Open Access Research of Social Network Log Analysis System Based on MongoDB

Abstract: This paper mainly studies the design of an efficient social network log analysis program based on the distribut-ed database, MongoDB. The so-called social network log analysis is to gather and store the log information generated when users access the social network pages, and then transform, clean and excavate. This article compares MongoDB da-tabase with traditional relational database, analyzes its advantages and application scenarios. Its anti-paradigm design due to the nest avoids the association, making queries and storage of the large data efficiently by: storing social network logs in the MongoDB; directly analyzing the logs with its built-in MapReduce programming model, and saving the results of the analysis as files for business people to use. Our study aims to discover the hidden users ' access rules and patterns in the log data by effective data mining of the social network log data, thereby providing helpful information for optimizing website structure and business model