The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jul. 17, 2001
Filed:
Sep. 28, 1998
Christopher M. Farrar, Los Gatos, CA (US);
Harry A. Leslie, Los Altos, CA (US);
Pedro Celis, Austin, TX (US);
Diana L. Shak, San Jose, CA (US);
Compaq Computers, Corporation, Houston, TX (US);
Abstract
The invention provides a mechanism for using statistics, in connection with various database query cost modeling techniques, to more accurately estimate the number of rows and UECs that will be produced by relational operators and predicates in database systems. The ability to accurately estimate the number of rows and UECs returned by a relational operator and/or a predicate is fundamental to computing the cost of a query execution plan. This, in turn, drives the optimizer's ability to select the query plan best suited for the desired performance goal. According to the present invention, histogram statistics are synthesized bottom up from the leaf nodes to the root node of a query tree. Given input statistics in the form of histograms for each operand of a relational operator or predicate, the present inventive method and apparatus merge the input statistics in a way that it simulates the effects of the run time operator on the actual data, so as to produce a predicted row count and UEC for each histogram interval representative of the data that actually will be produced by each such operator or predicate in the query tree. A database query optimizer may use these statistics to select and implement an optimal query plan.