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A spatial bitmap-based index for geographical data warehouses

Published: 08 March 2009 Publication History

Abstract

In this paper we propose the Spatial Bitmap Index (SB-index), which is an index based on Bitmap and Minimum Bounding Rectangle (MBR) to provide efficient query processing in Geographical Data Warehouses. The SB-index is built on the primary key of a spatial dimension table, and maintains the MBR of a given spatial attribute. Query processing requires a scan on the index, which compares both the query spatial predicate and the current MBR. This scan supplies a set of candidate solutions to a refinement step that evaluates each candidate. Finally, only the index entries from objects that satisfy the spatial predicate must be accessed, in order to answer the submitted query. Comparisons between the SB-index and the star-join indexed with R-tree and GiST showed significantly improvement of 25% up to 95% with regards to the query processing time. This performance gain occurs since SB-index restricts a set of candidates and avoids the star-join calculation.

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cover image ACM Conferences
SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing
March 2009
2347 pages
ISBN:9781605581668
DOI:10.1145/1529282
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 08 March 2009

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Author Tags

  1. bitmap index
  2. geographical data warehouse
  3. projection index

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SAC09: The 2009 ACM Symposium on Applied Computing
March 8, 2009 - March 12, 2008
Hawaii, Honolulu

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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  • (2017)Fast and scalable inequality joinsThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-016-0441-626:1(125-150)Online publication date: 1-Feb-2017
  • (2016)Spatiotemporal data representation and its effect on the performance of spatial analysis in a cyberinfrastructure environment – A case study with raster zonal analysisComputers & Geosciences10.1016/j.cageo.2015.11.00587(11-21)Online publication date: Feb-2016
  • (2016)Asymmetric Scalar Product Encryption for Circular and Rectangular Range SearchesAdvances in Databases and Information Systems10.1007/978-3-319-44039-2_13(183-197)Online publication date: 14-Aug-2016
  • (2015)Lightning fast and space efficient inequality joinsProceedings of the VLDB Endowment10.14778/2831360.28313628:13(2074-2085)Online publication date: 1-Sep-2015
  • (2013)Polygon-Based Query Evaluation over Geospatial Data Using Distributed Hash TablesProceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing10.1109/UCC.2013.46(219-226)Online publication date: 9-Dec-2013
  • (2010)Benchmarking spatial data warehousesProceedings of the 12th international conference on Data warehousing and knowledge discovery10.5555/1881923.1881928(40-51)Online publication date: 30-Aug-2010
  • (2010)Modelling and querying geographical data warehousesInformation Systems10.1016/j.is.2009.10.00535:5(592-614)Online publication date: 1-Jul-2010
  • (2010)Benchmarking Spatial Data WarehousesData Warehousing and Knowledge Discovery10.1007/978-3-642-15105-7_4(40-51)Online publication date: 2010
  • (2009)FastBit: interactively searching massive dataJournal of Physics: Conference Series10.1088/1742-6596/180/1/012053180(012053)Online publication date: 11-Aug-2009

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