Normalized Tabular Indexed Data Structure for Hierarchical Database Queries
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Solution Overview
Problem
Relational database management systems face challenges in efficiently performing hierarchical computations on large datasets with diverse formats and topologies, requiring developers to handle 'corner cases' and manual recursive processing, which is time-consuming and error-prone.
Innovation Solution
A method is introduced that allows users to select generator and navigation functions through a structured query language, forming a normalized tabular indexed data structure, which supports various data formats and topologies, enabling efficient hierarchical attribute calculation and navigation without manual recursive processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual recursive processing is used to handle hierarchical data, then developers can process complex hierarchical structures, but the processing time increases and errors occur more frequently
Solution Approach 1:
The patent introduces an intermediary normalized tabular indexed data structure that mediates between the source hierarchical data and the query processing. This intermediate structure pre-computes and stores hierarchical relationships in a normalized format with indexes, eliminating the need for manual recursive processing during queries while maintaining accuracy and reducing errors.
2Adaptability or versatility
If custom hierarchy functions are developed to handle diverse data formats and topologies, then the system can support various hierarchical structures, but the development complexity and domain-specific knowledge required increase
Solution Approach 1:
The patent creates a universal normalized tabular indexed data structure that can handle diverse data formats and topologies through a single unified approach. The normalization process and indexing mechanism provide multi-functional support for various hierarchical structures without requiring separate custom functions for each data type, thereby reducing development complexity while maintaining versatility.
Solution Approach 2:
The patent transforms hierarchical data into a normalized tabular format by changing the structural parameters of the data representation. This parameter transformation allows diverse hierarchical structures to be processed through a common framework, reducing the need for domain-specific custom functions and lowering development complexity.
3Productivity
If normalized tabular indexed data structure is created, then query processing efficiency improves, but the initial data processing and index creation time increases
Solution Approach 1:
The patent applies preliminary action by pre-processing the hierarchical source data into a normalized tabular indexed structure before query execution. This upfront data preparation and indexing work is performed once, enabling significantly faster query processing subsequently, as the complex hierarchical relationships are already computed and stored in an optimized format.
Data Source
AI summary
A selection of a generator function can be received. The generator function can be configured to be applied to source data to form a normalized tabular indexed data structure. The tabular indexed data structure can include a set of hierarchical attributes. A navigation function can be selected to be applied to the tabular indexed data structure to determine a navigation result. The navigation result can be provided to a user.