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Towards Generating HiFi Databases

Sanghi, A and Santhanam, R and Haritsa, JR (2021) Towards Generating HiFi Databases. In: 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, 11-14 Apr 2021, Taipei, pp. 105-112.

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Official URL: https://doi.org/10.1007/978-3-030-73194-6_8


Generating synthetic databases that capture essential data characteristics of client databases is a common requirement for database vendors. We recently proposed Hydra, a workload-aware and scale-free data regenerator that provides statistical fidelity on the volumetric similarity metric. A limitation, however, is that it suffers poor accuracy on unseen queries. In this paper, we present HF-Hydra (HiFi-Hydra), which extends Hydra to provide better support to unseen queries through (a) careful choices among the candidate synthetic databases and (b) incorporation of metadata constraints. Our experimental study validates the improved fidelity and efficiency of HF-Hydra. © 2021, Springer Nature Switzerland AG.

Item Type: Conference Paper
Publication: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher: Springer Science and Business Media Deutschland GmbH
Additional Information: The copyright for this article belongs to Springer Science and Business Media Deutschland GmbH
Keywords: Computer science; Computers, Data characteristics; Data regenerators; Database vendors; Scale-free; Similarity metrics; Synthetic database, Artificial intelligence
Department/Centre: Division of Electrical Sciences > Computer Science & Automation
Division of Interdisciplinary Sciences > Computational and Data Sciences
Date Deposited: 10 Aug 2021 09:52
Last Modified: 16 Aug 2021 05:21
URI: http://eprints.iisc.ac.in/id/eprint/69122

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