July 28, 1999 to July 30, 1999
Paul M. Aoki , University of California at Berkeley
The object-relational database management system (ORDBMS) offers many potential benefits for scientific, multimedia and financial applications. However, work remains in the integration of domain-specific class libraries into ORDBMS query processing. A major problem is that the standard mechanisms for query selectivity estimation, taken from relational database systems, rely on properties specific to the standard data types; creation of new mechanisms remains extremely difficult because the software interfaces provided by vendors are relatively low-level. In this paper, we discuss extensions of the generalized search tree, or GiST, to support a higher-level but less type-specific approach. Specifically, we discuss the computation of selectivity estimates with confidence intervals using a variety of index-based approaches and present results from an experimental comparison of these methods with several estimators from the literature.
selectivity estimation, query optimization, extensible databases, generalized search tree
Paul M. Aoki, "How to Avoid Building DataBlades(r) That Know the Value of Everything and the Cost of Nothing", SSDBM, 1999, Scientific and Statistical Database Management, International Conference on, Scientific and Statistical Database Management, International Conference on 1999, pp. 122, doi:10.1109/SSDM.1999.787627