Hierarchical Data Structure Node Limit Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Hierarchical data structures face inefficiencies in querying and updating large datasets due to the need to traverse entire structures, leading to excessive processing power consumption and potential system delays, especially when rigid height and width limits are imposed on tree structures, which may not fit all organizational needs.
Innovation Solution
Implementing a system that allows for flexible structural limits on the number of nodes in hierarchical data structures, determining an optimal number of nodes through performance tests, and using synchronous or asynchronous update methods based on node thresholds to manage data efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the hierarchical data structure allows unlimited nodes, then the data storage capacity increases, but the querying and updating operations consume excessive processing power and time
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the maximum node limit based on system performance metrics. The node limit is not fixed but varies according to available processing power, memory resources, and query patterns, allowing the system to optimize between storage capacity and operational efficiency by changing the structural parameter of node quantity
2Productivity
If rigid height and width limits are imposed on tree structures, then system performance is optimized, but the adaptability to different organizational needs is reduced
Solution Approach 1:
The patent implements dynamics by transforming static, rigid height and width limits into dynamic, flexible constraints. The system continuously monitors performance metrics and automatically adjusts the structural limits of the hierarchical tree to match current organizational requirements and system capabilities, making the structure adaptable while maintaining performance optimization
Solution Approach 2:
The patent changes the parameters of tree height and width from fixed values to variable parameters that can be adjusted based on performance testing and organizational needs. This allows the system to modify structural parameters dynamically, balancing performance optimization with adaptability to different data organization requirements
3Reliability
If the hierarchical data structure is updated synchronously, then data consistency is maintained, but the update operations cause system delays and increased processing time
Solution Approach 1:
The patent applies periodic action by implementing batched or periodic update operations instead of continuous synchronous updates. The system groups multiple updates into periodic batches, maintaining data consistency within each batch while reducing the overall time impact on the system by spacing out update operations
4Productivity
If the hierarchical data structure is updated asynchronously, then processing speed increases, but data consistency and reliability are compromised
Solution Approach 1:
The patent implements feedback mechanisms to monitor and ensure data consistency in asynchronous update operations. The system uses feedback loops to verify that asynchronous updates maintain referential integrity and data consistency constraints, allowing high processing speed while preventing consistency violations through continuous validation
Data Source
AI summary
A method and system for generating a hierarchical data structure is described. The hierarchical data structure is comprised of a plurality of nodes, wherein each node represents a record. The system monitors the generation of the hierarchical data structure to determine if the number of nodes in the hierarchical data structure exceeds a predetermined maximum number of nodes for the hierarchical data structure. The maximum number of nodes is independent of a width and a height of the hierarchical data structure. The system generates a notification in response to a determination that the number of nodes in the hierarchical data structure exceeds the maximum number of nodes.