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|Title:||UpSizeR: Synthetically scaling an empirical relational database||Authors:||Tay, Y.C.
Attribute value correlation
Synthetic data generation
|Issue Date:||2013||Citation:||Tay, Y.C., Dai, B.T., Wang, D.T., Sun, E.Y., Lin, Y., Lin, Y. (2013). UpSizeR: Synthetically scaling an empirical relational database. Information Systems 38 (8) : 1168-1183. ScholarBank@NUS Repository. https://doi.org/10.1016/j.is.2013.07.004||Abstract:||The TPC benchmarks have helped users evaluate database system performance at different scales. Although each benchmark is domain-specific, it is not equally relevant to different applications in the same domain. The present proliferation of applications also leaves many of them uncovered by the very limited number of current TPC benchmarks. There is therefore a need to develop tools for application-specific database benchmarking. This paper presents UpSizeR, a software that addresses the Dataset Scaling Problem: Given an empirical set of relational tables D and a scale factor s, generate a database state DËœ that is similar to D but s times its size. Such a tool can be useful for scaling up D for scalability testing (s>1), scaling down for application testing (s||Source Title:||Information Systems||URI:||http://scholarbank.nus.edu.sg/handle/10635/104444||ISSN:||03064379||DOI:||10.1016/j.is.2013.07.004|
|Appears in Collections:||Staff Publications|
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