Hierarchical Data Space Operations for Relational Query Efficiency
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Solution Overview
Problem
Relational data management systems face inefficiencies in querying and operating on relations due to their reliance on indexing and sorting methods, which can lead to high tuple access costs and complex query planning, especially when dealing with complex queries and large datasets.
Innovation Solution
A system and method for transforming relational statements into hierarchical data space operations using hierarchical path identifiers, which allows for probabilistic evaluation and filtering of tuples without accessing actual values, enabling efficient support for complex queries and reducing tuple access costs by organizing data in a hierarchical structure that preserves hierarchy rather than order.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If relational data management systems use traditional indexing and sorting methods to organize data by column values, then data can be accessed and queried using standard relational algebra, but tuple access costs increase and query planning becomes complex especially for large datasets
Solution Approach 1:
The patent introduces hierarchical path identifiers as an intermediary layer between the relational query interface and the physical data storage. These identifiers enable efficient navigation through hierarchical data spaces without requiring traditional indexing or sorting operations, thus reducing tuple access costs while maintaining ease of query execution
Solution Approach 2:
The patent transforms the traditional flat relational data model into a multi-dimensional hierarchical data space. By organizing data in hierarchical levels with path identifiers representing positions in this hierarchy, the system enables efficient query execution through hierarchical navigation rather than linear scanning or indexing, significantly reducing access time for large datasets
2Adaptability or versatility
If relational systems store data in row-oriented or column-oriented formats with traditional indexing, then standard relational operations can be performed, but the system complexity increases for handling complex queries efficiently
Solution Approach 1:
The hierarchical data space structure serves multiple functions simultaneously: it enables efficient storage, provides rapid query execution through path-based navigation, supports complex hierarchical queries, and eliminates the need for separate indexing structures. This universal approach handles various query types without increasing system complexity
Solution Approach 2:
The patent extracts the indexing function entirely from the system by replacing traditional indexes with hierarchical path identifiers embedded directly in the data structure. This eliminates the complexity of maintaining separate index structures while preserving and enhancing query capabilities
Data Source
AI summary
A method for transforming a statement into at least one hierarchical data space operation may include analyzing the statement to produce at least one transformed statement. The method may further include selecting at least one element of the transformed statement. The method may further include determining at least one column for the at least one element. The method may further include generating at least one hierarchical data space operation for the at least one element. The method may further include extracting at least one value from the at least one element for the at least one column. The method may further include determining at least one first logical hierarchical data space for the at least one hierarchical data space operation. The method may further include generating at least one first hierarchical path identifier for the at least one value that preserves the hierarchy of its first hierarchical data space, wherein each value corresponds to at least one subdivision of its first hierarchical data space. The method may further include associating the at least one first hierarchical path identifier with the at least one hierarchical data space operation.