Similarity query processing using disk arrays

  • Authors:

  • Apostolos N. Papadopoulos;Yannis Manolopoulos

  • Affiliations:

  • Department of Informatics, Aristotle University, Thessaloniki 54006, Greece;Department of Informatics, Aristotle University, Thessaloniki 54006, Greece

  • Venue:
  • SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
  • Year:
  • 1998

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Abstract

Similarity queries are fundamental operations that are used extensively in many modern applications, whereas disk arrays are powerful storage media of increasing importance. The basic trade-off in similarity query processing in such a system is that increased parallelism leads to higher resource consumptions and low throughput, whereas low parallelism leads to higher response times. Here, we propose a technique which is based on a careful investigation of the currently available data in order to exploit parallelism up to a point, retaining low response times during query processing. The underlying access method is a variation of the R*-tree, which is distributed among the components of a disk array, whereas the system is simulated using event-driven simulation. The performance results conducted, demonstrate that the proposed approach outperforms by factors a previous branch-and-bound algorithm and a greedy algorithm which maximizes parallelism as much as possible. Moreover, the comparison of the proposed algorithm to a hypothetical (non-existing) optimal one (with respect to the number of disk accesses) shows that the former is on average two times slower than the latter.