Skip to main content

The BASIS System: A Benchmarking Approach for Spatial Index Structures

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1678))

Abstract

This paper describes the design of the BASIS prototype system. BASIS stands for Benchmarking Approach for Spatial Index Structures. It is a prototype system aiming at performance evaluation of spatial access methods and query processing strategies, under different data sets, various query types, and different workloads. BASIS is based on a modular architecture, composed of a simple storage manager, a query processor, and a set of algorithmic techniques to facilitate benchmarking. The main objective of BASIS is twofold: (i) to provide a benchmarking environment for spatial access methods and related query evaluation techniques, and (ii) to allow comparative studies of spatial access methods in different cases but under a common framework. We currently extend it to support the fundamental features of spatiotemporal data management and access methods.

Work supported by the European Union’s TMR program (“CHOROCHRONOS” project, contract number ERBFMRX-CT96-0056) and by the 1998-1999 French-Greek bilateral protocol.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. W. Aref: “Query Processing and Optimization in Spatial Databases” Technical Report CS-TR-3097, University of Maryland at College Park, 1993. 152

    Google Scholar 

  2. D. Bitton, D. DeWitt and C. Turby.ll: “Benchmarking Database Systems: a Systematic Approach”, Proceedings 9th VLDB Conference, pp.8–19, Florence, Italy, 1983. 153

    Google Scholar 

  3. N. Beckmann, H. P. Kriegel and B. Seeger: “The R*-tree: an Efficient and Robust Method for Points and Rectangles”, Proceedings 1990 ACM SIGMOD Conference, pp.322–331, Atlantic City, NJ, 1990. 152

    Google Scholar 

  4. T. Brinkho., H-P. Kriegel and B. Seeger: “Efficient Processing of Spatial Joins using R-trees”, Proceedings 1993 ACM SIGMOD Conference, pp.237–246, Washington DC, 1993. 152

    Google Scholar 

  5. L. Bouganim, O. Kapitskaia and P. Valduriez: “Memory Adaptive Scheduling for Large Query Execution”, Proceedings 7th CIKM Conference, 1998.

    Google Scholar 

  6. A. B. Chaudhri: “An Annotated Bibliography of Benchmarks for Object Databases”, ACM SIGMOD Record, Vol.24, No.1, pp.50–57, 1995. 153

    Article  Google Scholar 

  7. M. Dumas, M.-C. Fauvet and P.-C. Scholl: “Handling Temporal Grouping and Pattern-Matching Queries in a Temporal Object Model”, Proceedings 7th CIKM Conference, 1998. 161

    Google Scholar 

  8. R. H. Güting: “An Introduction to Spatial Database Systems”, The VLDB Journal, Vol.3, No.4, pp,357–399, 1994. 152

    Article  Google Scholar 

  9. O. Günther, V. Oria, P. Picouet, J-M. Saglio and M. Scholl: «Benchmarking Spatial Joins A la Carte», Proceedings International Conference on Scientific and Statistical Databases (SSDBM’ 98), 1998. 153, 161, 166

    Google Scholar 

  10. A. Guttman: “R-trees: a Dynamic Index Structure for Spatial Searching”, Proceedings 1984 ACM SIGMOD Conference, pp.47–57, Boston, MA, 1984. 152

    Google Scholar 

  11. G. Graefe: “Query Evaluation Techniques for Large Databases”, ACM Computing Surveys, Vol.25, No.2, pp.73–170, 1993. 159, 164

    Article  Google Scholar 

  12. J. M. Helerstein, J. F. Naughton and A. Pfeffer: “Generalized Search Trees for Database Systems”, Proceedings 21st VLDB Conference, pp.562–573, Zurich, Switzerland, 1995. 153

    Google Scholar 

  13. A. Henrich, H. W. Six and P. Widmayer: “The LSD-tree: Spatial Access to Multidimensional Point and Non-Point Objects”, Proceedings 15th VLDB Conference, pp.45–53, Amsterdam, Netherlands, 1989. 152

    Google Scholar 

  14. I. Kamel and C. Faloutsos: “On Packing R-trees”, Proceedings 2nd CIKM Conference, 1993.

    Google Scholar 

  15. KF94. I. Kamel and C. Faloutsos: “Hilbert R-tree: an Improved R-tree Using Fractals”, Proceedings 20th VLDB Conference, pp.500–509, Santiago, Chile, 1994. 152

    Google Scholar 

  16. N. Katayama and S. Satoh: “The SR-tree: an Index Structure for High-Dimensional Nearest Neighbor Queries”, Proceedings 1997 ACM SIGMOD Conference, pp.369–380, May 1997. 155

    Google Scholar 

  17. S. Leutenegger, J. Edgington and M. Lopez: “STR: a Simple and Efficient Algorithm for R-tree Packing”, Proceedings 12th IEEE ICDE Conference, 1996. 165

    Google Scholar 

  18. M. Livny, R. Ramakrishnan, K. Beyer, G. Chen, D. Donjerkovic, S. Lawande, J. Myllymaki and K. Wenger: “DEVISE: Integrated Querying and Visual Exploration of Large Datasets”, Proceedings 1997 ACM SIGMOD Conference, 1997. 153

    Google Scholar 

  19. R. Laurini and D. Thomson: “Fundamentals of Spatial Information Systems”, Academic Press, London, 1992. 152

    MATH  Google Scholar 

  20. M.-L. Lo and C. V. Ravishankar: “The Design and Implementation of Seeded Trees: An Efficient Method for Spatial Joins”, IEEE Transactions on Knowledge and Data Engineering, Vol.10, No.1, 1998. 165

    Google Scholar 

  21. B. Nag and D. DeWitt: “Memory Allocation Strategies for Complex Decision Support Queries”, Proceedings 7th CIKM Conference, 1998.

    Google Scholar 

  22. A. N. Papadopoulos, P. Rigaux and M. Scholl: “A Performance Evaluation of Spatial Join Processing Strategies”, Proceedings International Conference on Large Spatial Databases (SSD’99), Honk-Kong, China, 1999. 164, 165, 166

    Google Scholar 

  23. N. Roussopoulos, S. Kelley and F. Vincent: “Nearest Neighbor Queries”, Proceedings 1995 ACM SIGMOD Conference, pp.71–79, San Jose, CA, 1995. 152

    Google Scholar 

  24. M. Stonebraker, J. Frew, K. Gardels, and J. Meredith: “The Sequoia 2000 Storage Benchmark”, Proceedings 1993 ACM SIGMOD Conference, pp.2–11, Washington DC, 1993. 161

    Google Scholar 

  25. T. Sellis, N. Roussopoulos and C. Faloutsos: “The R+-tree: a Dynamic Index for Multidimensional Objects”, Proceedings 13th VLDB Conference, pp.507–518, Brighton, UK, 1987. 152

    Google Scholar 

  26. Bureau of the Census: “Tiger/line files”, Washington DC, 1994. 161

    Google Scholar 

  27. Transaction Processing Performance Council TPC. TPC Benchmark D Specification, version 1.1 edition, December 1995. 153

    Google Scholar 

  28. Transaction Processing Performance Council TPC. TPC Benchmark C Specification, revision 3.3.2 edition, June 1997. 153

    Google Scholar 

  29. Y. Theodoridis and T. Sellis: “A Model for the Prediction of R-tree Performance”, Proceedings of the 15th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS’96), Montreal, Canada, 1996. 152

    Google Scholar 

  30. Y. Theodoridis, E. Stefanakis and T. Sellis: “Cost Models for Join Queries in Spatial Databases”, Proceedings Intl. Conf. on Data Engineering (ICDE’98), 1998. 152

    Google Scholar 

  31. Y. Theodoridis, E. Stefanakis, and T. Sellis: “Spatio-Temporal Indexing for Large Multimedia Applications”, Proceedings of the IEEE International Conference on Multimedia Systems, Hiroshima, Japan, 1996. 162

    Google Scholar 

  32. P. Valduriez: “Join Indices”, ACM Transactions on Database Systems, Vol.12, No.2, pp.218–246, 1987.

    Article  Google Scholar 

  33. X. Xu, J. Han and W. Lu: “RT-Tree: an Improved R-tree Index Structure for Spatiotemporal Databases”, Proceedings 4th Symposium on Spatial Data Handling (SDH’90), pp.1040–1049, 1990. 162

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Gurret, C., Manolopoulos, Y., Papadopoulos, A., Rigaux, P. (1999). The BASIS System: A Benchmarking Approach for Spatial Index Structures. In: Böhlen, M.H., Jensen, C.S., Scholl, M.O. (eds) Spatio-Temporal Database Management. STDBM 1999. Lecture Notes in Computer Science, vol 1678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48344-6_9

Download citation

  • DOI: https://doi.org/10.1007/3-540-48344-6_9

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66401-7

  • Online ISBN: 978-3-540-48344-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics