Symbolic Intersect Detection: A Method for Improving Spatial Intersect Joins
Rent the article at a discountRent now
* Final gross prices may vary according to local VAT.Get Access
Due to the increasing popularity of spatial databases, researchers have focused their efforts on improving the query processing performance of the most expensive spatial database operation: the spatial join. While most previous work focused on optimizing the filter step, it has been discovered recently that, for typical GIS data sets, the refinement step of spatial join processing actually requires a longer processing time than the filter step. Furthermore, two-thirds of the time in processing the refinement step is devoted to the computation of polygon intersections. To address this issue, we therefore introduce a novel approach to spatial join optimization that drastically reduces the time of the refinement step. We propose a new approach called Symbolic Intersect Detection (SID) for early detection of true hits. Our SID optimization eliminates most of the expensive polygon intersect computations required by a spatial join by exploiting the symbolic topological relationships between the two candidate polygons and their overlapping minimum bounding rectangle. One important feature of our SID optimization is that it is complementary to the state-of-the-art methods in spatial join processing and therefore can be utilized by these techniques to further optimize their performance. In this paper, we also develop an analytical cost model that characterizes SID’s effectiveness under various conditions. Based on real map data, we furthermore conduct an experimental evaluation comparing the performance of the spatial joins with SID against the state-of-the-art approach. Our experimental results show that SID can effectively identify more than 80% of the true hits with negligible overhead. Consequently, with SID, the time needed for resolving polygon intersect in the refinement step is improved by over 50% over known techniques, as predicted by our analytical model.
- N. Beckmann, H. Kriegel, R. Schneider, and B. Seeger. “The R*-tree: An Efficient and Robust Access Method for Points and Rectangles,” in Proc. of the 1990 ACM SIGMOD Int. Conf. on Management of Data, 322–332, 1990.
- T. Brinkhoff, H. Kriegel, and B. Seeger. “Efficient Processing of Spatial Joins Using R-trees,” in Proc. Of the 1993 ACM SIGMOD Int. Conf. on Management of Data, 237–246, 1993.
- T. Brinkhoff, H. Kriegel, R. Schneider, and B. Seeger. “Multi-Step Processing of Spatial Joins,” in Proc. of the 1994 ACM SIGMOD Int. Conf. on Management of Data, 197–208, 1994.
- P.A. Burrough. Principles of Geographic Information Systems for Land Resources Assessment. Oxford University Press, 1986.
- C. Faloutsos and I. Kamel. “On Packing R-tree,” in Proc. of the Conference on Information and Knowledge Management, 490–499, 1993.
- O. Gunther. “Efficient Computation of Spatial Joins,” in Proc. of the 9th Int. Conf. on Data Eng., 50–59, 1993.
- A. Guttman. “R-tree: a dynamic index structure for spatial searching,” in Proc. of the 1984 ACM SIGMOD Int. Conf. on Management of Data, 45–57, 1984.
- Y.W. Huang, M. Jones, and E.A. Rundensteiner. “Improving Spatial Intersect Joins Using Symbolic Intersect Detection,” in Proc. of the 5th International Symposium on Spatial Databases, 165–177, 1997.
- Y.W. Huang and E.A. Rundensteiner. “Spatial Joins Using R-trees: Breadth-First Traversal with Global Optimizations,” in Proc. of the 23rd International Conference on Very Large Data Bases, 396–405, 1997.
- M.L. Lo and C.V. Ravishankar. “Spatial Join Using Seeded Trees,” in Proc. of the 1994 ACM SIGMOD Int. Conf. on Management of Data, 209–220, 1994.
- M.L. Lo and C.V. Ravishankar. “Spatial Hash-Joins,” in Proc. of the 1996 ACM SIGMOD Int. Conf. on Management of Data, 247–258, 1996.
- W. Lu and J. Han. “Distance-associated Join Indices for Spatial Range Search,” IEEE 8th Int. Conf. on Data Engineering, 284–292, 1992.
- Maguire, D.J., Goodchild, M.F., Rhind, D.W. (1991) Geographic Information Systems. John Wiley & Sons, Inc., New York
- Nievergelt, J., Hinterberger, H. (1984) The Grid File: An Adaptable, Symmetric Multikey File Structure. ACM Transactions on Database Systems 9: pp. 39-71
- J.A. Orenstein. “Spatial Query Processing in an Object-Oriented Database System,” in Proc. of the 1986 ACM SIGMOD Int. Conf. on Management of Data, 1986.
- J.A. Orenstein. “A Comparison of Spatial Query Processing Techniques for Native and Parameter Spaces,” in Proc. of the 1990 ACM SIGMOD Int. Conf. on Management of Data, 343–352, 1990.
- J.M. Patel and D.J. DeWitt. “Partition Based Spatial-Merge Join,” in Proc. of the 1996 ACM SIGMOD Int. Conf. on Management of Data, 259–270, 1996.
- F.P. Preparata and M.I. Shamos. Computation Geometry. Springer, 1985.
- D. Papadias, Y. Theodoridis, T. Sellis, and M.J. Egenhofer. “Relations in the World of Minimum Bounding Rectangles: A Study with R-trees,” in Proc. of the 1995 ACM SIGMOD Int. Conf. on Management of Data, 92–103, 1995.
- D. Rotem. “Spatial Join Indices,” IEEE 7th Int. Conf. on Data Engineering, 500–509, 1991.
- T. Sellis, N. Roussopoulos, and C. Faloutsos. “The R+-Tree: A Dynamic Index for Multi-dimensional Objects,” in Proc. of the International Conference on Very Large Data Bases, Brighton, England, 3–17, 1987.
- M.I. Shamos and D.J. Hoey. “Geometric Intersection Problems,” in Proc. 17th Annual Conf. on Foundations of Computer Science, 208–215, 1976.
- M. Stonebraker, J. Frew, K. Gardels, and J. Meredith. “The SEQUOIA 2000 Storage Benchmark,” in Proc. of the 1993 ACM SIGMOD Int. Conf. on Management of Data, 1993.
- Symbolic Intersect Detection: A Method for Improving Spatial Intersect Joins
Volume 2, Issue 2 , pp 149-174
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers
- Additional Links
- true hit detection
- spatial joins
- spatial databases
- spatial query processing
- Industry Sectors
- Author Affiliations
- 1. IBM T.J. Watson Research Center, Hawthorne, NY, 10532
- 2. Electrical Eng. and Computer Science Dept, University of Michigan, Ann Arbor, MI, 48109
- 3. Department of Computer Science, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA, 01609