LogMerge——面向多语法日志的通用异常检测机制研究

论文如下： 题目：面向多语法日志的通用异常检测机制研究

源码细节如下.

Requirement:

Python: 3.6  
Tenssorflow: 1.9.0 
keras:2.2.4
numpy:1.17.2

代码结构:

├── model                   # 聚类模型权重
├── codes                   # 代码
├── data                    # 数据集（以Hadoop数据集为例，其他数据整理成相应格式即可）
├── result                  # 结果  
├── README.md               # README文件

输入数据样例：

2015-10-17 15:37:56,547 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: Created MRAppMaster for application appattempt_1445062781478_0011_000001 2015-10-17 15:37:56,899 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: Executing with tokens: 2015-10-17 15:37:56,900 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: Kind: YARN_AM_RM_TOKEN, Service: , Ident: (appAttemptId { application_id { id: 11 cluster_timestamp: 1445062781478 } attemptId: 1 } keyId: 471522253) 2015-10-17 15:37:57,036 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: Using mapred newApiCommitter. 2015-10-17 15:37:57,634 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: OutputCommitter set in config null 2015-10-17 15:37:57,720 INFO [main] org.apache.hadoop.mapreduce.v2.app.MRAppMaster: OutputCommitter is org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter

结果样例：

p:0.5069444444444444 r:0.6224806201550388 f1:0.558803061934586

简单运行

1. git clone https://github.com/Logs2019/LogMerge.git
2. cd codes
3. bash train.sh or bash predict.sh