USTEP: Structuration des logs en flux grâce à un arbre de recherche évolutif

Arthur Vervaet, Raja Chiky, Mar Callau-Zori
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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. Here, we propose USTEP, an online log parsing method based on an evolving tree structure. Evaluation results on a wide panel of datasets coming from different real-world systems demonstrate USTEP superiority in terms of both effectiveness and robustness when compared to other online methods.
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USTEP:通过可扩展的搜索树构建流日志
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。本文提出了一种基于演化树结构的在线日志解析方法USTEP。对来自不同现实世界系统的广泛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。
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