On-line social network mass data storage method based on community division

Abstract

The invention discloses an on-line social network mass data storage method based on community division. With a graph structure of a social network serving as the starting point, firstly, the social network is divided into a celebrity user layer and a common user layer according to node degrees, and then the community division is conducted on each layer through a modularity optimization method. A small group forming strategy is designed to preprocess an initial network, a supernet is formed, and an edge weight optimization scheme is adopted for merging super nodes step by step so as to improve the modularity. After the community division is completed, common user data are stored preferentially, user data of the same community are stored in the same server node, celebrity user data are preferentially considered to be stored in the server with the most fans, and then the celebrity user data are secondly considered to be stored in the server node where the community of the celebrity user data are located. By the design that the celebrity user data are stored in a multi-replication mode, the load of a single server is reduced; since social network data are stored through the community division method, the locality of access can be improved, and communication expenditure can be reduced.

Description

technical field [0001] The invention relates to a data storage method, in particular to a method for storing mass data in an online social network based on community division. Background technique [0002] Web 2.0, which focuses on user-created content, has penetrated into all aspects of people's daily life. A large number of online social networking sites have sprung up rapidly. Foreign ones such as Facebook and Twitter, and domestic ones such as Weibo and Renren.com have become an important platform for people to share and obtain information. main platform. People interact and communicate through social networks, resulting in explosive growth of data and access scale, which poses severe challenges to data storage and management. [0003] The current website architecture basically adopts traditional distributed storage solutions, such as hashing, consistent hashing and other technologies. For example, Twitter uses Gizzard to divide data by mapping a specific range of data...

AI Technical Summary

Problems solved by technology

If a user's friends in the same community of a user in a social network are spread over multiple servers, then query and update operations need to send requests to multiple servers, which is too expensive for a social network with a large number of users

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