A rule-based data grouping method for personalized log analysis system in big data computing

Nowadays, providing personalized service to customers is one of the main issues in big data services. To provide the personalized service, analyzing various logs and cooperation between data analysts and developers are critical. However, the problem is that overhead can occur when the log data is analyzed due to general characteristics of big data system as well-known 4Vs(Velocity, Various, Value and Volume). Also, generally it is hard for data analysts and developers to work together because they use different interfaces. Therefore, we propose a personalized log analysis system including rule-based data grouping method in order for the improved performance of personalized log analysis and more flexible cooperation between data analysts and developers. The evaluation of the proposed system performs well for cooperation and grouping along with the R SW tool.