Towards preference-aware relational databases

Arvanitis, A; Koutrika, G

dc.contributor.author	Arvanitis, A	en
dc.contributor.author	Koutrika, G	en
dc.date.accessioned	2014-03-01T02:54:03Z
dc.date.available	2014-03-01T02:54:03Z
dc.date.issued	2012	en
dc.identifier.issn	10844627	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36563
dc.subject.other	Algebraic properties	en
dc.subject.other	Black boxes	en
dc.subject.other	Database engine	en
dc.subject.other	Plug-ins	en
dc.subject.other	Preference models	en
dc.subject.other	Query optimization	en
dc.subject.other	Query-processing needs	en
dc.subject.other	Relational data models	en
dc.subject.other	Relational Database	en
dc.subject.other	Three dimensions	en
dc.subject.other	Algebra	en
dc.subject.other	Query languages	en
dc.subject.other	Query processing	en
dc.title	Towards preference-aware relational databases	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICDE.2012.31	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICDE.2012.31	en
heal.identifier.secondary	6228103	en
heal.publicationDate	2012	en
heal.abstract	In implementing preference-aware query processing, a straightforward option is to build a plug-in on top of the database engine. However, treating the DBMS as a black box affects both the expressivity and performance of queries with preferences. In this paper, we argue that preference-aware query processing needs to be pushed closer to the DBMS. We present a preference-aware relational data model that extends database tuples with preferences and an extended algebra that captures the essence of processing queries with preferences. A key novelty of our preference model itself is that it defines a preference in three dimensions showing the tuples affected, their preference scores and the credibility of the preference. Our query processing strategies push preference evaluation inside the query plan and leverage its algebraic properties for finer-grained query optimization. We experimentally evaluate the proposed strategies. Finally, we compare our framework to a pure plug-in implementation and we show its feasibility and advantages. © 2012 IEEE.	en
heal.journalName	Proceedings - International Conference on Data Engineering	en
dc.identifier.doi	10.1109/ICDE.2012.31	en
dc.identifier.spage	426	en
dc.identifier.epage	437	en