2013/07/30 by Zhen Jia, Jia, Zhen, Runlin Zhou +13
Computer Science · #Cloud Computing and Resource Management #FOS: Computer and information sciences #IoT and Edge/Fog Computing #Performance (cs.PF) #Software System Performance and Reliability #cs.PF
paper · pdf · doi:10.48550/arxiv.1307.7943
16 pages, 3 figures
arxiv created 2013/07/30 · openalex publication_date 2013/07/30 · arxiv updated 2013/07/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Now we live in an era of big data, and big data applications are becoming more and more pervasive. How to benchmark data center computer systems running big data applications (in short big data systems) is a hot topic. In this paper, we focus on measuring the performance impacts of diverse applications and scalable volumes of data sets on big data systems. For four typical data analysis applications---an important class of big data applications, we find two major results through experiments: first, the data scale has a significant impact on the performance of big data systems, so we must provide scalable volumes of data sets in big data benchmarks. Second, for the four applications, even all of them use the simple algorithms, the performance trends are different with increasing data scales, and hence we must consider not only variety of data sets but also variety of applications in benchmarking big data systems.