CAJ | 학술논문

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。
수착수거량적불단증가，사용 MongoDB 수거고내치적 skip 화 limit 조합분혈산법효솔저하，성위영향수거고방문성능제승적중요문제。종분석영향분혈사순속도적관건인소입수，제출세립도사순개진산법화 where-limit 산법。통과이론추도화여원산법적실험결과적비교，분석료량충신산법사용장경화우결점。장량충산법응용우실제 Web2.0일지계통응용중，취득료교호적효과。최후，대영향수거분혈적기타인소진행료탐토，이경호적제고 Web 응용성능。
With the increasing amount of data,the efficiency of using the built-in mongo database skip and limit combi-nation 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 al-gorithm,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.