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Should SDBMS support a join index?: a case study from CrimeStat

Published: 05 November 2008 Publication History

Abstract

Given a spatial crime data warehouse, that is updated infrequently and a set of operations O as well as constraints of storage and update overheads, the index type selection problem is to find a set of index types that can reduce the I/O cost of the set of operations. The index type selection problem is important to improve user experience and system resource utilization in crucial spatial statistics application domains such as mapping and analysis for public safety, public health, ecology, and transportation. This is because the response time of frequent queries based on the set of operations can be improved significantly by an effective choice of index types. Many spatial statistical queries in these application domains make use of a spatial neighborhood matrix, known as W in spatial statistics, which can be thought of as a spatial self-join in spatial database terminology. Currently supported index types such as B-Tree and R-Tree families do not adequately support spatial statistical analysis because they require on-the-fly computation of the WMatrix, slowing down spatial statistical analysis. In contrast, this paper argues that Spatial Database Management Systems (SDBMS) should support a join index to materialize the WMatrix and eliminate on-the-fly computation of the common selfjoin. A detailed case study using the popular spatial statistical software package for public safety, namely CrimeStat, shows that join indices can significantly speed up spatial analysis such as calculation of Ripley's K and identification of hotspots.

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  • (2017)Spatial Analysis of Social Volume of Crime Issues Social Media DataProceedings of the 4th Multidisciplinary International Social Networks Conference10.1145/3092090.3092102(1-7)Online publication date: 17-Jul-2017
  • (2013)A projection-based hotspot analysis methodProceedings 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC)10.1109/MEC.2013.6885391(2066-2069)Online publication date: Dec-2013
  • (2012)Towards Vague Geographic Data WarehousesGeographic Information Science10.1007/978-3-642-33024-7_13(173-186)Online publication date: 2012
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  1. Should SDBMS support a join index?: a case study from CrimeStat

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    cover image ACM Conferences
    GIS '08: Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
    November 2008
    559 pages
    ISBN:9781605583235
    DOI:10.1145/1463434
    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: 05 November 2008

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    Author Tags

    1. W matrix
    2. join index
    3. self-join
    4. spatial statistics

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    View all
    • (2017)Spatial Analysis of Social Volume of Crime Issues Social Media DataProceedings of the 4th Multidisciplinary International Social Networks Conference10.1145/3092090.3092102(1-7)Online publication date: 17-Jul-2017
    • (2013)A projection-based hotspot analysis methodProceedings 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC)10.1109/MEC.2013.6885391(2066-2069)Online publication date: Dec-2013
    • (2012)Towards Vague Geographic Data WarehousesGeographic Information Science10.1007/978-3-642-33024-7_13(173-186)Online publication date: 2012
    • (2011)Efficient processing of drill-across queries over geographic data warehousesProceedings of the 13th international conference on Data warehousing and knowledge discovery10.5555/2033616.2033632(152-166)Online publication date: 29-Aug-2011
    • (2011)Efficient Processing of Drill-across Queries over Geographic Data WarehousesData Warehousing and Knowledge Discovery10.1007/978-3-642-23544-3_12(152-166)Online publication date: 2011

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