Title :
Algorithms for index-assisted selectivity estimation
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA
Abstract :
The standard mechanisms for query selectivity estimation used in relational database systems rely on properties that are specific to the attribute types. The query optimizer in an extensible database system is, in general, unable to exploit these mechanisms for user-defined types, forcing the database extender to invent new estimation mechanisms. In this paper, we discuss extensions to the generalized search tree (GiST) that simplify the creation of user-defined selectivity estimation methods. An experimental comparison of such methods with multidimensional estimators from the literature has demonstrated very competitive results
Keywords :
abstract data types; database indexing; query processing; relational databases; tree searching; GiST; attribute type-specific properties; database extension; extensible database system; generalized search tree; index-assisted query selectivity estimation algorithms; multidimensional estimators; query optimizer; relational database systems; user-defined selectivity estimation methods; user-defined types; Computer vision; Costs; Database systems; Fractals; Multidimensional systems; NASA; Partitioning algorithms; Query processing; Sampling methods; Statistics;
Conference_Titel :
Data Engineering, 1999. Proceedings., 15th International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7695-0071-4
DOI :
10.1109/ICDE.1999.754938
