Group Join Operator for Hierarchical Data Relationships
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Solution Overview
Problem
Conventional relational database systems lack the ability to efficiently navigate and represent complex one-to-many or many-to-one data relationships, resulting in flat and repetitive results that do not accurately reflect the underlying data associations.
Innovation Solution
A group join operator and associated mechanisms are introduced to facilitate traversal of relationships across multiple data collections, enabling nested or hierarchical results, which can be flattened if needed, and supporting conventional joins as a subset of group joins, using query syntax like 'GroupJoin' or 'join ... into' for efficient data retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional relational database systems use traditional join operations, then data can be retrieved from multiple tables, but the results are flat and repetitive, failing to accurately reflect complex one-to-many or many-to-one data relationships
Solution Approach 1:
The patent applies nesting by placing related data collections inside each other to represent one-to-many relationships. The result of a group join is a collection of objects where each object contains the related elements from the other collection, creating a nested structure that preserves the original relationship semantics without requiring repetitive flattening.
Solution Approach 2:
The patent transitions from two-dimensional flat table results to three-dimensional nested collection structures. By adding a hierarchical dimension that represents the relationship between collections, the system can preserve complex data associations that would otherwise be lost in traditional flat join results.
2Quantity of substance
If conventional SQL joins are used to retrieve data across multiple tables, then data can be combined, but rows with null values or no matches are not returned in inner joins
Solution Approach 1:
The group join operator provides universal functionality by handling multiple join types (inner join, left outer join, right outer join, full outer join) through a single unified operation. The same group join mechanism can retrieve matching rows for inner joins while also preserving rows with null values or no matches for outer joins, eliminating the need to choose between different join types.
3Productivity
If nested queries or hash joins are employed to facilitate relation navigation, then data relationships can be traversed efficiently, but the query syntax and mechanisms become more complex
Solution Approach 1:
The patent merges multiple join operations and query mechanisms into a single group join operator. By combining inner joins, outer joins, and relationship navigation into one unified operation, the system achieves efficient data retrieval while simplifying the query syntax and eliminating the need for complex nested queries or multiple separate join operations.
4Adaptability or versatility
If traditional relational databases are used, then data can be stored in tables with rows and columns, but complex data relationships cannot be efficiently navigated or represented
Solution Approach 1:
The patent introduces dynamic data collection structures that can adapt to represent different relationship types (one-to-many, many-to-one, many-to-many) without requiring changes to the underlying data storage structure. The group join operator dynamically creates appropriate collection hierarchies based on the query requirements, providing versatility while maintaining a consistent data model.
Data Source
AI summary
A group join query facilitates navigation of relationships (e.g., one-to-many or many-to-one) across a plurality of data collections. Such a query operator produces nested or hierarchical results that capture the arguments passed thereto. If desired, the nested results can be flattened to simulate conventional relational database results.