Rule Variable Processing Weight Optimization
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Solution Overview
Problem
Existing data processing rules do not utilize optimized vocabulary and grammar, leading to unnecessary consumption of processing resources and time.
Innovation Solution
A variable mapping system is employed to determine processing weights for rule variables, optimizing rule construction by mapping variables to similar ones with lower processing costs, and using AI systems to correlate variables and determine weights based on runtime statistics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If rules are constructed using non-optimized vocabulary and grammar, then rule authoring is simpler and more flexible, but processing resources and time are unnecessarily consumed
Solution Approach 1:
The system performs preliminary analysis of rule variables during rule authoring, calculating processing weights and identifying optimization opportunities before the rule is executed. This advance preparation allows the system to select the most efficient vocabulary and grammar constructs, reducing processing resources and time consumed during actual rule execution while maintaining authoring flexibility
Solution Approach 2:
The system changes parameters related to variable representation and grammar structure based on calculated processing weights. By dynamically selecting vocabulary and grammar constructs with optimal processing characteristics, the system improves data processing efficiency while managing resource consumption, allowing rule authors to benefit from optimized performance without sacrificing authoring simplicity
2Adaptability or versatility
If multiple variables are used to retrieve the same data, then rule flexibility and coverage are improved, but processing load increases
Solution Approach 1:
The system implements feedback mechanisms that monitor variable usage patterns and processing weights during rule execution. By analyzing which variables are actually used and their performance characteristics, the system can provide feedback to rule authors about alternative variables that achieve the same data retrieval with lower processing loads, maintaining rule flexibility while reducing overall processing requirements
Solution Approach 2:
The system creates optimized copies or alternatives of frequently used variables based on processing weight analysis. When multiple variables can retrieve the same data, the system identifies and promotes the use of the most efficient variant, allowing rule authors to maintain flexible rule designs with multiple variable options while the system ensures optimal processing performance by selecting the lightest-weight variable for execution
Data Source
AI summary
There are provided systems and methods for determining processing weights of rule variables for rule processing optimization. A service provider, such as an electronic transaction processor for digital transactions, may utilize different decision services that implement rules for decision-making of data including real-time data in production computing environments. Rules may correspond to coded statements that perform an automated decision-making service for the computing services and platforms of the service provider. When writing rules, different variables for data objects may be utilized, where each variable may perform a different operation and/or utilize a different operation for fetching and retrieving data used during rule processing. Each variable may therefore have a different data processing weights based on processing requirements of the data. Thus, optimization of rule authoring may be performed by mapping variables to other similar variables and showing a processing weight of each variable.