Loosely Associated Data Structure Recursive Traversal
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional 'tightly associated' data structures require excessive storage and administrative overhead due to multiple association references, leading to inefficiencies in data access and processing, especially as database size increases.
Innovation Solution
A 'loosely associated' data structure using a single association identifier and a recursive traversal method that reduces storage requirements and administrative overhead by eliminating the need for additional columns and database transactions, allowing efficient iteration and processing of nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a tightly associated data structure is used with multiple association references, then data relationships can be easily queried and maintained, but storage space requirements increase and query processing becomes more complex
Solution Approach 1:
The patent extracts only the necessary association information by using a single association identifier column instead of multiple association reference columns. This removes redundant data while maintaining the ability to traverse relationships through the single identifier, directly reducing storage space without sacrificing relationship maintenance capability
Solution Approach 2:
The single association identifier serves multiple functions: it identifies parent-child relationships, enables recursive traversal, and maintains data integrity. This multi-functional design eliminates the need for separate columns for different association types, reducing storage while maintaining reliability
2Reliability
If multiple association references are stored in database records, then node relationships can be accurately maintained, but the number of database transactions increases significantly
Solution Approach 1:
The patent extracts only the essential association identifier from multiple reference columns, reducing the number of database operations required. By storing only the single association identifier instead of multiple references, the system maintains accuracy while significantly reducing the number of transactions needed for insertions, updates, and deletions
Solution Approach 2:
The association identifier is pre-computed and stored during data insertion, eliminating the need for subsequent transactions to maintain relationship accuracy. This preliminary action ensures that association integrity is maintained without requiring multiple coordinated database transactions
3Adaptability or versatility
If additional columns are added to store association references, then data structure relationships can be fully represented, but device complexity increases
Solution Approach 1:
The single association identifier column is designed to be universal, serving as the reference point for all relationship types (parent-child, grandparent-grandchild, etc.). This multi-functional column replaces what would traditionally require multiple specialized columns, reducing device complexity while maintaining data structure flexibility
Solution Approach 2:
The patent transitions from a horizontal expansion approach (adding multiple columns) to a vertical approach (using a single column with hierarchical values). By storing association identifiers in a dimensional hierarchy rather than spreading them across multiple columns, the system achieves the same representational capability with fewer columns
Data Source
AI summary
A data structure and its characteristics, and an associated process for searching the structure in a manner that ensures that each node or data location is traversed regardless of which node is the starting point of the traversal process. An embodiment of the invention may be used to locate a node of a data structure so that it may be processed or otherwise manipulated, such as by eliminating a node, moving a node, processing the data associated with a node, etc. In some embodiments, a combination of a “loosely associated” data structure and a specified method of traversing the data structure provide an efficient way to structure and administer a database, and provide a scalable and computationally efficient solution to the problems posed by conventional and more “tightly associated” structures.