Optimization of disjunctive predicates for main memory column stores


Kastrati, Fisnik ; Moerkotte, Guido



DOI: https://doi.org/10.1145/3035918.3064022
URL: https://www.researchgate.net/publication/317039745...
Weitere URL: https://dl.acm.org/citation.cfm?id=3064022
Dokumenttyp: Konferenzveröffentlichung
Erscheinungsjahr: 2017
Buchtitel: SIGMOD '17 : Proceedings of the 2017 ACM International Conference on Management of Data, May 14-19, 2017, Chicago, IL, USA
Seitenbereich: 731-744
Veranstaltungstitel: SIGMOD '17
Veranstaltungsort: Chicago, IL
Veranstaltungsdatum: 14.-19.05.2017
Herausgeber: Chirkova, Rada
Ort der Veröffentlichung: Chicago, IL
Verlag: ACM
ISBN: 978-1-4503-4197-4
Verwandte URLs:
Sprache der Veröffentlichung: Englisch
Einrichtung: Fakultät für Wirtschaftsinformatik und Wirtschaftsmathematik > Practical Computer Science III (Moerkotte 1996-)
Fachgebiet: 004 Informatik
Abstract: Optimization of disjunctive predicates is a very challenging task which has been vastly neglected by the research community and commercial databases. In this work, we focus on the complex problem of optimizing disjunctive predicates by means of the bypass processing technique. In bypass processing, selection operators split the input tuple stream into two disjoint output streams: the true-stream with tuples that satisfy the selection predicate and the false-stream with tuples that do not. Bypass processing is crucial in avoiding expensive predicates whenever the outcome of the query predicate can be determined by evaluating the less expensive ones. In main memory databases, CPU architectural characteristics, such as the branch misprediction penalty, become a prominent cost factor which cannot be ignored. Our algorithm takes into account the branch misprediction penalty, and, in addition, it eliminates common subexpressions. The current literature relies on two assumptions: (1) predicate costs are assumed to be constant, (2) predicate selectivities are assumed to be independent. Since both assumptions do not hold in practice, our approach is not based on any of them.




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