Computer Science > Distributed, Parallel, and Cluster Computing
arXiv:2211.04240 (cs)
[Submitted on 8 Nov 2022 (v1), last revised 3 Feb 2023 (this version, v2)]
Title:Ruya: Memory-Aware Iterative Optimization of Cluster Configurations for Big Data Processing
View a PDF of the paper titled Ruya: Memory-Aware Iterative Optimization of Cluster Configurations for Big Data Processing, by Jonathan Will and Lauritz Thamsen and Jonathan Bader and Dominik Scheinert and Odej Kao
View PDFAbstract:Selecting appropriate computational resources for data processing jobs on large clusters is difficult, even for expert users like data engineers. Inadequate choices can result in vastly increased costs, without significantly improving performance. One crucial aspect of selecting an efficient resource configuration is avoiding memory bottlenecks. By knowing the required memory of a job in advance, the search space for an optimal resource configuration can be greatly reduced.
Therefore, we present Ruya, a method for memory-aware optimization of data processing cluster configurations based on iteratively exploring a narrowed-down search space. First, we perform job profiling runs with small samples of the dataset on just a single machine to model the job's memory usage patterns. Second, we prioritize cluster configurations with a suitable amount of total memory and within this reduced search space, we iteratively search for the best cluster configuration with Bayesian optimization. This search process stops once it converges on a configuration that is believed to be optimal for the given job. In our evaluation on a dataset with 1031 Spark and Hadoop jobs, we see a reduction of search iterations to find an optimal configuration by around half, compared to the baseline.
| Comments: | 9 pages, 5 Figures, 3 Tables; IEEE BigData 2022. arXiv admin note: substantial text overlap witharXiv:2206.13852 |
| Subjects: | Distributed, Parallel, and Cluster Computing (cs.DC) |
| ACM classes: | C.2.4; I.2.8; I.2.6 |
| Cite as: | arXiv:2211.04240 [cs.DC] |
| (orarXiv:2211.04240v2 [cs.DC] for this version) | |
| https://doi.org/10.48550/arXiv.2211.04240 arXiv-issued DOI via DataCite | |
| Journal reference: | 2022 IEEE International Conference on Big Data (Big Data) pp. 161-169 |
| Related DOI: | https://doi.org/10.1109/BigData55660.2022.10020295 DOI(s) linking to related resources |
Submission history
From: Jonathan Will [view email][v1] Tue, 8 Nov 2022 13:36:28 UTC (228 KB)
[v2] Fri, 3 Feb 2023 11:18:17 UTC (228 KB)
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View a PDF of the paper titled Ruya: Memory-Aware Iterative Optimization of Cluster Configurations for Big Data Processing, by Jonathan Will and Lauritz Thamsen and Jonathan Bader and Dominik Scheinert and Odej Kao
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