Skip to main content

Bulk Loading the M-Tree to Enhance Query Performance

  • Conference paper
Key Technologies for Data Management (BNCOD 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3112))

Included in the following conference series:

Abstract

The M-tree is a paged, dynamically balanced metric access method that responds gracefully to the insertion of new objects. Like many spatial access methods, the M-tree’s performance is largely dependent on the degree of overlap between spatial regions represented by nodes in the tree, and minimisation of overlap is key to many of the design features of the M-tree and related structures. We present a novel approach to overlap minimisation using a new bulk loading algorithm, resulting in a query cost saving of between 25% and 40% for non-uniform data.

The structural basis of the new algorithm suggests a way to modify the M-tree to produce a variant which we call the SM-tree. The SM-tree has the same query performance after bulk loading as the M-tree, but further supports efficient object deletion while maintaining the usual balance and occupancy constraints.

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

Access this chapter

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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ciaccia, P., Patella, M.: Bulk loading the M-tree. In: Proceedings of the 9th Australasian Database Conference (ADC 1998), Perth, Australia, pp. 15–26 (1998)

    Google Scholar 

  2. Ciaccia, P., Patella, M., Zezula, P.: M-tree: An efficient access method for similarity search in metric spaces. In: Proceedings of the 23rd VLDB Conference, Athens, Greece, pp. 426–435 (1997)

    Google Scholar 

  3. Guttman, A.: R-trees: A dynamic index structure for spatial searching. SIGMOD Record 14(2), 47–57 (1984)

    Article  Google Scholar 

  4. Traina Jr., C., Traina, A., Faloutsos, C., Seeger, B.: Fast indexing and visualization of metric data sets using Slim-trees. IEEE Transactions on Knowledge and Data Engineering 14(2), 244–260 (2002)

    Article  Google Scholar 

  5. Sexton, A.P., Swinbank, R.: Symmetric M-tree. Technical Report CSR- 04-2, University of Birmingham, UK (2004), Available at www.cs.bham.ac.uk/~rjs/research

  6. Uhlmann, J.K.: Satisfying general proximity/similarity queries with metric trees. Information Processing Letters 40(4), 175–179 (1991)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sexton, A.P., Swinbank, R. (2004). Bulk Loading the M-Tree to Enhance Query Performance. In: Williams, H., MacKinnon, L. (eds) Key Technologies for Data Management. BNCOD 2004. Lecture Notes in Computer Science, vol 3112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27811-5_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-27811-5_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22382-5

  • Online ISBN: 978-3-540-27811-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics