Dynamic Schema Transition for Memory-Efficient Database Compatibility
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Solution Overview
Problem
Static schema entities in databases consume significant memory due to unused field data, leading to inefficient memory usage and incompatibility issues when transitioning to dynamic schema, which requires removing static schema elements, making third-party code incompatible.
Innovation Solution
A mechanism to transition static schema to dynamic schema by generating a software development kit (SDK) that supports dropped fields, allowing dynamic schema entities to be removed while maintaining third-party code compatibility, and optimizing memory usage by not loading unused fields.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static schema entities are used to ensure high performance and code compatibility, then access performance and reliability are improved, but memory consumption increases due to loading all field data including unused fields
Solution Approach 1:
The patent introduces dynamic schema entities that can be added, removed, or modified at runtime, allowing the system to adapt to changing requirements. This enables the database to load only the fields actually needed by third-party code at runtime, rather than loading all static schema fields, thus reducing memory consumption while maintaining compatibility.
Solution Approach 2:
The patent changes the parameter of schema entity from static (compile-time fixed) to dynamic (runtime changeable). This allows the system to modify which fields are loaded and which are dropped based on actual usage patterns, resolving the contradiction between ensuring all fields are available for compatibility and reducing memory usage by loading only necessary fields.
2Quantity of substance
If static schema elements are removed to reduce memory usage, then memory consumption decreases, but third-party code compatibility is broken since the code references removed schema entities
Solution Approach 1:
By using dynamic schema entities instead of static ones, the system can remove unused fields from the active schema at runtime while maintaining the ability to add them back if needed. This dynamic approach allows memory optimization without breaking third-party code compatibility, as the schema can adapt to both current needs and historical references.
Solution Approach 2:
The dynamic schema mechanism serves multiple functions: it can drop unused fields to save memory, but also can restore or modify fields when needed to maintain compatibility with third-party code. This multi-functionality resolves the contradiction by allowing the same mechanism to serve both memory optimization and compatibility preservation.
3Speed
If all fields are loaded at startup to ensure data availability, then access performance is improved, but memory consumption increases significantly for unused fields
Solution Approach 1:
The system performs preliminary identification of which fields are actually used by third-party code through analysis of the code itself during compilation or initialization. This preliminary action allows the system to load only the necessary fields at startup, optimizing both memory consumption and access performance by avoiding the loading of unused fields while still ensuring all needed fields are available when accessed.
Data Source
AI summary
Systems and methods that provide a mechanism to transition static schema to dynamic schema while maintaining backwards capability. Simple removal of static schema elements, followed by replacement with dynamic schema elements, make a third-party code incompatible since the third-party code references schema entities that no longer exist. Provided is a mechanism to decrease the memory use of non-material static schema entities. Transitioning static schema to dynamic schema allows the database to avoid loading non-material schema entities, thereby decreasing overall memory usage.