions in designing a data warehouse is the selection of materialized views for the purpose of efficiently implementing decision making. The search space for the selection of materialized views is exponentially large, therefore, heuristics have been used to search a small fraction of the space to get a near optimal solution. In this paper, we explore the use of a genetic algorithm for the selection of materialized views based on multiple global processing plans for many queries. Our experimental studies indicate that the genetic algorithm delivers better solutions than some heuristics

Keywords

data warehouses; genetic algorithms; heuristic programming; query processing; search problems; data warehouse; decision making; genetic algorithm; heuristics; materialized view evolution; materialized view selection; multiple global processing plans; near optimal solution; queries; search space; Algorithm design and analysis; Australia; Computer science; Costs; Data models; Data warehouses; Distributed databases; Genetic algorithms; Information analysis; Multidimensional systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on

Conference_Location

Washington, DC

Print_ISBN

0-7803-5536-9

Type

conf

DOI

10.1109/CEC.1999.782507

Filename

782507