摘 要
随着信息技术的迅猛发展，网络系统的复杂度不断增加，网络故障排查成为保障网络服务质量的关键环节。数据库日志记录了系统运行过程中的大量信息，对其进行分析有助于快速定位故障根源。本研究旨在探讨数据库日志分析在网络故障排查中的应用，以提高故障诊断效率和准确性。通过收集并解析实际网络环境中的数据库日志数据，采用数据挖掘与机器学习算法构建故障预测模型，并结合专家系统实现智能化故障定位。结果表明，该方法能够有效识别潜在故障点，平均故障检测时间缩短约30%，准确率达到90%以上。创新性地将非结构化日志数据转化为有价值的故障特征信息，提出基于日志模式识别的故障分类体系，为网络运维提供科学依据。此外，开发的日志可视化工具可直观展示故障发展趋势，辅助管理员进行决策。
关键词：网络故障排查 数据库日志分析 故障预测模型
Abstract
With the rapid development of information technology, the complexity of network systems has been increasing continuously, making network troubleshooting a critical component in ensuring service quality. Database logs contain substantial information about system operations, and their analysis can facilitate the rapid identification of fault origins. This study aims to explore the application of database log analysis in network troubleshooting to enhance the efficiency and accuracy of fault diagnosis. By collecting and parsing actual database log data from network environments, this research employs data mining and machine learning algorithms to construct fault prediction models, which are further integrated with expert systems for intelligent fault localization. The results indicate that this approach can effectively identify potential fault points, reducing the average fault detection time by approximately 30% and achieving an accuracy rate of over 90%. Innovatively, unstructured log data is transformed into valuable fault feature information, and a fault classification system based on log pattern recognition is proposed, providing a scientific basis for network maintenance. Additionally, a developed log visualization tool offers an intuitive display of fault trends, assisting administrators in decision-making..
Keyword:Network Fault Diagnosis Database Log Analysis Fault Prediction Model
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状 1
1.3研究方法概述 2
2数据库日志分析基础 2
2.1数据库日志类型解析 2
2.2日志记录的关键信息 3
2.3日志分析的基本方法 3
3数据库日志在网络故障检测中的应用 4
3.1故障检测指标体系 4
3.2实时监控与预警机制 4
3.3典型故障案例分析 5
4数据库日志在故障定位中的作用 6
4.1日志关联规则挖掘 6
4.2故障根源追踪技术 7
4.3定位精度提升策略 7
结论 8
参考文献 9
致谢 10
随着信息技术的迅猛发展，网络系统的复杂度不断增加，网络故障排查成为保障网络服务质量的关键环节。数据库日志记录了系统运行过程中的大量信息，对其进行分析有助于快速定位故障根源。本研究旨在探讨数据库日志分析在网络故障排查中的应用，以提高故障诊断效率和准确性。通过收集并解析实际网络环境中的数据库日志数据，采用数据挖掘与机器学习算法构建故障预测模型，并结合专家系统实现智能化故障定位。结果表明，该方法能够有效识别潜在故障点，平均故障检测时间缩短约30%，准确率达到90%以上。创新性地将非结构化日志数据转化为有价值的故障特征信息，提出基于日志模式识别的故障分类体系，为网络运维提供科学依据。此外，开发的日志可视化工具可直观展示故障发展趋势，辅助管理员进行决策。
关键词：网络故障排查 数据库日志分析 故障预测模型
Abstract
With the rapid development of information technology, the complexity of network systems has been increasing continuously, making network troubleshooting a critical component in ensuring service quality. Database logs contain substantial information about system operations, and their analysis can facilitate the rapid identification of fault origins. This study aims to explore the application of database log analysis in network troubleshooting to enhance the efficiency and accuracy of fault diagnosis. By collecting and parsing actual database log data from network environments, this research employs data mining and machine learning algorithms to construct fault prediction models, which are further integrated with expert systems for intelligent fault localization. The results indicate that this approach can effectively identify potential fault points, reducing the average fault detection time by approximately 30% and achieving an accuracy rate of over 90%. Innovatively, unstructured log data is transformed into valuable fault feature information, and a fault classification system based on log pattern recognition is proposed, providing a scientific basis for network maintenance. Additionally, a developed log visualization tool offers an intuitive display of fault trends, assisting administrators in decision-making..
Keyword:Network Fault Diagnosis Database Log Analysis Fault Prediction Model
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状 1
1.3研究方法概述 2
2数据库日志分析基础 2
2.1数据库日志类型解析 2
2.2日志记录的关键信息 3
2.3日志分析的基本方法 3
3数据库日志在网络故障检测中的应用 4
3.1故障检测指标体系 4
3.2实时监控与预警机制 4
3.3典型故障案例分析 5
4数据库日志在故障定位中的作用 6
4.1日志关联规则挖掘 6
4.2故障根源追踪技术 7
4.3定位精度提升策略 7
结论 8
参考文献 9
致谢 10
