[1]张国华,徐建军,刘丽娟. 基于NoSQL的新农合高效云存储方法[J].计算机技术与发展,2017,27(10):197-200.
　ZHANG Guo-hua,XU Jian-jun,LIU Li-juan. An Efficient Cloud Storage Method with NoSQL for New Rural Cooperative Medical Care[J].,2017,27(10):197-200.
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 基于NoSQL的新农合高效云存储方法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年10期
页码:
197-200
栏目:
应用开发研究
出版日期:
2017-10-10

文章信息/Info

Title:
 An Efficient Cloud Storage Method with NoSQL for New Rural Cooperative Medical Care
文章编号:
1673-629X（2017)10-0197-04
作者:
 张国华; 徐建军; 刘丽娟
 南京师范大学泰州学院
Author(s):
 ZHANG Guo-hua; XU Jian-jun; LIU Li-juan
关键词:
 ; 新农合; MongoDB; 大数据; NoSQL
Keywords:
 ; NRCMS; MongoDB; big data; NoSQL
分类号:
TP311
文献标志码:
A
摘要:
 国内新型农村合作医疗系统(以下简称新农合)大多采用了关系型数据库作为数据存储介质,新农合中的参合、门诊、药品等数据分布在各省厅、县市乃至镇村等医疗卫生服务部门的服务器中.它们的业务数据量增长速度极快,服务器节点也经常变化,所以该方案一直无法突破数据量横向拓展的瓶颈问题.随着数据量的快速增长,该问题对整个新农合系统的影响也愈加突出.为此,提出了另一种大数据存储解决方案,即采用非关系型数据库MongoDB来存储和扩展新农合中的大数据.为进一步验证该方案在新农合应用中的有效性和可行性,进行了非关系数据库MongoDB与关系型数据库两个集群并发与读写能力的对比实验验证.理论分析和实验结果表明,非关系型数据库MongoDB在处理海量数据方面展现出了更好的优越性和适用性,能有效解决新农合系统大数据的横向拓展问题,也能为其他类似信息系统提供理论支撑和技术参考.
Abstract:
 The New Rural Cooperative Medical System ( NRCMS) in China mostly uses the relational database as the data storage medi-um,and the data of participation,clinic, drug in NRCMS is distributed in medical and health services department server in all ministries, counties and towns and villages. Their business data volume is extremely fast in growth rate,and server nodes are often changed,so the program has been unable to break through the bottleneck of the horizontal expansion of the data volume. With the rapid increase in the a-mount of data,the impact of NRCMS is also more prominent. Therefore another solution is proposed with use of non relational database MongoDB for storing and expanding the big data. In order to further verify its effectiveness and feasibility in the new rural cooperative medical system,comparative experiments for verifications of the relationship between the two clusters of non relational database Mon-goDB and relational database is conducted. Theoretical analysis and experimental results show that the MongoDB in the treatment of mas-sive data indicates better superiority and applicability in solving the expansion of horizontal big data medical system and has provided the-oretical support and technical reference for other similar information systems.

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更新日期/Last Update: 2017-11-24