Building regression cost models for multidatabase systems

Conference · Tue Dec 31 04:00:00 EST 1996

OSTI ID:535555

Zhu, Qiang ^[1]; Larson, P A ^[2]

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1. Univ. of Michigan, Dearborn, MI (United States)
2. Univ. of Waterloo (Canada)

A major challenge for performing global query optimization in a multidatabase system (MDBS) is the lack of cost models for local database systems at the global level. In this paper we present a statistical procedure based on multiple regression analysis for building cost models for local database systems in an MDBS. Explanatory variables that can be included in a regression model are identified and a mixed forward and backward method for selecting significant explanatory variables is presented. Measures for developing useful regression cost models, such as removing outliers, eliminating multicollinearity, validating regression model assumptions, and checking significance of regression models, are discussed. Experimental results demonstrate that the presented statistical procedure can develop useful local cost models in an MDBS.

• OSTI ID: 535555
• Report Number(s): CONF-961209--
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
ALGORITHMS
COST ESTIMATION
DATA BASE MANAGEMENT
INFORMATION RETRIEVAL
OPTIMIZATION
REGRESSION ANALYSIS