dc.contributor.author | Hazelwood, Kim | |
dc.date.accessioned | 2015-11-12T18:38:23Z | |
dc.date.issued | 2003 | |
dc.identifier.citation | Hazelwood, Kim. 2003. Feedback-Directed Query Optimization. Harvard Computer Science Group Technical Report TR-03-03. | en_US |
dc.identifier.uri | http://nrs.harvard.edu/urn-3:HUL.InstRepos:23526055 | |
dc.description.abstract | Current database systems employ static heuristics for estimating the access time of a particular query. These heuristics are based on several parameters, such as relation size and number of tuples. Yet these parameters are only updated intermittently, and the heuristics themselves are hand-tuned. As trends in database systems aim toward self-tuning systems, we can apply the experience of the feedback-directed compiler world to provide robust, self-tuning query optimizers. This paper presents the design and evaluation of a feedback-directed query optimization infrastructure. Using trace-driven simulation, we conclude that dynamic feedback can be quite effective at improving the accuracy of a query optimizer, and adapting to predictable query overhead. | en_US |
dc.description.sponsorship | Engineering and Applied Sciences | en_US |
dc.language.iso | en_US | en_US |
dash.license | LAA | |
dc.title | Feedback-Directed Query Optimization | en_US |
dc.type | Research Paper or Report | en_US |
dc.description.version | Version of Record | en_US |
dc.date.available | 2015-11-12T18:38:23Z | |