Indexing non-uniform spatial data

  • Authors:

  • K. V. Ravi Kanth;Divyakant Agrawal;Amr El Abbadi;Ambuj K. Singh

  • Affiliations:

  • Department of Computer Science, University of California at Santa Barbara, Santa Barbara, CA;Department of Computer Science, University of California at Santa Barbara, Santa Barbara, CA;Department of Computer Science, University of California at Santa Barbara, Santa Barbara, CA;Department of Computer Science, University of California at Santa Barbara, Santa Barbara, CA

  • Venue:
  • IDEAS'97 Proceedings of the 1997 international conference on International database engineering and applications symposium
  • Year:
  • 1997

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Abstract

Non-uniformity in data extents is a general characteristic of spatial data. Indexing such non-uniform data using conventional spatial index structures such as R* -trees is inefficient for two reasons: (1) The non-uniformity increases the likelihood of overlapping index entries, and, (2) clustering of non-uniform data is likely to index more dead space than clustering of uniform data. To reduce the impact of these anomalies, we propose a new scheme that promotes data objects to higher levels in tree-based index structures. We examine two criteria for promotion of data objects and evaluate their relative merits using an R* -tree. In experiments on cartographic data, we observe that our promotion criteria yield upto 45% improvement in query performance for an R* -tree.