Optimizing queries over multimedia repositories

Abstract

Repositories of multimedia objects having multiple types of attributes (e.g., image, text) are becoming increasingly common. A selection on these attributes will typically produce not just a set of objects, as in the traditional relational query model ( filtering ), but also a grade of match associated with each object, indicating how well the object matches the selection condition ( ranking ). Also, multimedia repositories may allow access to the attributes of each object only through indexes. We investigate how to optimize the processing of queries over multimedia repositories. A key issue is the choice of the indexes used to search the repository. We define an execution space that is search-minimal, i.e., the set of indexes searched is minimal. Although the general problem of picking an optimal plan in the search-minimal execution space is NP-hard, we solve the problem efficiently when the predicates in the query are independent. We also show that the problem of optimizing queries that ask for a few top-ranked objects can be viewed, in many cases, as that of evaluating selection conditions. Thus, both problems can be viewed together as an extended filtering problem.