ACM SIGMOD Anthology ACM SIGMOD dblp.uni-trier.de

Partition Based Spatial-Merge Join.

Jignesh M. Patel, David J. DeWitt: Partition Based Spatial-Merge Join. SIGMOD Conference 1996: 259-270
@inproceedings{DBLP:conf/sigmod/PatelD96,
  author    = {Jignesh M. Patel and
               David J. DeWitt},
  editor    = {H. V. Jagadish and
               Inderpal Singh Mumick},
  title     = {Partition Based Spatial-Merge Join},
  booktitle = {Proceedings of the 1996 ACM SIGMOD International Conference on
               Management of Data, Montreal, Quebec, Canada, June 4-6, 1996},
  publisher = {ACM Press},
  year      = {1996},
  pages     = {259-270},
  ee        = {http://doi.acm.org/10.1145/233269.233338, db/conf/sigmod/PatelD96.html},
  crossref  = {DBLP:conf/sigmod/96},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

This paper describes PBSM (Partition Based Spatial-Merge), a new algorithm for performing spatial join operation. This algorithm is especially effective when neither of the inputs to the join have an index on the joining attribute. Such a situation could arise if both inputs to the join are intermediate results in a complex query, or in a parallel environment where the inputs must be dynamically redistributed. The PBSM algorithm partitions the inputs into manageable chunks, and joins them using a computational geometry based plane-sweeping technique. This paper also presents a performance study comparing the traditional indexed nested loops join algorithm, a spatial join algorithm based on joining spatial indices, and the PBSM algorithm. These comparisons are based on complete implementations of these algorithms in Paradise, a database system for handling GIS applications. Using real data sets, the performance study examines the behavior of these spatial join algorithms in a variety of situations, including the cases when both, one, or none of the inputs to the join have an suitable index. The study also examines the effect of clustering the join inputs on the performance of these join algorithms. The performance comparisons demonstrates the feasibility, and applicability of the PBSM algorithm.

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H. V. Jagadish, Inderpal Singh Mumick (Eds.): Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, Montreal, Quebec, Canada, June 4-6, 1996. ACM Press 1996 BibTeX , SIGMOD Record 25(2), June 1996
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Referenced by

  1. Hyoseop Shin, Bongki Moon, Sukho Lee: Adaptive Multi-Stage Distance Join Processing. SIGMOD Conference 2000: 343-354
  2. Christos Faloutsos, Bernhard Seeger, Agma J. M. Traina, Caetano Traina Jr.: Spatial Join Selectivity Using Power Laws. SIGMOD Conference 2000: 177-188
  3. Jochen Van den Bercken, Martin Schneider, Bernhard Seeger: Plug&Join: An easy-to-use Generic Algorithm for Efficiently Processing Equi and Non-Equi Joins. EDBT 2000: 495-509
  4. Lars Arge, Octavian Procopiuc, Sridhar Ramaswamy, Torsten Suel, Jan Vahrenhold, Jeffrey Scott Vitter: A Unified Approach for Indexed and Non-Indexed Spatial Joins. EDBT 2000: 413-429
  5. Michael Jaedicke, Bernhard Mitschang: User-Defined Table Operators: Enhancing Extensibility for ORDBMS. VLDB 1999: 494-505
  6. Nikos Mamoulis, Dimitris Papadias: Integration of Spatial Join Algorithms for Processing Multiple Inputs. SIGMOD Conference 1999: 1-12
  7. Hongjun Zhu, Jianwen Su, Oscar H. Ibarra: An Index Structure for Spatial Joins in Linear Constraint Databases. ICDE 1999: 636-643
  8. Geraldo Zimbrao, Jano Moreira de Souza: A Raster Approximation For Processing of Spatial Joins. VLDB 1998: 558-569
  9. Narayanan Shivakumar, Hector Garcia-Molina, Chandra Chekuri: Filtering with Approximate Predicates. VLDB 1998: 263-274
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  11. Oliver Günther, Vincent Oria, Philippe Picouet, Jean-Marc Saglio, Michel Scholl: Benchmarking Spatial Joins À La Carte. SSDBM 1998: 32-41
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  13. Yannis Theodoridis, Emmanuel Stefanakis, Timos K. Sellis: Cost Models for Join Queries in Spatial Databases. ICDE 1998: 476-483
  14. Nick Koudas, Kenneth C. Sevcik: High Dimensional Similarity Joins: Algorithms and Performance Evaluation. ICDE 1998: 466-475
  15. John C. Shafer, Rakesh Agrawal: Parallel Algorithms for High-dimensional Similarity Joins for Data Mining Applications. VLDB 1997: 176-185
  16. Yun-Wu Huang, Ning Jing, Elke A. Rundensteiner: Spatial Joins Using R-trees: Breadth-First Traversal with Global Optimizations. VLDB 1997: 396-405
  17. Sven Helmer, Guido Moerkotte: Evaluation of Main Memory Join Algorithms for Joins with Set Comparison Join Predicates. VLDB 1997: 386-395
  18. Yun-Wu Huang, Ning Jing, Elke A. Rundensteiner: A Cost Model for Estimating the Performance of Spatial Joins Using R-trees. SSDBM 1997: 30-38
  19. Jignesh M. Patel, Jie-Bing Yu, Navin Kabra, Kristin Tufte, Biswadeep Nag, Josef Burger, Nancy E. Hall, Karthikeyan Ramasamy, Roger Lueder, Curt J. Ellmann, Jim Kupsch, Shelly Guo, David J. DeWitt, Jeffrey F. Naughton: Building a Scaleable Geo-Spatial DBMS: Technology, Implementation, and Evaluation. SIGMOD Conference 1997: 336-347
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  21. Kyuseok Shim, Ramakrishnan Srikant, Rakesh Agrawal: High-Dimensional Similarity Joins. ICDE 1997: 301-311
  22. Yun-Wu Huang, Ning Jing, Elke A. Rundensteiner: Integrated Query Processing Strategies for Spatial Path Queries. ICDE 1997: 477-486
  23. Ming-Ling Lo, Chinya V. Ravishankar: Spatial Hash-Joins. SIGMOD Conference 1996: 247-258
BibTeX
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