Efficient search operations in databases are paramount for timely retrieval of information various applications. This research introduces a novel approach, combining dynamicalgorithm1 selection and caching2 strategies, to optimize search performance. The proposed dynamic search algorithm intelligently switches between Binary3 and Interpolation 4 Search based on dataset characteristics, significantly improving efficiency for non-uniformly distributed data. Additionally, a robust caching mechanism5 stores and retrieves previous search results, further enhancing computational efficiency6. Theoretical analysis and extensive experiments demonstrate the effectiveness of the approach, showcasing its potential to revolutionize database performance7 in scenarios with diverse data distributions. This research contributes valuable insights and practical solutions to the realm of database optimization, offering a promising avenue for enhancing search operations in real-world applications

翻译：数据库中的高效搜索操作对于各类应用中的及时信息检索至关重要。本研究提出了一种结合动态算法选择与缓存策略的创新方法，以优化搜索性能。所提出的动态搜索算法能够根据数据集特征在二分搜索与插值搜索之间智能切换，显著提升非均匀分布数据的搜索效率。此外，鲁棒的缓存机制可存储和检索历史搜索结果，进一步增强计算效率。理论分析与大量实验证明了该方法的有效性，展示了其在处理多样化数据分布场景时革新数据库性能的潜力。本研究为数据库优化领域贡献了有价值的见解与实用解决方案，为提升实际应用中的搜索操作提供了有前景的路径。