PrefDB: bringing preferences closer to the DBMS
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Composition and efficient evaluation of context-aware preference queries
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part II
Flexible and extensible preference evaluation in database systems
ACM Transactions on Database Systems (TODS)
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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.