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| Zitatschlüssel | AlexandrovTM2012 |
|---|---|
| Autor | Alexander Alexandrov, Kostas Tzoumas, Volker Markl |
| Seiten | 1890-1893 |
| Jahr | 2012 |
| DOI | 10.14778/2367502.2367530 |
| Journal | Proceedings of the VLDB Endowment |
| Jahrgang | 5 |
| Nummer | 12 |
| Zusammenfassung | The current research focus on Big Data systems calls for a rethinking of data generation methods. The traditional sequential data generation approach is not well suited to large-scale systems as generating a terabyte of data may require days or even weeks depending on the number of constraints imposed on the generated model. We demonstrate Myriad, a new data generation toolkit that enables the specification of semantically rich data generator programs that can scale out linearly in a shared-nothing environment. Data generation programs built on top of Myriad implement an efficient parallel execution strategy leveraged by the extensive use of pseudo-random number generators with random access support. |