Optimizing queries over multimedia repositories

  • Authors:

  • Surajit Chaudhuri;Luis Gravano

  • Affiliations:

  • Microsoft Research and Hewlett-Packard Laboratories;Hewlett-Packard Laboratories, Stanford University

  • Venue:
  • SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
  • Year:
  • 1996

Quantified Score

Hi-index 0.02

Visualization

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.