Research on log data analysis technology based on improved Hadoop

In view of the low computational efficiency of traditional log data analysis technology in processing large amounts of data, this paper proposes a set of log data analysis solutions based on big data technology. A parallel log analysis tool is designed on the Hadoop open source framework, and the anomaly detection of log data is implemented using the MapReduce model. Through experimental demonstration, when analyzing massive log data, the use of big data technology can significantly improve the execution efficiency of anomaly detection.