Self tuning database retrieval optimization using regression...

Details Self tuning database retrieval optimization using regression... Self tuning database retrieval optimization using regression...

2006-11-14

2006-11-14

Alam, Shahid (Department: 2162)

Data processing: database and file management or data structures

Database design

Data structure types

C707S793000, C707S793000, C707S793000

Reexamination Certificate

active

07136850

ABSTRACT:
A system and method for accessing a relational database and estimating the selectivity of a query (e.g., an SQL query) in order to better predict the number of qualifying records for simple and complex queries. A dataset is created based upon queries applied against the database by the user community. The dataset is populated with information related to query conditions and their respective combinations. A regression function reflecting correlations between query conditions is generated and used as a data mining model to calculate table-specific estimates for the cardinality of subsequent queries. An appropriate access method is then selected from a set of available access methods based upon the number of estimated query-qualifying records. By periodically updating the regression model with FIFO managed queries, a self-tuning mechanism is achieved resulting in better selectivity/result size estimates for use in selecting access methods used in compiling subsequent SQL queries applied against the database.

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Lise Getoor, et al.; “Selectively Estimation Using Probabilistic Models”; ACM SIGMOD 2001, May 21 24, Santa Barbara, California, 12 pages.

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