USTEP: Unfixed Search Tree for Efficient Log Parsing

Arthur Vervaet, Raja Chiky, Mar Callau-Zori
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引用次数: 6

Abstract

Logs record valuable system information at runtime. They are widely used by data-driven approaches for development and monitoring purposes. Parsing log messages to structure their format is a classic preliminary step for log-mining tasks. As they appear upstream, parsing operations can become a processing time bottleneck for downstream applications. The quality of parsing also has a direct influence on their efficiency. Previous approaches toward online log parsing focused on stateful methods. But an increasing number of tasks ask for real time monitoring. Regarding this problem, we propose USTEP, an online log parsing method based on an evolving tree structure. Evaluation results on a panel of 13 datasets coming from different real-world systems demonstrate USTEP superiority in terms of both effectiveness and robustness when compared to other online methods. We also introduce USTEP-UP, a way of running multiple decentralized instances of USTEP in parallel.
USTEP:用于高效日志解析的不固定搜索树
日志记录了运行时有价值的系统信息。它们被数据驱动的方法广泛用于开发和监测目的。解析日志消息以构建其格式是日志挖掘任务的典型初步步骤。当解析操作出现在上游时,它们可能成为下游应用程序的处理时间瓶颈。解析的质量也直接影响它们的效率。以前的在线日志解析方法侧重于有状态方法。但是越来越多的任务需要实时监控。针对这一问题,我们提出了一种基于进化树结构的在线日志解析方法USTEP。来自不同现实世界系统的13个数据集的评估结果表明,与其他在线方法相比,USTEP在有效性和鲁棒性方面都具有优势。我们还介绍了USTEP- up,一种并行运行多个分散的USTEP实例的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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