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The P2P-based system for the distributed computing of statistics called DuDE is presented. High scalability and failure resilience features of P2P are exploited to achieve a high- performance distributed system, which avoids the bottlenecks of a centralized computing system. To ensure high data availability, a sophisticated algorithm for distributed data storage is integrated. Furthermore, an algorithm for global peer discovery is presented, which allows for finding all data assigned to peers without the need for a central instance. For the realization of DuDE, common working stages of distributed computing are extended to enable a highly scalable computing system based on P2P technology. Generated results from a test system show a nearly perfect linear speedup for distributed computing as well as high processor and memory relief compared to a centralized solution.