Apollo: Rapidly Picking the Optimal Cloud Configurations for Big Data Analytics Using a Data-Driven Approach

Author:

Wu Yue-Wen,Xu Yuan-Jia,Wu Heng,Su Lin-Gang,Zhang Wen-Bo,Zhong Hua

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,Computer Science Applications,Hardware and Architecture,Theoretical Computer Science,Software

Reference30 articles.

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2. Alipourfard O, Liu H H, Chen J, Venkataraman S, Yu M, Zhang M. Cherrypick: Adaptively unearthing the best cloud configurations for big data analytics. In Proc. the 14th USENIX Symposium on Networked Systems Design and Implementation, March 2017, pp.469-482.

3. Delimitrou C, Kozyrakis C. QoS-aware scheduling in heterogeneous datacenters with paragon. ACM Transactions on Computer Systems, 2013, 31(4): Article No. 12. https://doi.org/10.1145/2556583.

4. Venkataraman S, Yang Z, Franklin M, Recht B, Stoica I. Ernest: Efficient performance prediction for large-scale advanced analytics. In Proc. the 13th USENIX Symposium on Networked Systems Design and Implementation, March 2016, pp.363-378.

5. Hsu C J, Nair V, Freeh V W, Menzies T. Arrow: Low-level augmented Bayesian optimization for finding the best cloud VM. In Proc. the 38th IEEE International Conference on Distributed Computing Systems, July 2018, pp.660-670. https://doi.org/10.1109/ICDCS.2018.00070.

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