Hierarchical Data Objects for Replication System
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Solution Overview
Problem
Current computing systems face challenges in efficiently integrating and replicating data across different systems, particularly in managing hierarchical data structures and filtering data based on attributes, which hinders seamless data exchange and processing.
Innovation Solution
A system that generates hierarchical lists of attributes and replicates data objects based on specified hierarchies, allowing for precise data mapping and filtering, enabling efficient data integration and processing across multiple computing systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is replicated across different computing systems using traditional methods, then data exchange can occur, but data integrity and consistency are compromised due to lack of hierarchical structure management
Solution Approach 1:
The patent segments data attributes into hierarchical levels (e.g., parent attributes and child attributes) and replicates them separately through distinct interface calls. This segmentation ensures that each hierarchical level maintains its structural integrity during replication, improving data integrity while managing system complexity through organized, modular data handling.
Solution Approach 2:
The patent introduces a hierarchical dimension to data replication by organizing attributes into multiple levels (parent-child relationships) and replicating data along this new dimensional structure. This allows the system to maintain complex hierarchical relationships across distributed systems without proportionally increasing overall system complexity.
2Loss of information
If all attributes of data objects are replicated between systems, then complete data exchange is achieved, but transmission time and bandwidth are excessive
Solution Approach 1:
The patent extracts and replicates only the necessary hierarchical attributes of data objects rather than all attributes. By selectively identifying and replicating parent and child attributes that are essential for maintaining data relationships, the system achieves complete data exchange without the overhead of transmitting unnecessary information, reducing transmission time and bandwidth consumption.
Solution Approach 2:
The patent applies partial action by replicating only the specific hierarchical levels and attributes that are necessary for data integrity, rather than performing excessive full-data replication. This selective approach maintains data completeness where needed while avoiding unnecessary transmission of redundant or non-essential data elements.
3Stability of the object's composition
If hierarchical data structures are implemented for data replication, then data organization and integrity are improved, but the complexity of data mapping and filtering increases
Solution Approach 1:
The patent segments the complex data mapping process into distinct hierarchical levels (parent attributes and child attributes), with each level handled through separate, standardized interface calls. This segmentation simplifies the mapping complexity by breaking down the overall complex task into manageable, repeatable units that can be processed independently while maintaining overall structural stability.
Solution Approach 2:
The patent resolves mapping complexity by introducing a hierarchical dimension to data organization, where attributes are structured in parent-child relationships across multiple levels. This hierarchical dimension provides a natural framework for data mapping and filtering operations, making complex hierarchical data management more systematic and less cumbersome than flat-structure approaches.
4Reliability
If multiple interface calls are used to replicate hierarchical attributes, then data integrity is maintained, but the number of operations and processing time increase
Solution Approach 1:
The patent segments data replication into hierarchical levels (parent and child attributes) processed through separate interface calls. This segmentation maintains data consistency by ensuring each hierarchical level is replicated and validated independently, while the modular nature of segmented processing allows for efficient parallel execution and reuse of validation logic across different data objects.
Solution Approach 2:
The patent creates universal interface calls that can handle both parent and child attribute replication through standardized methods. These multi-functional interface calls maintain data consistency across different hierarchical levels while improving replication efficiency by eliminating the need for separate, specialized handling code for each attribute type, allowing the same interface to serve multiple hierarchical levels.
Data Source
AI summary
Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a specification of a set of attributes associated with a plurality of data objects managed by a first system. Each attribute in the set of attributes is associated with a different level in a hierarchy that includes a set of levels. The program further generates a hierarchical list of the set of attributes associated with the plurality of data objects based on the hierarchy. The program also replicates the plurality of data objects from the first system to a second system based on the hierarchical list of the set of attributes associated with the plurality of data objects in order for the second system to store the plurality of data objects according to the hierarchy.