Physical database design and tuning with deep reinforcement learning
US11593334B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 27, 2019 |
| Grant date | Feb 28, 2023 |
| Priority date | — |
| Expiry date | Nov 16, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/092
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An apparatus, method and computer program product for physical database design and tuning in relational database management systems. A relational database management system executes in a computer system, wherein the relational database management system manages a relational database comprised of one or more tables storing data. A Deep Reinforcement Learning based feedback loop process also executes in the computer system for recommending one or more tuning actions for the physical database design and tuning of the relational database management system, wherein the Deep Reinforcement Learning based feedback loop process uses a neural network framework to select the tuning actions based on one or more query workloads performed by the relational database management system.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.