Database storage optimization method and system, electronic device and storage medium
By acquiring database instance information and utilizing machine learning prediction models, the database storage strategy is automatically optimized, solving the problems of high storage costs and low tuning efficiency in existing technologies, and achieving cost reduction and efficiency improvement.
Patent Information
- Application Number
- CN202310223086.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-03-03
- Publication Date
- 2026-07-07
- Estimated Expiration
- 2043-03-03
AI Technical Summary
Existing technologies such as solid-state drive hot storage and full indexing result in high storage costs and total cost of ownership in databases. Furthermore, it is difficult for database administrators to effectively identify unaccessed database table objects, leading to increased labor costs and low optimization efficiency.
By obtaining instance information of the database instance, the machine learning prediction model is used to predict the probability of future access to database table objects. Based on the prediction results, the expected optimization benefits are determined, and optimization suggestions are automatically output. These suggestions include moving unaccessed database table objects from hot storage to cold storage or deleting indexes, thus achieving automatic tuning.
It reduces storage costs, lowers total cost of ownership, improves tuning efficiency, saves on labor costs, and eliminates the need to rely on a database administrator.