Database Feature Upgrade Mechanism for Deprecated Statistics
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Solution Overview
Problem
Database systems face challenges in adopting new statistics gathering features due to hard-coded older techniques, requiring costly expert intervention to identify and update deprecated methods, and users may be unaware of performance issues caused by outdated statistics gathering practices.
Innovation Solution
An automatic detection and recommendation system that identifies deprecated statistics gathering commands, generates reports, and provides recommendations for upgrading to newer techniques, allowing for user-controlled or automated implementation of these changes, leveraging machine learning to learn from ongoing overrides and improve performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If older statistics gathering techniques are hard-coded into application code, then application stability is maintained, but adaptability to new database features deteriorates
Solution Approach 1:
The patent introduces an intermediary component (feature upgrade mechanism) that sits between the application code and the database system. This intermediary automatically detects new database features, analyzes compatibility, and applies upgrades without requiring direct modification of the hard-coded application code, thus maintaining stability while enabling adaptability.
Solution Approach 2:
The system implements self-service capabilities where the database management system automatically identifies new features, assesses their compatibility with existing application code, and applies appropriate upgrades autonomously or with minimal user intervention, eliminating the need for manual code review and modification.
2Manufacturing precision
If expert intervention is used to identify and update deprecated features, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The system performs self-diagnosis and self-upgrade by automatically scanning application code for deprecated features, analyzing compatibility requirements, and applying appropriate updates without requiring external expert intervention, thereby maintaining precision while reducing complexity.
Solution Approach 2:
The patent implements a feedback mechanism where the system continuously monitors the application codebase, detects usage of deprecated features, and automatically triggers upgrade processes. This closed-loop feedback system ensures accurate identification and updating of features without requiring manual expert analysis.
3Reliability
If manual code review and updates are performed, then reliability is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary analysis of application code to identify deprecated features before they cause problems. By proactively detecting and preparing upgrade plans in advance, the system ensures reliable updates are executed promptly when needed, reducing both time loss and maintaining reliability.
Solution Approach 2:
The automated system performs the entire code review and update process without manual intervention, significantly reducing the time required while maintaining or improving reliability through consistent, error-free automated analysis and application of updates.
4Productivity
If new statistics gathering features are added to database systems, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary upgrade mechanism that manages the complexity of multiple statistics gathering features by automatically detecting which new features are compatible with existing applications and applying them selectively, thus enabling productivity improvements without proportionally increasing system complexity.
Solution Approach 2:
The system dynamically adapts to new database features by continuously monitoring for updates, analyzing compatibility, and selectively applying upgrades. This dynamic approach allows the system to leverage new productivity-enhancing features while managing complexity through automated, context-aware feature adoption.
Data Source
AI summary
Systems for database system management. A method embodiment commences upon intercepting a feature or command that is issued from a software application that interfaces with a database management system. Rules are used to identify that the feature or command is of a first type (e.g., an older type). The feature or command is analyzed to determine if it is a candidate to be modified or upgraded to implement a newer feature or command of a second type (e.g., a newer type). Modifications are made to the old feature or command of the first type to implement a new feature or command of a second type. The new feature or command of the second type is sent to the database management system for processing.