Dynamically learning optimal cost profiles for heterogenous workloads
US11593371B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 18, 2020 |
| Grant date | Feb 28, 2023 |
| Priority date | — |
| Expiry date | Aug 20, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F17/16
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A relational database management system (RDBMS) accepts a workload comprised of one or more queries against a relational database. The RDBMS evolves a default cost profile into a plurality of cost profiles using fixed or dynamic evolution, wherein each of the cost profiles captures one or more cost parameters for the workload. The cost profiles are represented by a multi-dimensional matrix that has one or more dimensions, and each of the dimensions represents one of the cost parameters. The RDBMS dynamically determines which of the cost profiles is an optimal cost profile for the workload by mapping the cost profiles to the workload using a random walk scoring algorithm or a biased walk scoring algorithm that searches the multi-dimensional matrix to identify the optimal cost profile. The RDBMS selects and performs one or more query execution plans for the workload based on the optimal cost profile for the workload.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.