海洋测绘Issue(4)：78-82,5.DOI:10.3969/j.issn.1671-3044.2025.04.015
一种基于MongoDB的分布式存储与查询方法
A distributed storage and query method based on MongoDB
摘要
Abstract
In order to solve the problem of low data query efficiency in MongoDB database in the face of massive marine environmental data access,this paper proposes a method based on MongoDB distributed storage model and index construction to improve the query efficiency of marine environmental data.Firstly,based on the MongoDB database sharding and partitioning strategy,different types of marine environmental data are distributed and stored,and then according to the spatiotemporal characteristics of marine environmental data,an index structure is proposed,which uses S2 algorithm and Hilbert curve to reduce the data dimension,so as to improve the query efficiency of massive marine environmental data.Experimental results show that compared with MongoDB,the proposed method uses compound indexes to increase the efficiency by 1.65 times and 5 times by range query,which can effectively improve the query efficiency of marine environmental data.关键词
分布式存储/MongoDB数据库/索引构建/S2算法/Hilbert曲线Key words
distributed storage/MongoDB database/index building/S2 algorithm/hilbert curve分类
天文与地球科学引用本文复制引用
李俊杰,范冲,赵丹丹,李盘盘,胡海立..一种基于MongoDB的分布式存储与查询方法[J].海洋测绘,2025,(4):78-82,5.基金项目
湖南省重点领域研发计划(2023SK2012). （2023SK2012）
