Towards Preference-aware Relational Databases

Anastasios Arvanitis, Georgia Koutrika
2012 2012 IEEE 28th International Conference on Data Engineering  
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
more » ... rocessing 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. • Sr(rating) = 0.1 * rating • Sm(year, x) = year/x • S d (duration, x) = 1 − |duration − x|/x Example 3: Let us consider preference p 4 (Fig. 2) , ex-
doi:10.1109/icde.2012.31 dblp:conf/icde/ArvanitisK12 fatcat:k6sxm62jkrgbdn2frxodmotiim