Abstract: Aiming at the problem of extracting network events directly from large-scale network log,a template extraction method based on large-scale network log was proposed.The method can automatically convert the massive and original network logs into log templates,so as to provide important pre-preparation for understanding the network events root causes and preventing the occurrence of network failure.Firstly,the structure of the log is analyzed,and the words in the log are divided into two types:template word and parameter word.Then,from three different angles,the log template extraction is studied respectively.Finally,the actual production data of the Internet company is used,and Rand_index method is used to evaluate the accuracy and validity of the three extraction methods.The results show that the average accuracy of the log templates based on the tag recognition tree model is 99.57%,which is higher than that of the four different types of messages collected from the service cluster.

Key words: Cut words,Extract template,Statistical clustering,Signature tree,Online clustering