Cost modeling of spatial operators using non-parametric regression |
| |
Authors: | Songtao Jiang Zhen He |
| |
Affiliation: | a Department of Computer Science, University of Vermont, Room 323 Votey Building, Burlington, VT 05405, USA b Department of Computer Science, La Trobe University, Bundoora ,Vic. 3086, Australia |
| |
Abstract: | In an object-relational database management system, a query optimizer requires users to provide cost models of user-defined functions. The traditional approach is analytical, that is, it builds a cost model generated as a result of analyzing the query processing steps. This analytical approach is difficult, however, especially for spatial query operators because of the complexity of the processing steps. In this paper, a new approach that uses non-parametric regression is proposed. This approach significantly simplifies the process of building a cost model, while achieving highly accurate cost estimation. We demonstrate the simplicity and efficacy of this approach through experiments for three spatial operators—the range query, the window query, and the k-nearest neighbor query—commonly used in spatial databases, using both real and synthetic data sets. |
| |
Keywords: | Cost model Non-parametric regression Spatial database Spatial operator |
本文献已被 ScienceDirect 等数据库收录! |
|