Virtual Table Assembly for Flexible Relational Schema Changes
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Solution Overview
Problem
The development of a relational datastore schema is time-consuming and requires updates during application deployments, limiting flexibility and efficiency in schema changes.
Innovation Solution
A virtual table is created using elements like physical tables, views, functions, and stored procedures to populate and modify data without adding a new schema, allowing dynamic assembly and modification of data within the relational datastore.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a relational datastore schema is developed ahead of time to match current usage, then data organization and query efficiency are improved, but flexibility and speed of schema changes deteriorate
Solution Approach 1:
The patent implements dynamic schema evolution by allowing the system to automatically detect changes in data usage patterns and transform the schema accordingly. Instead of static pre-defined schemas, the system dynamically adapts the relational structure based on actual query patterns and data access behaviors, resolving the contradiction between organized data structure and flexibility for changes.
Solution Approach 2:
The system changes the parameter of schema rigidity by introducing automatic schema evolution capabilities. The schema transitions from a fixed state to an evolving state where parameters such as table structures, relationships, and constraints can be automatically modified based on detected usage patterns, maintaining both organization and adaptability.
2Reliability
If schema changes are implemented during application updates, then data integrity and consistency are maintained, but deployment time and productivity deteriorate
Solution Approach 1:
The system performs preliminary schema evolution actions by continuously monitoring and analyzing data usage patterns in the background. Schema changes are prepared and validated ahead of time through automatic detection and transformation processes, so that when deployment occurs, the changes are already optimized and ready to be applied with minimal disruption, maintaining both consistency and speed.
Solution Approach 2:
The system provides self-service schema evolution by automatically detecting usage patterns, generating schema transformation plans, and applying changes without requiring manual intervention during deployment. This self-managing capability maintains data integrity through automated validation while significantly reducing deployment time and increasing productivity.
3Adaptability or versatility
If a virtual table is used to populate data from physical tables, then schema flexibility is improved, but system complexity increases
Solution Approach 1:
The patent introduces a virtual table as an intermediary layer between physical storage tables and the application layer. This virtual table acts as a mediator that provides flexible data access and schema evolution capabilities without requiring changes to the underlying physical structure. The intermediary handles the complexity of schema transformations internally, presenting a simplified and flexible interface to users while maintaining manageable system architecture.
Data Source
AI summary
A method, computer program product, and computer system for defining, by a computing device, a virtual table created using one or more elements. The virtual table may be populated with data retrieved from one or more physical tables, wherein the one or more physical tables may include one or more relational datastore schemas of a relational datastore. A modification to the virtual table may be received. The virtual table may be modified in the relational datastore without adding another relational datastore schema.