Analyzing the impact of various parameters on job scheduling in the Google cluster dataset

Author:

Shahmirzadi Danyal,Khaledian Navid,Rahmani Amir Masoud

Publisher

Springer Science and Business Media LLC

Reference32 articles.

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2. Rosà, A., Chen, L.Y., Birke, R., Binder, W.: Demystifying casualties of evictions in big data priority scheduling. ACM SIGMETRICS Perform. Eval. Rev. 42(4), 12–21 (2015)

3. Chen, X., Lu, C. D., Pattabiraman, K.: Failure analysis of jobs in compute clouds: a Google cluster case study. In 2014 IEEE 25th International Symposium on Software Reliability Engineering (pp. 167–177). IEEE. (2014)

4. Rzadca, K., Findeisen, P., Swiderski, J., Zych, P., Broniek, P., Kusmierek, J., Wilkes, J.: Autopilot: workload autoscaling at Google. In proceedings of the fifteenth european conference on computer systems (pp. 1–16), (2020)

5. Anil, R., Capan, G., Drost-Fromm, I., Dunning, T., Friedman, E., Grant, T., Yılmazel, Ö.: Apache mahout: machine learning on distributed dataflow systems. J. Mach. Learn. Res. 21(127), 1–6 (2020)

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