N-Conjoined Tree Rearrangement for Multidimensional Data Updates
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Query evaluation systems face challenges in handling large and complex multi-dimensional datasets, particularly in storing and manipulating data associated with planning models, due to performance issues and difficulties in data structure manipulations such as inserting or rotating table rows and columns.
Innovation Solution
The implementation of an N-conjoined tree data structure as an intermediary data structure for data manipulation, which includes generating, changing, and rearranging data structures while enforcing rules that ensure each leaf node has an associated linkage to each tree, allowing for efficient data manipulation and representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional multi-dimensional database structures are used to store and manipulate planning model data, then data can be organized in a structured format, but performance deteriorates when handling large and complex datasets due to difficulties in data structure manipulations
Solution Approach 1:
The patent segments the multi-dimensional data structure into multiple tree structures, where each dimension is represented as a separate tree. This segmentation allows independent manipulation of each dimension without affecting others, improving manipulation efficiency while maintaining structured organization of large datasets.
Solution Approach 2:
The patent introduces an intermediary data structure layer between the traditional multi-dimensional database and the query evaluation system. This intermediary uses tree-based representations that simplify manipulation operations while preserving the ability to handle complex multi-dimensional data, thus improving productivity without losing data organization capabilities.
2Adaptability or versatility
If data structures are manipulated to insert or rotate table rows and columns for analysis, then data can be reorganized for different analytical perspectives, but performance deteriorates due to the computational complexity of these operations
Solution Approach 1:
The patent implements dynamic tree structures that can be efficiently reconfigured through pointer manipulation rather than physical data movement. Inserting or rotating dimensions becomes a matter of reassigning parent-child relationships in the tree structure, which is computationally efficient compared to traditional table row/column operations, thus enabling versatile data reorganization with minimal time loss.
Solution Approach 2:
The patent transforms the traditional two-dimensional table structure into multi-dimensional tree structures, adding hierarchical dimensions to the data organization. This allows analytical perspectives to be changed by traversing different tree paths rather than performing complex row/column rotations, significantly reducing manipulation time while maintaining adaptability.
Data Source
AI summary
A system, method, and device for managing updates to a hypercube is provided. The method includes (i) obtaining a tree data structure to represent the data, (ii) receiving a request to rearrange data stored in the N-conjoined tree data structure, (iii) enforcing a first rule that requires each leaf node to have an associated linkage to each tree in the N-conjoined tree data structure while rearranging the N-conjoined tree data structure in accordance with the request, and (iv) providing a rearranged N-conjoined tree data structure. The tree data structure is an N-conjoined tree data structure, and N is a positive integer.