Computer Science > Distributed, Parallel, and Cluster Computing
arXiv:2211.08227 (cs)
[Submitted on 15 Nov 2022 (v1), last revised 30 Jan 2023 (this version, v2)]
Title:Perona: Robust Infrastructure Fingerprinting for Resource-Efficient Big Data Analytics
View a PDF of the paper titled Perona: Robust Infrastructure Fingerprinting for Resource-Efficient Big Data Analytics, by Dominik Scheinert and 5 other authors
View PDFAbstract:Choosing a good resource configuration for big data analytics applications can be challenging, especially in cloud environments. Automated approaches are desirable as poor decisions can reduce performance and raise costs. The majority of existing automated approaches either build performance models from previous workload executions or conduct iterative resource configuration profiling until a near-optimal solution has been found. In doing so, they only obtain an implicit understanding of the underlying infrastructure, which is difficult to transfer to alternative infrastructures and, thus, profiling and modeling insights are not sustained beyond very specific situations.
We present Perona, a novel approach to robust infrastructure fingerprinting for usage in the context of big data analytics. Perona employs common sets and configurations of benchmarking tools for target resources, so that resulting benchmark metrics are directly comparable and ranking is enabled. Insignificant benchmark metrics are discarded by learning a low-dimensional representation of the input metric vector, and previous benchmark executions are taken into consideration for context-awareness as well, allowing to detect resource degradation. We evaluate our approach both on data gathered from our own experiments as well as within related works for resource configuration optimization, demonstrating that Perona captures the characteristics from benchmark runs in a compact manner and produces representations that can be used directly.
| Comments: | 8 pages, 5 figures, 3 tables |
| Subjects: | Distributed, Parallel, and Cluster Computing (cs.DC); Machine Learning (cs.LG) |
| Cite as: | arXiv:2211.08227 [cs.DC] |
| (orarXiv:2211.08227v2 [cs.DC] for this version) | |
| https://doi.org/10.48550/arXiv.2211.08227 arXiv-issued DOI via DataCite | |
| Journal reference: | IEEE BigData (2022) 209-216 |
| Related DOI: | https://doi.org/10.1109/BigData55660.2022.10020860 DOI(s) linking to related resources |
Submission history
From: Dominik Scheinert [view email][v1] Tue, 15 Nov 2022 15:48:09 UTC (298 KB)
[v2] Mon, 30 Jan 2023 10:05:48 UTC (299 KB)
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View a PDF of the paper titled Perona: Robust Infrastructure Fingerprinting for Resource-Efficient Big Data Analytics, by Dominik Scheinert and 5 other authors
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