From be4fa3e9cce95cd9015f0e34fcb0b78f28f5d20e Mon Sep 17 00:00:00 2001 From: zhujiem Date: Tue, 18 Jul 2023 15:04:48 +0800 Subject: [PATCH] Update logparser v1.0.0 to support Python 3 compatibility * Fix PRs: fix #86, fix #85, #83, #80, #78, #65, #57, #53, #52, #51, #49 * Fix issues: #98, #79, #72, #84, #75, #71, #69, #56, #50, #45, #16, #82 --- .gitignore | 1 - CITATION | 18 +- LICENSE | 328 +- README.md | 161 +- THIRD_PARTIES.md | 9 + benchmark/AEL_benchmark.py | 164 - benchmark/Drain_benchmark.py | 163 - benchmark/IPLoM_benchmark.py | 164 - benchmark/LFA_benchmark.py | 131 - benchmark/LKE_benchmark.py | 148 - benchmark/Lenma_benchmark.py | 151 - benchmark/LogCluster_benchmark.py | 147 - benchmark/LogMine_benchmark.py | 180 - benchmark/LogSig_benchmark.py | 145 - benchmark/MoLFI_benchmark.py | 131 - benchmark/SHISO_benchmark.py | 197 - benchmark/SLCT_benchmark.py | 148 - benchmark/Spell_benchmark.py | 148 - data/README.md | 18 + data/loghub/LICENSE | 1 - data/loghub/Mac/Mac.log | 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data/loghub_2k_corrected/Apache/Apache_2k.log_templates_corrected.csv create mode 100644 data/loghub_2k_corrected/BGL/BGL_2k.log create mode 100644 data/loghub_2k_corrected/BGL/BGL_2k.log_structured.csv create mode 100644 data/loghub_2k_corrected/BGL/BGL_2k.log_structured_corrected.csv create mode 100644 data/loghub_2k_corrected/BGL/BGL_2k.log_templates.csv create mode 100644 data/loghub_2k_corrected/BGL/BGL_2k.log_templates_corrected.csv create mode 100644 data/loghub_2k_corrected/HDFS/HDFS_2k.log create mode 100644 data/loghub_2k_corrected/HDFS/HDFS_2k.log_structured.csv create mode 100644 data/loghub_2k_corrected/HDFS/HDFS_2k.log_structured_corrected.csv create mode 100644 data/loghub_2k_corrected/HDFS/HDFS_2k.log_templates.csv create mode 100644 data/loghub_2k_corrected/HDFS/HDFS_2k.log_templates_corrected.csv create mode 100644 data/loghub_2k_corrected/HPC/HPC_2k.log create mode 100644 data/loghub_2k_corrected/HPC/HPC_2k.log_structured.csv create mode 100644 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data/loghub_2k_corrected/HealthApp/HealthApp_2k.log_templates_corrected.csv create mode 100644 data/loghub_2k_corrected/Linux/Linux_2k.log create mode 100644 data/loghub_2k_corrected/Linux/Linux_2k.log_structured.csv create mode 100644 data/loghub_2k_corrected/Linux/Linux_2k.log_structured_corrected.csv create mode 100644 data/loghub_2k_corrected/Linux/Linux_2k.log_templates.csv create mode 100644 data/loghub_2k_corrected/Linux/Linux_2k.log_templates_corrected.csv create mode 100644 data/loghub_2k_corrected/Mac/Mac_2k.log create mode 100644 data/loghub_2k_corrected/Mac/Mac_2k.log_structured.csv create mode 100644 data/loghub_2k_corrected/Mac/Mac_2k.log_structured_corrected.csv create mode 100644 data/loghub_2k_corrected/Mac/Mac_2k.log_templates.csv create mode 100644 data/loghub_2k_corrected/Mac/Mac_2k.log_templates_corrected.csv create mode 100644 data/loghub_2k_corrected/OpenSSH/OpenSSH_2k.log create mode 100644 data/loghub_2k_corrected/OpenSSH/OpenSSH_2k.log_structured.csv create 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data/loghub_2k_corrected/Proxifier/Proxifier_2k.log_templates.csv create mode 100644 data/loghub_2k_corrected/Proxifier/Proxifier_2k.log_templates_corrected.csv create mode 100644 data/loghub_2k_corrected/Spark/Spark_2k.log create mode 100644 data/loghub_2k_corrected/Spark/Spark_2k.log_structured.csv create mode 100644 data/loghub_2k_corrected/Spark/Spark_2k.log_structured_corrected.csv create mode 100644 data/loghub_2k_corrected/Spark/Spark_2k.log_templates.csv create mode 100644 data/loghub_2k_corrected/Spark/Spark_2k.log_templates_corrected.csv create mode 100644 data/loghub_2k_corrected/Thunderbird/Thunderbird_2k.log create mode 100644 data/loghub_2k_corrected/Thunderbird/Thunderbird_2k.log_structured.csv create mode 100644 data/loghub_2k_corrected/Thunderbird/Thunderbird_2k.log_structured_corrected.csv create mode 100644 data/loghub_2k_corrected/Thunderbird/Thunderbird_2k.log_templates.csv create mode 100644 data/loghub_2k_corrected/Thunderbird/Thunderbird_2k.log_templates_corrected.csv create mode 100644 data/loghub_2k_corrected/Windows/Windows_2k.log create mode 100644 data/loghub_2k_corrected/Windows/Windows_2k.log_structured.csv create mode 100644 data/loghub_2k_corrected/Windows/Windows_2k.log_structured_corrected.csv create mode 100644 data/loghub_2k_corrected/Windows/Windows_2k.log_templates.csv create mode 100644 data/loghub_2k_corrected/Windows/Windows_2k.log_templates_corrected.csv create mode 100644 data/loghub_2k_corrected/Zookeeper/Zookeeper_2k.log create mode 100644 data/loghub_2k_corrected/Zookeeper/Zookeeper_2k.log_structured.csv create mode 100644 data/loghub_2k_corrected/Zookeeper/Zookeeper_2k.log_structured_corrected.csv create mode 100644 data/loghub_2k_corrected/Zookeeper/Zookeeper_2k.log_templates.csv create mode 100644 data/loghub_2k_corrected/Zookeeper/Zookeeper_2k.log_templates_corrected.csv create mode 100644 data/test_log/unknow.log delete mode 100644 demo/AEL_demo.py delete mode 100644 demo/LFA_demo.py delete mode 100644 demo/SLCT_demo.py delete mode 100644 demo/logmatch_demo.py delete mode 100644 docs/img/accuracy.png create mode 100644 docs/img/example.jpg delete mode 100644 docs/img/example.png delete mode 100644 docs/img/parsers.png create mode 100644 example/parse_your_own_logs.py create mode 100644 logparser/AEL/benchmark.py create mode 100644 logparser/AEL/demo.py create mode 100644 logparser/AEL/requirements.txt create mode 100644 logparser/Drain/benchmark.py rename demo/Drain_demo.py => logparser/Drain/demo.py (62%) create mode 100644 logparser/Drain/demo_result/HDFS_2k.log_structured.csv create mode 100644 logparser/Drain/demo_result/HDFS_2k.log_templates.csv create mode 100644 logparser/Drain/requirements.txt create mode 100644 logparser/IPLoM/benchmark.py rename demo/IPLoM_demo.py => logparser/IPLoM/demo.py (57%) create mode 100644 logparser/IPLoM/requirements.txt create mode 100644 logparser/LFA/benchmark.py create mode 100644 logparser/LFA/demo.py create mode 100644 logparser/LFA/requirements.txt create mode 100644 logparser/LKE/benchmark.py rename demo/LKE_demo.py => logparser/LKE/demo.py (51%) create mode 100644 logparser/LKE/requirements.txt delete mode 100644 logparser/LenMa/LenMa.py create mode 100644 logparser/LenMa/benchmark.py rename demo/LenMa_demo.py => logparser/LenMa/demo.py (51%) create mode 100644 logparser/LenMa/requirements.txt rename logparser/LenMa/{templateminer => src}/LICENSE (100%) create mode 100644 logparser/LenMa/src/LenMa.py rename logparser/LenMa/{templateminer => src}/__init__.py (100%) rename logparser/LenMa/{templateminer => src}/lenma_template.py (79%) rename logparser/LenMa/{templateminer => src}/template.py (65%) delete mode 100644 logparser/LogCluster/LogCluster.py create mode 100644 logparser/LogCluster/benchmark.py rename demo/LogCluster_demo.py => logparser/LogCluster/demo.py (53%) create mode 100644 logparser/LogCluster/requirements.txt create mode 100644 logparser/LogCluster/src/COPYING create mode 100644 logparser/LogCluster/src/LogCluster.py rename logparser/{MoLFI/main => LogCluster/src}/__init__.py (100%) rename logparser/LogCluster/{ => src}/logcluster.pl (100%) create mode 100644 logparser/LogMine/benchmark.py rename demo/LogMine_demo.py => logparser/LogMine/demo.py (59%) create mode 100644 logparser/LogMine/requirements.txt rename logparser/LogMine/{ => src}/LogMine.py (53%) rename logparser/{MoLFI/main/org => LogMine/src}/__init__.py (100%) rename logparser/LogMine/{ => src}/alignment.py (92%) create mode 100644 logparser/LogSig/benchmark.py rename demo/LogSig_demo.py => logparser/LogSig/demo.py (52%) create mode 100644 logparser/LogSig/requirements.txt delete mode 100644 logparser/MoLFI/MoLFI.py create mode 100644 logparser/MoLFI/benchmark.py rename demo/MoLFI_demo.py => logparser/MoLFI/demo.py (53%) delete mode 100644 logparser/MoLFI/setup.py create mode 100644 logparser/MoLFI/src/LICENSE rename logparser/MoLFI/{ => src}/Makefile (100%) create mode 100644 logparser/MoLFI/src/MoLFI.py rename logparser/MoLFI/{main/org/core => src}/__init__.py (100%) rename logparser/MoLFI/{ => src}/definitions.py (100%) rename logparser/MoLFI/{main/org/core/chromosome => src/main}/__init__.py (100%) rename logparser/MoLFI/{main/org/core/fitness => src/main/org}/__init__.py (100%) rename logparser/MoLFI/{main/org/core/metaheuristics => src/main/org/core}/__init__.py (100%) rename logparser/MoLFI/{main/org/core/operators => src/main/org/core/chromosome}/__init__.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/chromosome/chromosome.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/chromosome/template.py (100%) rename logparser/MoLFI/{main/org/core/post_process => src/main/org/core/fitness}/__init__.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/fitness/objectives2D.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/metaheuristics/NSGA_II_2D.py (100%) rename logparser/MoLFI/{main/org/core/utility => src/main/org/core/metaheuristics}/__init__.py (100%) rename logparser/MoLFI/{main/org/core/validation => src/main/org/core/operators}/__init__.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/operators/crossover.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/operators/mutation.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/operators/mutation_100cov.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/operators/selection.py (100%) rename logparser/MoLFI/{test => src/main/org/core/post_process}/__init__.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/post_process/post_process_chromosomes.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/utility/Chromosome_Generator.py (100%) rename logparser/MoLFI/{test/org => src/main/org/core/utility}/__init__.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/utility/chromosome_corrections.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/utility/log_file_reader.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/utility/log_message_adaptation.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/utility/match_utility.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/utility/message.py (100%) rename logparser/MoLFI/{test/org/core => src/main/org/core/validation}/__init__.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/validation/oracle.py (100%) rename logparser/MoLFI/{ => src}/main/org/core/validation/validate_chromosomes.py (100%) rename logparser/MoLFI/{ => src}/validation.py (100%) delete mode 100644 logparser/MoLFI/test/org/core/chromosome/test_chromosome.py delete mode 100644 logparser/MoLFI/test/org/core/chromosome/test_template.py delete mode 100644 logparser/MoLFI/test/org/core/fitness/__init__.py delete mode 100644 logparser/MoLFI/test/org/core/fitness/test_objectives2D.py delete mode 100644 logparser/MoLFI/test/org/core/operators/__init__.py delete mode 100644 logparser/MoLFI/test/org/core/operators/test_crossover.py delete mode 100644 logparser/MoLFI/test/org/core/operators/test_mutation.py delete mode 100644 logparser/MoLFI/test/org/core/operators/test_mutation_100cov.py delete mode 100644 logparser/MoLFI/test/org/core/post_process/__init__.py delete mode 100644 logparser/MoLFI/test/org/core/post_process/test_post_process_chromosome.py delete mode 100644 logparser/MoLFI/test/org/core/test_validation/__init__.py delete mode 100644 logparser/MoLFI/test/org/core/test_validation/test_oracle.py delete mode 100644 logparser/MoLFI/test/org/core/test_validation/test_validate_chromosome.py delete mode 100644 logparser/MoLFI/test/org/core/utility/__init__.py delete mode 100644 logparser/MoLFI/test/org/core/utility/test_chromosome_corrections.py delete mode 100644 logparser/MoLFI/test/org/core/utility/test_chromosome_generator.py delete mode 100644 logparser/MoLFI/test/org/core/utility/test_log_message_adaptation.py delete mode 100644 logparser/MoLFI/test/org/core/utility/test_match_utility.py delete mode 100644 logparser/MoLFI/test/org/core/utility/test_message.py delete mode 100644 logparser/MoLFI/test/resources/oracle_test.txt create mode 100644 logparser/SHISO/benchmark.py rename demo/SHISO_demo.py => logparser/SHISO/demo.py (53%) create mode 100644 logparser/SHISO/requirements.txt delete mode 100644 logparser/SLCT/SLCT.py create mode 100644 logparser/SLCT/benchmark.py create mode 100644 logparser/SLCT/demo.py create mode 100644 logparser/SLCT/requirements.txt create mode 100644 logparser/SLCT/src/COPYING create mode 100644 logparser/SLCT/src/SLCT.py rename logparser/{MoLFI/test/org/core/chromosome => SLCT/src}/__init__.py (100%) rename logparser/SLCT/{ => src}/cslct.c (100%) rename logparser/SLCT/{ => src}/cslct.h (100%) create mode 100644 logparser/Spell/benchmark.py rename demo/Spell_demo.py => logparser/Spell/demo.py (50%) create mode 100644 logparser/Spell/requirements.txt create mode 100644 logparser/logmatch/README.md create mode 100644 logparser/logmatch/demo.py create mode 100644 logparser/logmatch/requirements.txt create mode 100644 logparser/version.py create mode 100644 requirements.txt create mode 100644 tests/test_all.sh delete mode 100644 tests/test_py2.sh delete mode 100644 tests/test_py3.sh diff --git a/.gitignore b/.gitignore index 8ad09ebf..15a8045b 100644 --- a/.gitignore +++ b/.gitignore @@ -1,6 +1,5 @@ # Self-defined *result/ -slct # Byte-compiled / optimized / DLL files __pycache__/ diff --git a/CITATION b/CITATION index 506b041e..777200bf 100644 --- a/CITATION +++ b/CITATION @@ -1,4 +1,4 @@ -@inproceedings{logparser, +@inproceedings{Logparser, author = {Jieming Zhu and Shilin He and Jinyang Liu and @@ -10,5 +10,17 @@ booktitle = {Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE)}, pages = {121--130}, - publisher = {{IEEE} / {ACM}}, - year = {2019}} \ No newline at end of file + year = {2019}} + +@inproceedings{DSN16, + author = {Pinjia He and + Jieming Zhu and + Shilin He and + Jian Li and + Michael R. Lyu}, + title = {An Evaluation Study on Log Parsing and Its Use in Log Mining}, + booktitle = {Annual {IEEE/IFIP} International Conference on Dependable Systems + and Networks (DSN)}, + pages = {654--661}, + year = {2016} +} \ No newline at end of file diff --git a/LICENSE b/LICENSE index 853c895d..cab27047 100644 --- a/LICENSE +++ b/LICENSE @@ -1,22 +1,308 @@ -MIT License - -Copyright (c) 2018-2023 LOGPAI Team - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. 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This section summarizes their copyrights and licenses. + ----------------------------------------------------------------------- + + SLCT source code: + http://ristov.github.io/slct/ + + Copyright (C) 2003-2007 Risto Vaarandi + + This program is free software; you can redistribute it and/or + modify it under the terms of the GNU General Public License + as published by the Free Software Foundation; either version 2 + of the License, or (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program; if not, write to the Free Software + Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. + + ----------------------------------------------------------------------- + + LogCluster source code: + https://github.com/ristov/logcluster + + Copyright (C) 2015-2019 Risto Vaarandi + + This program is free software; you can redistribute it and/or + modify it under the terms of the GNU General Public License + as published by the Free Software Foundation; either version 2 + of the License, or (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program; if not, write to the Free Software + Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. + + ----------------------------------------------------------------------- + + LenMa source code: + https://github.com/keiichishima/templateminer + + Copyright (c) 2016, IIJ Innovation Institute, Inc. + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + + 1. Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + 2. 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Thus, it is licensed under GNU General + Public License. Python implementation to Smith-Waterman Algorithm for + Homework 1 of Bioinformatics class. + Forrest Bao, Sept. 26 diff --git a/README.md b/README.md index cf6dfb59..26cbbc37 100644 --- a/README.md +++ b/README.md @@ -1,79 +1,128 @@ -

+

+# Logparser -# Logparser -[![Documentation Status](https://readthedocs.org/projects/logparser/badge/?version=latest)](https://logparser.readthedocs.io/en/latest/?badge=latest) -[![license](https://img.shields.io/badge/license-MIT-green.svg)](./LICENSE.md) +
+Python version +Pypi version +Downloads +License +
+
-Logparser provides a toolkit and benchmarks for automated log parsing, which is a crucial step towards structured log analytics. By applying logparser, users can automatically learn event templates from unstructured logs and convert raw log messages into a sequence of structured events. In the literature, the process of log parsing is sometimes refered to as message template extraction, log key extraction, or log message clustering. +
+ +
-


An illustrative example of log parsing

+Logparser provides a machine learning toolkit and benchmarks for automated log parsing, which is a crucial step for structured log analytics. By applying logparser, users can automatically extract event templates from unstructured logs and convert raw log messages into a sequence of structured events. The process of log parsing is also known as message template extraction, log key extraction, or log message clustering in the literature. -:point_right: Read the docs: https://logparser.readthedocs.io +


An example of log parsing

-:telescope: If you use any of our tools or benchmarks in your research for publication, please kindly cite the following papers. -+ [**ICSE'19**] Jieming Zhu, Shilin He, Jinyang Liu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu. [Tools and Benchmarks for Automated Log Parsing](https://arxiv.org/pdf/1811.03509.pdf). *International Conference on Software Engineering (ICSE)*, 2019. -+ [**DSN'16**] Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu. [An Evaluation Study on Log Parsing and Its Use in Log Mining](https://jiemingzhu.github.io/pub/pjhe_dsn2016.pdf). *IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)*, 2016. +### 🌈 New updates + ++ Since the first release of logparser, many PRs and issues have been submitted due to incompatibility with Python 3. Finally, we update logparser v1.0.0 with support for Python 3. Thanks for all the contributions! ([#PR86](https://github.com/logpai/logparser/pull/86), [#PR85](https://github.com/logpai/logparser/pull/85), [#PR83](https://github.com/logpai/logparser/pull/83), [#PR80](https://github.com/logpai/logparser/pull/80), [#PR65](https://github.com/logpai/logparser/pull/65), [#PR57](https://github.com/logpai/logparser/pull/57), [#PR53](https://github.com/logpai/logparser/pull/53), [#PR52](https://github.com/logpai/logparser/pull/52), [#PR51](https://github.com/logpai/logparser/pull/51), [#PR49](https://github.com/logpai/logparser/pull/49), [#PR18](https://github.com/logpai/logparser/pull/18), [#PR22](https://github.com/logpai/logparser/pull/22)) ++ We build the logpai package wheel, which contains logparser as a submodule. Please install it via `pip install logpai`. ++ We refactor the code structure and beautify the code via the Python code formatter black. + +### Log parsers available: + +| Publication | Parser | Paper Reference | +| :---: | :---: | :--- | +| IPOM'03 | [SLCT](https://github.com/logpai/logparser/tree/main/logparser/SLCT#slct) | [A Data Clustering Algorithm for Mining Patterns from Event Logs](https://ristov.github.io/publications/slct-ipom03-web.pdf), by Risto Vaarandi. | +| QSIC'08 | [AEL](https://github.com/logpai/logparser/tree/main/logparser/AEL#ael) | [Abstracting Execution Logs to Execution Events for Enterprise Applications](https://www.researchgate.net/publication/4366728_Abstracting_Execution_Logs_to_Execution_Events_for_Enterprise_Applications_Short_Paper), by Zhen Ming Jiang, Ahmed E. Hassan, Parminder Flora, Gilbert Hamann. | +| KDD'09 | [IPLoM](https://github.com/logpai/logparser/tree/main/logparser/IPLoM#iplom) | [Clustering Event Logs Using Iterative Partitioning](https://web.cs.dal.ca/~makanju/publications/paper/kdd09.pdf), by Adetokunbo Makanju, A. Nur Zincir-Heywood, Evangelos E. Milios. | +| ICDM'09 | [LKE](https://github.com/logpai/logparser/tree/main/logparser/LKE#lke) | [Execution Anomaly Detection in Distributed Systems through Unstructured Log Analysis](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/DM790-CR.pdf), by Qiang Fu, Jian-Guang Lou, Yi Wang, Jiang Li. [**Microsoft**] | +| MSR'10 | [LFA](https://github.com/logpai/logparser/tree/main/logparser/LFA#lfa) | [Abstracting Log Lines to Log Event Types for Mining Software System Logs](http://www.se.rit.edu/~mei/publications/pdfs/Abstracting-Log-Lines-to-Log-Event-Types-for-Mining-Software-System-Logs.pdf), by Meiyappan Nagappan, Mladen A. Vouk. | +| CIKM'11 | [LogSig](https://github.com/logpai/logparser/tree/main/logparser/LogSig#logsig) | [LogSig: Generating System Events from Raw Textual Logs](https://users.cs.fiu.edu/~taoli/pub/liang-cikm2011.pdf), by Liang Tang, Tao Li, Chang-Shing Perng. | +| SCC'13 | [SHISO](https://github.com/logpai/logparser/tree/main/logparser/SHISO#shiso) | [Incremental Mining of System Log Format](http://ieeexplore.ieee.org/document/6649746/), by Masayoshi Mizutani. | +| CNSM'15 | [LogCluster](https://github.com/logpai/logparser/tree/main/logparser/LogCluster#logcluster) | [LogCluster - A Data Clustering and Pattern Mining Algorithm for Event Logs](http://dl.ifip.org/db/conf/cnsm/cnsm2015/1570161213.pdf), by Risto Vaarandi, Mauno Pihelgas. | +| CNSM'15 | [LenMa](https://github.com/logpai/logparser/tree/main/logparser/LenMa#lenma) | [Length Matters: Clustering System Log Messages using Length of Words](https://arxiv.org/pdf/1611.03213.pdf), by Keiichi Shima. | +| CIKM'16 | [LogMine](https://github.com/logpai/logparser/tree/main/logparser/LogMine#logmine) | [LogMine: Fast Pattern Recognition for Log Analytics](http://www.cs.unm.edu/~mueen/Papers/LogMine.pdf), by Hossein Hamooni, Biplob Debnath, Jianwu Xu, Hui Zhang, Geoff Jiang, Adbullah Mueen. [**NEC**] | +| ICDM'16 | [Spell](https://github.com/logpai/logparser/tree/main/logparser/Spell#spell) | [Spell: Streaming Parsing of System Event Logs](https://www.cs.utah.edu/~lifeifei/papers/spell.pdf), by Min Du, Feifei Li. | +| ICWS'17 | [Drain](https://github.com/logpai/logparser/tree/main/logparser/Drain#drain) | [Drain: An Online Log Parsing Approach with Fixed Depth Tree](https://jiemingzhu.github.io/pub/pjhe_icws2017.pdf), by Pinjia He, Jieming Zhu, Zibin Zheng, and Michael R. Lyu.| +| ICPC'18 | [MoLFI](https://github.com/logpai/logparser/tree/main/logparser/MoLFI#molfi) | [A Search-based Approach for Accurate Identification of Log Message Formats](http://publications.uni.lu/bitstream/10993/35286/1/ICPC-2018.pdf), by Salma Messaoudi, Annibale Panichella, Domenico Bianculli, Lionel Briand, Raimondas Sasnauskas. | + +:bulb: Welcome to submit a PR to push your parser code to logparser and add your paper to the table. + +### Installation + +We recommend installing the logparser package and requirements via pypi. -### Log parsers currently available: - -| Tools | References | -| :--- | :--- | -| SLCT | [**IPOM'03**] [A Data Clustering Algorithm for Mining Patterns from Event Logs](http://www.quretec.com/u/vilo/edu/2003-04/DM_seminar_2003_II/ver1/P12/slct-ipom03-web.pdf), by Risto Vaarandi. | -| AEL | [**QSIC'08**] [Abstracting Execution Logs to Execution Events for Enterprise Applications](https://www.researchgate.net/publication/4366728_Abstracting_Execution_Logs_to_Execution_Events_for_Enterprise_Applications_Short_Paper), by Zhen Ming Jiang, Ahmed E. Hassan, Parminder Flora, Gilbert Hamann.
[**JSME'08**] [An Automated Approach for Abstracting Execution Logs to Execution Events](http://www.cse.yorku.ca/~zmjiang/publications/jsme2008.pdf), by Zhen Ming Jiang, Ahmed E. Hassan, Gilbert Hamann, Parminder Flora. | -| IPLoM | [**KDD'09**] [Clustering Event Logs Using Iterative Partitioning](https://web.cs.dal.ca/~makanju/publications/paper/kdd09.pdf), by Adetokunbo Makanju, A. Nur Zincir-Heywood, Evangelos E. Milios.
[**TKDE'12**] [A Lightweight Algorithm for Message Type Extraction in System Application Logs](http://ieeexplore.ieee.org/abstract/document/5936060/), by Adetokunbo Makanju, A. Nur Zincir-Heywood, Evangelos E. Milios. | -| LKE | [**ICDM'09**] [Execution Anomaly Detection in Distributed Systems through Unstructured Log Analysis](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/DM790-CR.pdf), by Qiang Fu, Jian-Guang Lou, Yi Wang, Jiang Li. [**Microsoft**] | -| LFA | [**MSR'10**] [Abstracting Log Lines to Log Event Types for Mining Software System Logs](http://www.se.rit.edu/~mei/publications/pdfs/Abstracting-Log-Lines-to-Log-Event-Types-for-Mining-Software-System-Logs.pdf), by Meiyappan Nagappan, Mladen A. Vouk. | -| LogSig | [**CIKM'11**] [LogSig: Generating System Events from Raw Textual Logs](https://users.cs.fiu.edu/~taoli/pub/liang-cikm2011.pdf), by Liang Tang, Tao Li, Chang-Shing Perng. | -| SHISO | [**SCC'13**] [Incremental Mining of System Log Format](http://ieeexplore.ieee.org/document/6649746/), by Masayoshi Mizutani. | -| LogCluster | [**CNSM'15**] [LogCluster - A Data Clustering and Pattern Mining Algorithm for Event Logs](http://dl.ifip.org/db/conf/cnsm/cnsm2015/1570161213.pdf), by Risto Vaarandi, Mauno Pihelgas. | -| LenMa | [**CNSM'15**] [Length Matters: Clustering System Log Messages using Length of Words](https://arxiv.org/pdf/1611.03213.pdf), by Keiichi Shima. | -| LogMine | [**CIKM'16**] [LogMine: Fast Pattern Recognition for Log Analytics](http://www.cs.unm.edu/~mueen/Papers/LogMine.pdf), by Hossein Hamooni, Biplob Debnath, Jianwu Xu, Hui Zhang, Geoff Jiang, Adbullah Mueen. [**NEC**] | -| Spell | [**ICDM'16**] [Spell: Streaming Parsing of System Event Logs](https://www.cs.utah.edu/~lifeifei/papers/spell.pdf), by Min Du, Feifei Li. | -| Drain | [**ICWS'17**] [Drain: An Online Log Parsing Approach with Fixed Depth Tree](https://jiemingzhu.github.io/pub/pjhe_icws2017.pdf), by Pinjia He, Jieming Zhu, Zibin Zheng, and Michael R. Lyu.
[IBM-Drain3](https://github.com/IBM/Drain3): IBM's upgrade version of Drain in Python 3.6 with additional features. | -| MoLFI | [**ICPC'18**] [A Search-based Approach for Accurate Identification of Log Message Formats](http://publications.uni.lu/bitstream/10993/35286/1/ICPC-2018.pdf), by Salma Messaoudi, Annibale Panichella, Domenico Bianculli, Lionel Briand, Raimondas Sasnauskas. | +``` +pip install logpai==logparserv1.0.0 +``` + +In particular, the package depends on the following requirements. + ++ Python 3.6+ ++ regex 2022.3.2 ++ numpy ++ pandas ++ scipy ++ deap (if using logparser.MoLFI) ++ gcc (if using logparser.SLCT) ### Get started -Code organization: +1. Run the demo: + + For each log parser, we provide a demo to help you get started. Each demo shows the basic usage of a target log parser and the hyper-parameters to configure. For example, the following command shows how to run the demo for Drain. + + ``` + cd logparser/Drain + python demo.py + ``` + After finishing running the demo, you can obtain extracted event templates and parsed structured logs in the result folder. -+ [benchmark](./benchmark): the benchmark scripts to reproduce the evaluation results of log parsing -+ [demo](./demo): the demo files to show how to run logparser on HDFS logs. -+ [logparser](./logparser): the logparser package -+ [logs](./logs): Some log samples and manually parsed structured logs with their templates (ground truth). + + [HDFS_2k.log_templates.csv](https://github.com/logpai/logparser/blob/main/logparser/Drain/demo_result/HDFS_2k.log_templates.csv) + + [HDFS_2k.log_structured.csv](https://github.com/logpai/logparser/blob/main/logparser/Drain/demo_result/HDFS_2k.log_structured.csv) -Please follow the [installation steps](https://logparser.readthedocs.io/en/latest/installation/dependency.html) and [demo](https://logparser.readthedocs.io/en/latest/demo.html) in the docs to get started. +2. Run the benchmark: + + For each log parser, we provide a benchmark script to run log parsing on the [loghub_2k datasets](https://github.com/logpai/logparser/tree/main/data#loghub_2k) for evaluating parsing accuarcy. You can also use [other benchmark datasets for log parsing](https://github.com/logpai/logparser/tree/main/data#datasets). -### Benchmarking results -All the log parsers have been evaluated across 16 different logs available in [loghub](https://github.com/logpai/loghub). We report parsing accuracy as the percentage of accurately parsed log messages. To reproduce the experimental results, please run the [benchmark](./benchmark) scripts. + ``` + cd logparser/Drain + python benchmark.py + ``` -

+3. Parse your own logs: -
- :point_down: Check the detailed bechmarking result table (click to expand) - -

- - In the table, accuracy values above 0.9 are marked in bold, and the best accuracy results achieved are marked with \*. Some of the accuracy values may be lower than what have been reported by previous studies (e.g., Drain, LogMine). The reasons are two-fold: 1) We use a more rigorous accuracy metric which rejects events that are only partially matched. 2) For fairness of comparison, we apply only a few preprocessing regular expressions (e.g., IP or number replacement) to each log parser. Adding more preprocessing rules can boost parsing accuracy, but requires more manual efforts as well. + It is easy to apply logparser to parsing your own log data. To do so, you need to install the logpai package first. Then you can develop your own script following the below code snippet to start log parsing. -
+ ```python + from logparser.Drain import LogParser + input_dir = 'PATH_TO_LOGS/' # The input directory of log file + output_dir = 'result/' # The output directory of parsing results + log_file = 'unknow.log' # The input log file name + log_format = '