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Small selectivities matter: Lifting the burden of empty samples
Hertzschuch, Axel
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Moerkotte, Guido
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Lehner, Wolfgang
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May, Norman
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Wolf, Florian
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Fricke, Lars
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DOI:
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https://doi.org/10.1145/3448016.3452805
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URL:
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https://dl.acm.org/doi/10.1145/3448016.3452805
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Weitere URL:
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https://www.researchgate.net/publication/352535983...
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Dokumenttyp:
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Konferenzveröffentlichung
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Erscheinungsjahr:
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2021
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Buchtitel:
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Proceedings of the 2021 International Conference on Management of Data : SIGMOD/PODS '21
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Seitenbereich:
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697-709
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Veranstaltungstitel:
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SIGMOD/PODS '21
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Veranstaltungsort:
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Online
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Veranstaltungsdatum:
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20.-25.06.2021
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Herausgeber:
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Li, Guoliang
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Li, Zhanhuai
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Ort der Veröffentlichung:
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New York, NY
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Verlag:
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Association for Computing Machinery
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ISBN:
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978-1-4503-8343-1
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Verwandte URLs:
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Sprache der Veröffentlichung:
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Englisch
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Einrichtung:
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Fakultät für Wirtschaftsinformatik und Wirtschaftsmathematik > Practical Computer Science III (Moerkotte 1996-)
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Fachgebiet:
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004 Informatik
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Abstract:
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Every year more and more advanced approaches to cardinality estimation are published, using learned models or other data and workload specific synopses. In contrast, the majority of commercial in-memory systems still relies on sampling. It is arguably the most general and easiest estimator to implement. While most methods do not seem to improve much over sampling-based estimators in the presence of non-selective queries, sampling struggles with highly selective queries due to limitations of the sample size. Especially in situations where no sample tuple qualifies, optimizers fall back to basic heuristics that ignore attribute correlations and lead to large estimation errors. In this work, we present a novel approach, dealing with these 0-Tuple Situations. It is ready to use in any DBMS capable of sampling, showing a negligible impact on optimization time. Our experiments on real world and synthetic data sets demonstrate up to two orders of magnitude reduced estimation errors. Enumerating single filter predicates according to our estimates reveals 1.3 to 1.8 times faster query responses for complex filters.
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
 Suche Autoren in
BASE:
Hertzschuch, Axel
;
Moerkotte, Guido
;
Lehner, Wolfgang
;
May, Norman
;
Wolf, Florian
;
Fricke, Lars
Google Scholar:
Hertzschuch, Axel
;
Moerkotte, Guido
;
Lehner, Wolfgang
;
May, Norman
;
Wolf, Florian
;
Fricke, Lars
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