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We focus our work on three specific self-managing database challenges: (i) system integration, (ii) index selection, and (iii) cost estimation. (i) System integration: DBMSs were not designed with self-managing capabilities in mind. We propose a generalized framework that provides facilities to enable self-managing DBMS by providing components for workload monitoring, forecasting, and tuning. (ii) Index selection: Diverse and volatile workloads from different applications complicate the selection of performance-enhancing indexes. We developed an efficient and scalable index selection approach that accounts for index interaction and reconfiguration costs while outperforming the runtime of state-of-the-art algorithms. (iii) Cost estimation: knowledge of query costs is crucial to determine efficient query execution plans. Self-managing systems must assess and quantify the cost impact of options available to them to be able to select the most beneficial one. We generate cost estimations with high accuracy by training estimation models continuously on actual runtime observations.
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Jan Kossmann,Martin Boissier, Alexander Dubrawski, Fabian Heseding,Caterina Mandel, Udo Pigorsch, Max Schneider, Til Schniese, Mona Sobhani,Petr Tsayun,Katharina Wille,Michael Perscheid,
The VLDB Journalno. 2 (2021): 471-471
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