Working with large data sets is increasingly common in research and industry. There are some distributed data analytics solutions like Hadoop, that offer high scalability and fault-tolerance, but they usually lack a user interface and only developers can exploit their functionali- ties. In this paper, we present Radoop, an extension for the RapidMiner data mining tool which provides easy-to-use operators for running dis- tributed processes on Hadoop. We describe integration and development details and provide runtime measurements for several data transforma- tion tasks. We conclude that Radoop is an excellent tool for big data analytics and scales well with increasing data set size and the number of nodes in the cluster.
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