Bulk Update Function for View Resource Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing view building applications lack a bulk update function for resource data, requiring manual, instance-by-instance updates that are time-consuming, prone to human error, and increase system resource load.
Innovation Solution
A dynamic bulk updating function is introduced, allowing for the generic integration into any view to import and update resource data for multiple instances, eliminating the need for custom APIs and reducing code complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual instance-by-instance update process is used, then data can be updated in existing systems, but time consumption and system resource load increase significantly
Solution Approach 1:
The patent combines multiple individual update operations into a single bulk update operation. The system retrieves multiple instances of view data and updates them simultaneously through one API call, rather than requiring separate update operations for each instance. This merging approach directly reduces the time required for data updates while maintaining system reliability.
Solution Approach 2:
The patent creates a universal bulk update function that can handle updates across multiple instances and different views through a single standardized interface. This multi-functional capability allows the system to update diverse data instances without requiring instance-specific update logic, thereby reducing overall update time while ensuring reliable data modification across the platform.
2Reliability
If manual instance-by-instance update process is used, then data can be updated, but user convenience deteriorates due to repetitive manual effort
Solution Approach 1:
The system merges multiple update operations into a single user action. Users can select multiple instances and update them simultaneously through one interface operation, eliminating the need for repetitive manual updates. This significantly improves ease of operation while maintaining the reliability of data updates through the standardized bulk update function.
Solution Approach 2:
The bulk update function enables users to perform updates independently without requiring developer intervention or custom API development. The standardized interface allows users to update multiple instances directly through the user interface, improving convenience while ensuring reliable data modification through the system's built-in bulk update capability.
3Adaptability or versatility
If custom APIs are created for each backend table, then view data can be saved to specific tables, but code complexity and development time increase
Solution Approach 1:
The patent implements a universal bulk update function that can save view data to multiple different backend tables through a single standardized interface. This eliminates the need to create custom APIs for each table, as the universal function automatically routes data to the appropriate tables based on the view configuration. This maintains adaptability to different tables while dramatically reducing code complexity.
Solution Approach 2:
The system introduces an intermediary bulk update function that acts as a mediator between the user interface and multiple backend tables. This intermediary layer handles the complexity of routing data to different tables, eliminating the need for direct custom API creation for each table. The intermediary maintains versatility in handling different table structures while simplifying the overall system architecture.
4Adaptability or versatility
If custom APIs are created for each view modification, then data can be saved to corresponding tables, but development time and code complexity increase
Solution Approach 1:
The patent creates a universal bulk update function that handles view modifications without requiring custom API development for each view. The function automatically adapts to different view configurations and updates the corresponding backend tables through a standardized interface. This maintains full adaptability to view modifications while significantly improving development efficiency by eliminating repetitive API creation work.
Solution Approach 2:
The system performs preliminary configuration of the bulk update function to handle various view types and table mappings in advance. This preliminary setup allows the universal function to automatically adapt to different view modifications without requiring additional development work. The pre-configured routing logic enables rapid view modification while maintaining adaptability to different data structures.
Data Source
AI summary
A system for bulk updating resource data of parameters included in a view is provided. The system includes at least one processor configured to: receive a user request to bulk import data in a file including rows of the data, each row corresponding to a different instance of the view; make an import data API call to bulk import the data into one or more tables to which the data of the parameters is to be saved; make a save data API call to update existing resource data of the parameters, stored in the one or more tables, with the data included in the file; and update, in the one or more tables, the existing resource data of the parameters for the plurality of instances with the data included in the file, wherein the import data save data APIs are generic across a plurality of views and tables.