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Now we live in an era of big data, and big data applications are becomingmore and more pervasive. How to benchmark data center computer systems runningbig data applications (in short big data systems) is a hot topic. In thispaper, we focus on measuring the performance impacts of diverse applicationsand scalable volumes of data sets on big data systems. For four typical dataanalysis applications---an important class of big data applications, we findtwo major results through experiments: first, the data scale has a significantimpact on the performance of big data systems, so we must provide scalablevolumes of data sets in big data benchmarks. Second, for the four applications,even all of them use the simple algorithms, the performance trends aredifferent with increasing data scales, and hence we must consider not onlyvariety of data sets but also variety of applications in benchmarking big datasystems.

The Implications of Diverse Applications and Scalable Data Sets in Benchmarking Big Data Systems