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Workload analysis of a large-scale key-value store
Abstract
Key-value stores are a vital component in many scale-out enterprises, including social networks, online retail, and risk analysis. Accordingly, they are receiving increased attention from the research community in an effort to improve their performance, scalability, reliability, cost, and power consumption. To be effective, such efforts require a detailed understanding of realistic key-value workloads. And yet little is known about these workloads outside of the companies that operate them. This paper aims to address this gap.
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(2007) · doi:10.1145/1294261.1294281 · Cited by 3,447
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Metadata
- Authors
- Atikoglu, B., Xu, Y., Frachtenberg, E., Jiang, S., & Paleczny, M.
- Venue
- Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
- Publisher
- ACM
- Published
- 2012-06-11
- Pages
- 53-64
- OpenAlex
- W2125901106
- Cited by
- 901
- References
- 1
- FWCI
- 41.75
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Atikoglu, B., Xu, Y., Frachtenberg, E., Jiang, S., & Paleczny, M. (2012). Workload analysis of a large-scale key-value store. Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems. https://doi.org/10.1145/2254756.2254766
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
