Precise, compact, and fast data access counters for automated physical database design

Brendle, Michael ; Weber, Nick ; Valyiev, Mahammad ; May, Norman ; Schulze, Robert ; Böhm, Alexander ; Moerkotte, Guido ; Grossniklaus, Michael

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URN: urn:nbn:de:bsz:180-madoc-611561
Document Type: Conference or workshop publication
Year of publication: 2021
Book title: Datenbanksysteme für Business, Technologie und Web (BTW 2021) : 13.-17. September 2021 in Dresden, Deutschland
The title of a journal, publication series: GI-Edition : Lecture Notes in Informatics. Proceedings
Volume: 311
Page range: 79-100
Conference title: BTW 2021, Online Lecture Series
Location of the conference venue: Online
Date of the conference: 19.4.-21.06.2021
Publisher: Sattler, Kai-Uwe ; Herschel, Melanie ; Lehner, Wolfgang
Place of publication: Bonn
Publishing house: Ges. für Informatik
ISBN: 978-3-88579-705-0 , 3-88579-705-4
ISSN: 1617-5468
Related URLs:
Publication language: English
Institution: School of Business Informatics and Mathematics > Practical Computer Science III (Moerkotte)
Pre-existing license: Creative Commons Attribution, Share Alike 4.0 International (CC BY-SA 4.0)
Subject: 004 Computer science, internet
Abstract: Today’s database management systems offer numerous tuning knobs that allow an adaptation of database system behavior to specific customer needs, e. g., maximal throughput or minimal memory consumption. Because manual tuning by database experts is complicated and expensive, academia and industry devised tools that automate physical database tuning. The effectiveness of such advisor tools strongly depends on the availability of accurate statistics about the executed database workload. For advisor tools to run online, workload execution statistics must also be collected with low runtime and memory overhead. However, to the best of our knowledge, no approach collects precise, compact, and fast workload execution statistics for a physical database design tool. In this paper, we present data structures that solve the problem of providing workload execution statistics with high precision, low memory consumption, and low runtime overhead. In particular, we show how existing approaches can be combined and for which advisor tools, new data structures need to be designed. We evaluate our data structures in a prototype of a commercial database and show that they outperform previous approaches using real-world and synthetic benchmarks.
Additional information: Online-Ressource Die 19. Fachtagung "Datenbanksysteme für Business, Technologie und Web" (BTW) der Gesellschaft für Informatik (GI) war für den 13.-17. September 2021 an der Technischen Universität Dresden angekündigt und fand vom 19. April bis 21. Juni 2021 als "Online Lecture Series" statt. Die Abschlussveranstaltung "Data Science Challenge" fand am am 14. September 2021 statt.

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