NoSQL Schema Generation via Key Hierarchy Analysis
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Solution Overview
Problem
The integration of relational databases and NoSQL databases is hindered by the lack of a comparable schema, making data matching, consolidating, and exchanging between the two systems difficult, especially due to NoSQL's dynamic structure and variable attribute names.
Innovation Solution
A method and device for generating a schema for NoSQL databases by determining a treelike relationship between key hierarchies, identifying attribute name variations, and updating the record schema based on similarity, allowing for the creation of a schema that adapts to changing data structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If NoSQL database uses dynamic structure with variable attribute names, then adaptability and flexibility are improved, but difficulty of detecting and measuring increases
Solution Approach 1:
The patent applies preliminary action by pre-processing NoSQL data entries to extract and analyze attribute names before schema generation. The system performs preliminary detection of attribute name variations across multiple data entries, builds a frequency distribution, and pre-determines the schema structure before actual data storage operations. This allows the system to adapt to dynamic NoSQL structures while maintaining measurement capability through systematic analysis of attribute patterns.
2Adaptability or versatility
If NoSQL database uses dynamic structure with variable attribute names, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent applies self-service by enabling the NoSQL database system to automatically generate its own schema from stored data entries without requiring external schema definition tools or complex configuration systems. The database autonomously analyzes its own data structure, detects attribute variations, and constructs the schema internally, thereby improving adaptability while avoiding the complexity of external schema management infrastructure.
3Manufacturing precision
If schema generation for NoSQL database is manual and complex, then manufacturing precision is maintained, but productivity decreases
Solution Approach 1:
The patent applies mechanics substitution by replacing manual, mechanical schema generation processes with an automated computational system. Instead of manually analyzing data structures and defining schemas, the system uses automated algorithms to detect attribute patterns, analyze data entries, and generate schemas programmatically. This substitution maintains precision through systematic analysis while dramatically improving productivity by eliminating manual intervention.
4Stability of the object's composition
If relational database uses fixed structure with all fields allocated to each entry, then stability is improved, but productivity decreases
Solution Approach 1:
The patent applies dynamics by enabling the database schema to adapt dynamically to the actual data structure rather than enforcing a rigid fixed structure. The system analyzes stored data entries to determine the actual attributes present, allowing the schema to reflect the true data organization. This dynamic approach improves productivity by eliminating the overhead of allocating and managing unused fields while maintaining stability through consistent schema generation from actual data patterns.
Data Source
AI summary
Generation of a schema of a NoSQL type database, where a set of entry(ies) of a NoSQL type database can be determined, and the record schema is a treelike relationship between key hierarchies with a key as a node in the entry, wherein the key corresponds to an attribute name. For at least one record schema, a node in which there is an attribute name variation is determined based on a similarity of sub-nodes in the treelike relationship, and the record schema is updated according to the determined result. The schema of the NoSQL type database is generated based on the updated record schema.