摘 要
随着数据规模的快速增长和实时性需求的不断提升，数据库缓存策略在提高查询性能和降低系统延迟方面的重要性日益凸显本研究旨在优化数据库缓存策略并对其性能进行全面评估通过分析现有缓存算法的不足，提出了一种基于自适应预测的混合缓存策略，该策略结合了LRU与LFU的优点，并引入机器学习模型以动态调整缓存替换规则实验采用真实世界的数据集，在多种负载条件下对新策略进行测试结果表明，所提出的缓存策略能够显著提升命中率，减少平均响应时间，相较于传统方法性能提升约20%-35%此外，该策略具备较强的鲁棒性和可扩展性，适用于复杂多变的应用场景本研究的主要贡献在于将智能化元素融入缓存管理机制，为解决动态环境下的高效数据访问问题提供了新的思路关键词：数据库缓存策略; 自适应预测; 混合缓存; 机器学习; 性能优化
Abstract
With the rapid growth of data scale and the increasing demand for real-time performance, the importance of database caching strategies in enhancing query performance and reducing system latency has become increasingly prominent. This study aims to optimize database caching strategies and conduct a comprehensive evaluation of their performance. By analyzing the limitations of existing caching algorithms, an adaptive prediction-based hybrid caching strategy is proposed, which integrates the advantages of LRU and LFU while incorporating machine learning models to dynamically adjust cache replacement rules. Experiments using real-world datasets test the new strategy under various workload conditions. The results demonstrate that the proposed caching strategy significantly improves hit rates and reduces average response times, achieving a performance improvement of approximately 20%-35% compared to traditional methods. Additionally, the strategy exhibits strong robustness and scalability, making it suitable for complex and dynamic application scenarios. The primary contribution of this research lies in integrating intelligent elements into cache management mechanisms, providing a novel approach to addressing efficient data access challenges in dynamic environments.
Key words:Database Cache Strategy; Adaptive Prediction; Hybrid Caching; Machine Learning; Performance Optimization
目 录
中文摘要 I
英文摘要 II
引 言 1
第1章、数据库缓存策略的基础分析 2
1.1、缓存策略的基本概念 2
1.2、数据库缓存的关键技术 2
1.3、缓存策略的分类与应用 3
第2章、缓存优化方法的研究与设计 4
2.1、优化目标与性能指标 4
2.2、常见优化算法分析 4
2.3、自适应缓存优化策略 5
第3章、性能评估体系的构建与实施 6
3.1、性能评估的核心要素 6
3.2、测试环境与实验设计 6
3.3、数据分析与结果验证 7
第4章、缓存策略优化的实际应用案例 8
4.1、实际场景的需求分析 8
4.2、应用中的挑战与解决方案 8
4.3、案例效果与经验总结 9
结 论 10
参考文献 11
