[Objective] The real-time statistical analysis system of DSpace logs is designed and implemented to meet the different needs of users, and to make up for lack of DSpace's statistical functions itself. [Context] For the design limitations, the DSpace's statistical functions are simple, rigid form of expression, and can not achieve interactive statistical analysis. [Methods] Use Logstash to collect and analyze DSpace logs, and use ElasticSearch to index the logs. Building QueryDSL to call ElasticSearch Java API to achieve different statistical functions, and show the graphical results with ECharts component. [Results] The real-time statistical analysis system of DSpace logs can get the browse rankings of items, collections and communities, get the download rankings of bitstreams, and get the regional rankings of website access, and so on. The statistics time can be customized by user, and the statistical result can be showed in different forms. [Conclusions] Using Logstash and ElasticSearch to achieve statistical analysis of DSpace logs has many excellences, just like no need to modify the code of DSpace, simple installation and deployment of the components, man-machine interactive query, fast and real-time, and rich forms to show the results.
陈和. 运用开源软件Logstash和ElasticSearch实现DSpace日志实时统计分析[J]. 现代图书情报技术, 2015, 31(5): 88-93.
Chen He. Using Logstash and ElasticSearch to Achieve Real-time Statistical Analysis of DSpace Logs. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2015.05.12.