Schema-less Data Versioning with Cycle Number Tracking
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Solution Overview
Problem
Current systems face challenges in efficiently managing versioning of data items without predefined schemas, particularly in rolling back to previous versions and maintaining historical data without recording temporal validity, which complicates data analysis and error correction.
Innovation Solution
A method for recording and retrieving versioning information of data items using unique identifiers and version numbers, where attributes are associated with version numbers without recording time validity, allowing for asynchronous and synchronous updates across repositories, and utilizing cycle numbers to track temporal validity for efficient lookups and snapshot generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If versioning is implemented without recording time validity periods, then version retrieval efficiency is improved, but data temporal tracking capability deteriorates
Solution Approach 1:
The patent extracts temporal validity information from the main versioning structure and stores it separately in a dedicated data structure. This allows version retrieval to proceed without time period queries, improving efficiency, while temporal information remains preserved for analysis purposes.
Solution Approach 2:
The versioning system is segmented into two independent components: a version number-based indexing structure for efficient retrieval, and a separate temporal validity structure for maintaining time period information. This segmentation allows each component to optimize for its specific function without compromising the other.
2Adaptability or versatility
If schema-less data models are used, then data flexibility and adaptability are improved, but data structure validation and consistency deteriorate
Solution Approach 1:
The system dynamically adapts the data structure to match the actual data being stored, rather than enforcing a rigid predefined schema. The data model evolves based on the specific requirements of each data item, maintaining flexibility while ensuring consistency through dynamic validation rules that are applied based on the actual data context.
3Productivity
If asynchronous updates are implemented across repositories, then system responsiveness and throughput are improved, but data consistency and synchronization deteriorate
Solution Approach 1:
The system implements feedback mechanisms where repositories periodically synchronize version information and validate data consistency across the distributed system. This allows asynchronous operations to proceed at high speed while periodic feedback ensures that any drift in data consistency is detected and corrected.
Data Source
AI summary
Among other disclosed subject matter, a computer program product is tangibly embodied in a computer-readable storage medium and includes instructions that when executed by a processor perform a method for recording information about an item. The method includes assigning a unique identifier to an item in a repository, the item supporting versioning and being subject to a data model having no predefined schema for items. The method includes associating a first attribute with the unique identifier, the first attribute being part of the item and being configured for modification. The method includes associating the first attribute with a version number, wherein the versioning is supported without recording in the repository a time period when the first attribute is valid.