Categorical Range Queries in Large Databases

  • Alexandros Nanopoulos
  • Panayiotis Bozanis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2750)


In this paper, we introduce the categorical (a.k.a. chromatic) range queries (CRQs) in the context of large, disk-resident data sets, motivated by the fact that CRQs are conceptually simple and emerge often in DBMSs. On the basis of spatial data structures, and R-trees in particular, we propose a multi-tree index that follows the broad concept of augmenting nodes with additional information to accelerate queries. Augmentation is examined with respect to maximal/minimal points in subtrees, the properties of which are exploited by the proposed searching algorithm to effectively prune the search space. Detailed experimental results, with both real and synthetic data, illustrate the significant performance gains (up to an order of magnitude) due to the proposed method, compared to the regular range query (followed by the filtering w.r.t. categories) and to a naive R-tree augmentation method.


Execution Time Domain Size Range Query Categorical Attribute Replication Factor 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Alexandros Nanopoulos
    • 1
  • Panayiotis Bozanis
    • 2
  1. 1.Dept. InformaticsAristotle UniversityThessalonikiGreece
  2. 2.Dept. Computer Eng. and TelecomUniversity of ThessalyVolosGreece

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