图模型在智慧校园数据中心的应用

Application of Graph Model in Smart Campus Data Center

针对智慧校园数据平台中的数据来源不统一、数据质量不高、数据规模较大的问题,引入了图模型的建模方式。虽然主流结构化数据库建模方式的数据管理和操作更加可靠和成熟,可以确保数据的完整性和一致性,但对多样性和复杂性数据查询性能较差。区别于结构化的数据库建模方式,图模型重点聚焦数据间的联系而非数据本身,从而具备能够轻松处理复杂、多层级、非结构化的数据的能力。研究分析两种建模方式在智慧校园数据中心中的应用,并通过实验对比两种方式的查询性能,实验结果表明:与传统关系型建模相比,图模型在数据分类复杂且经常需要多分类连接查询的情况下能够更快地查询和遍历数据,具备更优秀的查询效率,能很好地解决智慧校园数据查询性能较差的问题。

In response to the problems of inconsistent data sources,low data quality and large data scale in the smart campus data platform,a graph modeling approach has been introduced.Although the data management and operation of mainstream structured database modeling methods are more reliable and mature,ensuring data integrity and consistency,their performance in querying diverse and complex data is poor.Unlike structured database modeling methods,graph models focus on the connections between data rather than the data itself,thus possessing the ability to easily handle complex,multi-level,and unstructured data.The application of the two modeling methods in the smart campus data center is studied and analyzed,and the query performance of the two methods is compared through experiments.The experimental results show that compared with the traditional relational modeling,the graph model can query and traverse the data faster and has better query efficiency when the data classification is complex and multiple classification join queries are often required.It solves the problem of poor query performance of smart campus data.