Efficient Execution of Conjunctive Complex Queries on Big Multimedia Databases

This paper proposes an approach to efficiently execute conjunctive queries on big complex data together with their related conventional data. The basic idea is to horizontally fragment the database according to criteria frequently used in query predicates. The collection of fragments is indexed to efficiently find the fragment(s) whose contents satisfy some query predicate(s). The contents of each fragment are then indexed as well, to support efficient filtering of the fragment data according to other query predicate(s) conjunctively connected to the former. This strategy has been applied to a collection of more than 106 million images together with their related conventional data. Experimental results show considerable performance gain of the proposed approach for queries with conventional and similarity-based predicates, compared to the use of a unique metric index for the entire database contents.