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Self-driving database systems
- Challenges for self-driving database systems, which tune their physical design and configuration autonomously, are manifold: Such systems have to anticipate future workloads, find robust configurations efficiently, and incorporate knowledge gained by previous actions into later decisions. We present a component-based framework for self-driving database systems that enables database integration and development of self-managing functionality with low overhead by relying on separation of concerns. By keeping the components of the framework reusable and exchangeable, experiments are simplified, which promotes further research in that area. Moreover, to optimize multiple mutually dependent features, e.g., index selection and compression configurations, we propose a linear programming (LP) based algorithm to derive an efficient tuning order automatically. Afterwards, we demonstrate the applicability and scalability of our approach with reproducible examples.
Verfasserangaben: | Jan KossmannORCiDGND, Rainer SchlosserORCiDGND |
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DOI: | https://doi.org/10.1007/s10619-020-07288-w |
ISSN: | 0926-8782 |
ISSN: | 1573-7578 |
Titel des übergeordneten Werks (Englisch): | Distributed and parallel databases |
Untertitel (Englisch): | a conceptual approach |
Verlag: | Springer |
Verlagsort: | Dordrecht |
Publikationstyp: | Wissenschaftlicher Artikel |
Sprache: | Englisch |
Datum der Erstveröffentlichung: | 16.03.2020 |
Erscheinungsjahr: | 2020 |
Datum der Freischaltung: | 28.10.2022 |
Freies Schlagwort / Tag: | database systems; recursive tuning; robustness; self-driving; workload prediction |
Band: | 38 |
Ausgabe: | 4 |
Seitenanzahl: | 23 |
Erste Seite: | 795 |
Letzte Seite: | 817 |
Fördernde Institution: | Projekt DEAL |
Organisationseinheiten: | An-Institute / Hasso-Plattner-Institut für Digital Engineering gGmbH |
DDC-Klassifikation: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
Peer Review: | Referiert |
Publikationsweg: | Open Access / Hybrid Open-Access |
Lizenz (Deutsch): | ![]() |