MongoDB分页技术改进与优化

随着数据量的不断增加，使用MongoDB数据库内置的skip和limit组合分页算法效率低下，成为影响数据库访问性能提升的重要问题。从分析影响分页查询速度的关键因素入手，提出细粒度查询改进算法和where-limit算法。通过理论推导和与原算法的实验结果的比较，分析了两种新算法使用场景和优缺点。将两种算法应用于实际Web2.0日志系统应用中，取得了较好的效果。最后，对影响数据分页的其它因素进行了探讨，以更好的提高Web应用性能。

Improvement and Optimization on MongoDB Paging Technology

With the increasing amount of data, the efficiency of using the built-in mongo database skip and limit combination paging algorithm is low, which has become an important issue affecting the performance of database access. From the analysis on the key factors affecting the speed paging query, this paper proposed the fine-grained query improved algorithm and where-limit algorithm. Through theoretical deduction and comparison of the experimental results with the original algorithm, this paper analyzed the usage scenarios and the advantages and disadvantages of two kinds of new algorithm. The two algorithms were applied to practical application of Web2.0 logging system, and achieved good results. Finally, other factors affecting the data pages were discussed in order to improve Web application performance better.