@inproceedings{49539fd8361d4e639581b264d1fceb62,
title = "A comparative study of large-scale cluster workload traces via multiview analysis",
abstract = "Understanding the characteristics of workloads of the large-scale Clusters is the key to diagnose the system bottlenecks, making optimal configuration decisions, improving the system throughput and resource usage. Due to the diversity and multiview of the workload traces, featuring the good designs and bottlenecks by analyzing the workloads under realworld scenarios becomes increasingly challenging. This paper introduces a multiview based trace comparative analysis method by comparatively characterizing how the architecture, jobs, tasks, machines, and resources usage were managed among different platforms. A case study is performed which verified the effectiveness of our method by comparatively analyzing two most representative big traces: Google trace and Alibaba 2018 trace. Quantitative findings, together with the performance bottleneck inferences and suggestions are also presented. To the best of our knowledge, we are the first to perform such comparative empirical study on these two traces using a multiview based approach. Our multifaceted analyses and new findings not only reveal insights that we believe are useful for system designers, IT practitioners and users, but also can promote more researches on big trace data comparative analysis in large-scale clusters.",
keywords = "big data analysis, cloud computing, multiview analysis, trace analysis",
author = "Li Ruan and Xiangrong Xu and Limin Xiao and Feng Yuan and Yin Li and Dong Dai",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019 ; Conference date: 10-08-2019 Through 12-08-2019",
year = "2019",
month = aug,
doi = "10.1109/HPCC/SmartCity/DSS.2019.00067",
language = "英语",
series = "Proceedings - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "397--404",
editor = "Zheng Xiao and Yang, \{Laurence T.\} and Pavan Balaji and Tao Li and Keqin Li and Albert Zomaya",
booktitle = "Proceedings - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019",
address = "美国",
}