Workload-aware data placement advisor for OLAP database systems
US12229135B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 21, 2022 |
| Grant date | Feb 18, 2025 |
| Priority date | — |
| Expiry date | Jun 26, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/278
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments implement a prediction-driven, rather than a trial-driven, approach to automatic data placement recommendations for partitioning data across multiple nodes in a database system. The system is configured to extract workload-specific features of a database workload running at a database system and dataset-specific features of a database running on the database system. The workload-specific features characterize utilization of the database workload. The dataset-specific features characterize how data is organized within the database. The system identifies a plurality of candidate keys for determining how to partition data stored in the database across nodes. Based at least in part on the workload-specific features, the dataset specific features, and the plurality of candidate keys, a set of candidate key combinations for partitioning data is generated. Using a machine learning model, determine a particular candidate key combination that optimizes query execution performance benefit based on the workload-specific features and the dataset specific features. Generate data placement commands to allocate the database tables across the nodes.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.