Real-time analysis of NetFlow data for generating network traffic statistics using Apache Spark

Milan Cermák, Tomás Jirsík, Martin Laštovička
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引用次数: 8

Abstract

In this paper, we present a framework for the real-time generation of network traffic statistics on Apache Spark Streaming, a modern distributed stream processing system. Our previous results showed that stream processing systems provide enough throughput to process a large volume of NetFlow data and hence they are suitable for network traffic monitoring. This paper describes the integration of Apache Spark Streaming into a current network monitoring architecture. We prove that it is possible to implement the same basic methods for NetFlow data analysis in the stream processing framework as in the traditional ones. Moreover, our stream processing implementation discovers new information which is not available when using traditional network monitoring approaches.
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使用Apache Spark实时分析NetFlow数据,生成网络流量统计数据
在本文中,我们提出了一个在Apache Spark Streaming(一个现代分布式流处理系统)上实时生成网络流量统计数据的框架。我们之前的研究结果表明,流处理系统提供了足够的吞吐量来处理大量的NetFlow数据,因此它们适合于网络流量监控。本文描述了Apache Spark Streaming与当前网络监控体系结构的集成。我们证明了在流处理框架中实现与传统流处理框架相同的NetFlow数据分析基本方法是可能的。此外,我们的流处理实现发现了传统网络监控方法无法获得的新信息。
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