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:
Dec. 15, 2015
Filed:
Oct. 11, 2007
Mihnea Andrei, Issy les Moulineaux, FR;
Xun Cheng, Dublin, CA (US);
Edwin Anthony Seputis, Oakland, CA (US);
Xiao Ming Zhou, Singapore, SG;
Mihnea Andrei, Issy les Moulineaux, FR;
Xun Cheng, Dublin, CA (US);
Edwin Anthony Seputis, Oakland, CA (US);
Xiao Ming Zhou, Singapore, SG;
Sybase, Inc., Dublin, CA (US);
Abstract
System and methodology for automatic tuning of database query optimizer is described. In one embodiment, in a database system having an optimizer for selecting a query plan for executing a database query, a method of the present invention is described for automatically tuning query performance to prevent query performance regression that may occur during upgrade of the database system from a prior version to a new version, the method comprises steps of: in response to receiving a given database query for execution, specifying a query plan generated by the prior version's optimizer as a baseline best plan for executing the given database query; generating at least one new query plan using the new version's optimizer; learning performance for each new query plan generated by recording corresponding query execution metrics; if a given new query plan is observed to have better performance than the best plan previously specified, specifying that given new query plan to be the best plan for executing the given database query; if a given new query plan is observed to have worse performance than the best plan previously specified, specifying that given new query plan to be a bad plan to be avoided in the future; and automatically tuning future execution of the given database query by using the query plan that the system learned was the best plan.