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Internet traffic measurement and analysis has become a significantly challenging job because large packet trace files captured on fast links could not be easily handled on a single server with limited computing and memory resources. Hadoop is a popular open-source cloud computing platform that provides a software programming framework called MapReduce and the distributed filesystem, HDFS, which are useful for analyzing a large data set. Therefore, in this paper, we present a Hadoop-based packet processing tool that provides scalability for a large data set by harnessing MapReduce and HDFS. To tackle large packet trace files in Hadoop efficiently, we devised a new binary input format, called PcapInputFormat, hiding the complexity of processing binary-formatted packet data and parsing each packet record. We also designed efficient traffic analysis MapReduce job models consisting of map and …