使用 Hadoop 进行基于 MapReduce 的日志分析的方法

Hemant Hingave, R. Ingle
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引用次数: 17

摘要

日志是系统运行状态、用户行为、系统操作等信息的主要来源。日志分析系统不仅需要海量、稳定的数据处理能力,还需要在高效、高性能的要求下适应各种场景,而这些都是现有的独立分析工具甚至单一计算框架无法实现的。因此,我们提出了一种结合 Hadoop 和 Map-Reduce 范式的日志分析器。Hadoop 和 MapReduce 编程工具的结合可以在最短的响应时间内提供批量分析,并提高内存计算能力,从而以可用、高效和稳定的方式处理日志。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An approach for MapReduce based log analysis using Hadoop
Log is the main source of system operation status, user behavior, system's actions etc. Log analysis system needs not only the massive and stable data processing ability but also the adaptation to a variety of scenarios under the requirement of efficiency and performance, which can't be achieved from available standalone analysis tools or even single computing framework. Hence we propose a log analyzer with the combination of Hadoop and Map-Reduce paradigm. The joint of Hadoop and MapReduce programming tools makes it possible to provide batch analysis in minimum response time and in-memory computing capacity in order to process log in a high available, efficient and stable way.
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