Regex Decomposition With Adaptive Evaluation for Large Log Search
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Solution Overview
Problem
Existing methods for evaluating regular expressions on large volumes of operational logs are inefficient and resource-intensive, leading to prolonged processing times and suboptimal performance.
Innovation Solution
A framework for regular expression decomposition and evaluation that identifies pattern and literal components, determines evaluation processes based on performance characteristics, and selects an optimal process for efficient execution, reducing reliance on statistics or catalogs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional regular expression evaluation methods are used on large volumes of operational logs, then the evaluation can be performed, but the processing time is prolonged and resource consumption is high
Solution Approach 1:
The patent segments the regular expression evaluation process into multiple evaluation processes with different strategies. Each evaluation process handles specific patterns or data characteristics differently, allowing parallel execution and optimized resource utilization. This segmentation enables the system to evaluate regular expressions more efficiently by distributing the workload across multiple specialized evaluation paths rather than using a single monolithic evaluation approach.
2Productivity
If traditional regular expression evaluation methods are used, then the evaluation can be completed, but resource consumption is excessive
Solution Approach 1:
The patent implements dynamic selection of evaluation processes based on the characteristics of the input data and regular expression patterns. The system adapts its evaluation strategy in real-time, choosing the most resource-efficient evaluation process for each specific case. This dynamic approach allows the system to optimize resource consumption by avoiding unnecessary computational overhead while maintaining evaluation accuracy.
3Speed
If multiple evaluation processes are implemented to improve efficiency, then processing speed increases, but the complexity of the evaluation system increases
Solution Approach 1:
The patent introduces an intermediary layer that manages multiple evaluation processes. This intermediary component selects and coordinates the execution of different evaluation processes based on input characteristics, abstracting the complexity from the user while enabling parallel and optimized evaluation. The intermediary acts as a mediator between the simple user interface and the complex underlying evaluation mechanisms, allowing high processing speed without exposing system complexity to the end user.
Data Source
AI summary
Regular expression (“regex”) decomposition and evaluation is disclosed. In an aspect of the disclosure, a literal component and a pattern component in a regex are determined. A plurality of evaluation processes is determined based on the regex, including a first evaluation process configured to identify text that matches the literal component and the pattern component. The evaluation processes are executed with respect to a sample of data to determine performance characteristics including a performance characteristic respective to each evaluation process. An evaluation process of the evaluation processes is selected based on the determined performance characteristics. The selected evaluation process is executed with respect to further data to retrieve results that satisfy the selected evaluation process. In another aspect, the pattern component is decomposed into subcomponents. In another aspect, the evaluation processes include an evaluation process that specifies a process to provide the regex to a regex engine for execution thereof.