Integration of spatial join algorithms for processing multiple inputs

  • Authors:

  • Nikos Mamoulis;Dimitris Papadias

  • Affiliations:

  • Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong;Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong

  • Venue:
  • SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
  • Year:
  • 1999

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Abstract

Several techniques that compute the join between two spatial datasets have been proposed during the last decade. Among these methods, some consider existing indices for the joined inputs, while others treat datasets with no index, providing solutions for the case where at least one input comes as an intermediate result of another database operator. In this paper we analyze previous work on spatial joins and propose a novel algorithm, called slot index spatial join (SISJ), that efficiently computes the spatial join between two inputs, only one of which is indexed by an R-tree. Going one step further, we show how SISJ and other spatial join algorithms can be implemented as operators in a database environment that joins more than two spatial datasets. We study the differences between relational and spatial multiway joins, and propose a dynamic programming algorithm that optimizes the execution of complex spatial queries.