Histogram domain ordering for path selectivity estimation

N. Yakovets, Li Wang, G.H.L. Fletcher, Craig Taverner, Alexandra Poulovassilis

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

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Samenvatting

We aim to improve the accuracy of path selectivity estimation in graph databases by intelligently ordering the domain of a histogram used for estimation. This problem has not, to our knowledge, received adequate attention in the research community. We present a novel framework for the systematic study of path ordering strategies in histogram construction and use. In this framework, we introduce new ordering strategies which we experimentally demonstrate lead to significant improvement of the accuracy of path selectivity estimation over current strategies. These positive results highlight the fundamental role that domain ordering plays in the design of effective histograms for efficient and scalable graph query processing.

Originele taal-2Engels
TitelAdvances in Database Technology - EDBT 2018
Subtitel21st International Conference on Extending Database Technology, Proceedings
RedacteurenMichael Bohlen, Reinhard Pichler, Norman May, Erhard Rahm, Shan-Hung Wu, Katja Hose
UitgeverijOpenProceedings.org
Pagina's493-496
Aantal pagina's4
ISBN van elektronische versie978-3-89318-078-3
DOI's
StatusGepubliceerd - 2018
EvenementEDBT/ICDT 2018 Joint Conference 21st International Conference on Extending Database Technology - Vienna, Oostenrijk
Duur: 26 mrt 201829 mrt 2018

Congres

CongresEDBT/ICDT 2018 Joint Conference 21st International Conference on Extending Database Technology
LandOostenrijk
StadVienna
Periode26/03/1829/03/18

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