Database Trace Field Adjustment via Data Analysis
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Solution Overview
Problem
Database tracing processes negatively impact system performance by occupying system resources and generating large volumes of data, making it difficult to obtain real-time background trace data for diagnosing database errors and performance issues.
Innovation Solution
A computer program product that analyzes database trace data to determine field-related rules, which are then applied to adjust trace fields, reducing the impact on system performance by eliminating or adding trace fields based on performance threshold curves, correlation dependencies, and association rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If database tracing is performed to collect trace data for diagnosing errors and performance issues, then diagnostic capability is improved, but system performance deteriorates due to resource occupation and large data generation
Solution Approach 1:
The patent extracts only the most relevant trace fields from the complete database trace data based on analysis of historical trace data and identification of performance-affecting fields. By taking out and retaining only critical fields (such as those with high correlation to performance issues), the system maintains diagnostic capability while significantly reducing the volume of trace data collected in real-time, thereby lessening the performance burden on the database system.
Solution Approach 2:
The patent applies partial action by performing complete trace field analysis only on historical or offline trace data, while using the derived insights to guide selective collection of only essential fields during real-time tracing. This partial application of full analysis allows the system to achieve good diagnostic results without the excessive resource consumption of analyzing all trace fields in real-time.
2Loss of information
If all trace fields are collected during database tracing, then complete diagnostic information is obtained, but the volume of data generated increases significantly
Solution Approach 1:
The patent extracts and identifies the subset of trace fields that have the greatest impact on performance and diagnostic value by analyzing correlations between different trace fields and performance metrics. Only these extracted critical fields are retained for continued collection, while non-critical fields are eliminated, thus maintaining diagnostic information completeness for essential parameters while dramatically reducing overall data volume.
Solution Approach 2:
The patent applies local quality by differentiating between critical and non-critical trace fields, assigning different collection strategies to different fields. Critical fields that provide essential diagnostic information are collected with high fidelity and retained, while non-critical fields are either collected minimally or eliminated entirely, creating a differentiated trace data collection approach that optimizes the balance between information quality and data volume.
3Measurement precision
If comprehensive database tracing is performed to identify performance issues, then diagnostic accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary analysis of trace field correlations and performance relationships offline or on historical data before real-time tracing begins. This preliminary action identifies which trace fields are most strongly correlated with performance issues, allowing the system to pre-configure the trace field selection criteria. During real-time tracing, this pre-established knowledge enables rapid identification of performance issues without the need to process and analyze all possible trace fields, thereby maintaining diagnostic accuracy while reducing processing time.
Solution Approach 2:
The patent applies partial action by using full comprehensive analysis only for offline training and model development, while employing a streamlined, partial analysis approach for real-time trace processing. The system processes only the essential trace fields identified through preliminary analysis during real-time operation, achieving sufficient diagnostic accuracy for production environments without the excessive processing time required for complete analysis of all trace fields.
Data Source
AI summary
Trace processing in a database system is facilitated by obtaining database trace data collected from database tracing a database system, and data analyzing, by one or more processors, the database trace data to determine one or more field-related rules to, in part, reduce impact on system performance of database tracing in the database system. Trace processing is further facilitated by applying the one or more field-related rules to a database trace in the database system to adjust trace fields of the database trace according to the one or more field-related rules, thereby reducing impact on system performance of the database trace in the database system.