Adaptive Schema Generation for Flexible Data Handling
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Solution Overview
Problem
Current application development environments require rigid schema definitions, limiting flexibility and cross-row operations, which complicates data handling and reduces application functionality.
Innovation Solution
A method for generating adaptive schemas that dynamically updates and validates record types based on incoming data, allowing for 'just-in-time' inclusion of new fields and automatic indexing, enabling flexible schema management and query functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If rigid schema definitions are used, then data integrity is ensured, but flexibility and adaptability are reduced
Solution Approach 1:
The patent implements dynamic schema evolution by allowing schemas to be automatically updated when new data records are introduced. The system transitions from static schema definitions to dynamic schemas that adapt to new data types and structures while maintaining validation rules, resolving the contradiction between data integrity and schema flexibility
Solution Approach 2:
The system changes the parameter state of schemas from fixed to mutable. By allowing schema parameters (data types, field structures) to be modified based on incoming data records, the system maintains data integrity through controlled evolution while gaining the flexibility to accommodate new data formats and requirements
2Ease of manufacture
If schemas are eliminated for simplicity, then development ease is improved, but cross-row operations and data consistency are compromised
Solution Approach 1:
The patent segments the schema management process into automatic schema generation, validation rule application, and adaptive update mechanisms. This segmentation allows the system to maintain simplified development processes while automatically ensuring data consistency and enabling cross-row operations through structured schema enforcement
Solution Approach 2:
The system implements self-service schema management where the database automatically generates and updates schemas based on incoming data records without requiring manual developer intervention. This self-service mechanism maintains development simplicity while ensuring data consistency and enabling cross-row operations through automatic schema enforcement
3Manufacturing precision
If manual schema definition is required, then data validation precision is improved, but development time and complexity increase
Solution Approach 1:
The system performs preliminary schema generation automatically based on incoming data records. By pre-defining schema structures and validation rules through automatic analysis of data patterns, the system achieves precise data validation without requiring manual schema definition, thereby reducing development time while maintaining validation precision
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors incoming data records and automatically adjusts schema definitions based on observed data patterns. This feedback-driven approach maintains precise data validation by learning from actual data while eliminating manual schema development time through automatic adaptation
Data Source
AI summary
A method of generating a schema including receiving a data record having a record type name and one or more data values is provided. The data values are associated with data value names. The method includes determining whether a set of existing schemas includes a schema associated with the record type name, determining whether the schema includes an element having the same name as a corresponding data element of the record, and validating the corresponding data element against the schema element. A new schema element is added to the schema, the new schema element having the same name and type as the corresponding data element of the record. The method can further include indexing at least one of the one or more data values, which involves querying the indexed data, forming subscription lists for the data values, and forming a derived data value associated with one or more data values.