TY  - JOUR
A1  - Kossmann, Jan
A1  - Schlosser, Rainer
T1  - Self-driving database systems
BT  - a conceptual approach
JF  - Distributed and parallel databases
N2  - 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.
KW  - database systems
KW  - self-driving
KW  - recursive tuning
KW  - workload prediction
KW  - robustness
Y1  - 2020
U6  - https://doi.org/10.1007/s10619-020-07288-w
SN  - 0926-8782
SN  - 1573-7578
VL  - 38
IS  - 4
SP  - 795
EP  - 817
PB  - Springer
CY  - Dordrecht
ER  -