RK-Hist: An r-tree based histogram for multi-dimensional selectivity estimation

International Conference on Information and Knowledge Management, Proceedings

Volumn , Issue , 2007, Pages 475-484

  Eavis, Todd ^a   Lopez, Alex ^a  

^a Civil and Environmental Engineering   (Canada)

Author keywords

Data warehousing; Multi dimensional selectivity estimation

Indexed keywords

DATA SKEWS; DATA WAREHOUSING; DATABASE QUERIES; DIMENSIONAL DATABASE; DIMENSIONAL VARIATIONS; HILBERT SPACE FILLING CURVES; HISTOGRAM MODELS; LARGE DATUM; MULTI-DIMENSIONAL HISTOGRAMS; MULTI-DIMENSIONAL SELECTIVITY ESTIMATION; SELECTIVITY ESTIMATORS; SPACE PARTITIONING; STATE-OF-THE ARTS; TREE-BASED;

DATABASE SYSTEMS; DECISION TREES; KNOWLEDGE MANAGEMENT;

ESTIMATION;

EID: 63449102406     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1321440.1321508     Document Type: Conference Paper

References (33)

1. N. Beckmann, H. Kriegel, R. Schneider, and B. Seeger. The rd'-tree: an efficient and robust method for points and rectangles. ACM SIGMOD, pages 322-331, 1990.
2. J. Bentley. Multidimensional binary search trees used for associative searching. Communications of the ACM, 18:509-517, 1975.
3. N. Bruno, S. Chaudhuri, and L. Gravano. STHoles: a multidimensional workload-aware histogram. SIGMOD Record, 30(2):211-222, 2001.
4. S. Christodoulakis. Implications of certain assumptions in database performance evaluation. ACM TODS, 36(1):163-186, 1984.
5. C. Faloutsos and S. Roseman. Fractals for secondary key retrieval. SIGACT-SIGMOD-SIGART symposium on principles ofdatabase systems, pages 247-252, 1989.
6. V. Gaede and O. Gunther. Multidimensional access methods. ACM Computing Surveys, 30(2):170-231, 1998.
7. S. Guha, K. Shim, and J. Woo. REHIST: Relative Error Histogram Construction Algorithms. VLDB, pages 300-311, 2004.
8. D. Gunopulos, G. Kollios, V. Tsotras, and C. Domeniconi. Approximating multi-dimensional aggregate range queries over real attributes. ACM SIGMOD, pages 463-474, 2000.
9. A. Guttman. R-trees: A dynamic index structure for spatial searching. In ACM SIGMOD, pages 47-57, 1984.
10. A. Guttman. R-trees: A dynamic index structure for spatial searching. ACM SIGMOD, pages 47-57, 1984.
11. P. Haas and A. Swami. Sequential sampling procedures for query size estiamtion. ACM SIGMOD, pages 194-205, 1992.
12. D. Hilbert. Ueber die stetige abbildung einer line auf ein flchenstck. Mathematische Annalen, 38(3):459U′460, 1891.
13. C. Hoare. Algorithym 63 (partition) and algorithm 65 (find). Communications of the ACM, 4(7):321-322, 1961.
14. Y. Ioannidis. The history of histograms (abridged). VLDB, pages 19-30, 2003.
15. Y. Ioannidis and V. Poosala. Balancing histogram optimality and practicality for query result size estimation. ACM SIGMOD, pages 233-244, 1995.
16. H. Jagadish. Linear clusertering objects with multiple attributes. ACM SIGMOD, pages 332-342, 1990.
17. H. Jagadish, N. K. N., S. Muthukrishnan, V. Poosala, K. Sevcik, and T. Suel. Optimal histograms with quality guarantees. VLDB, pages 275-286, 1998.
18. I. Kamel and C. Faloutsos. On packing r-trees. CIKM, pages 490-499, 1993.
19. R. Kooi. The optimization ofqueries in relational databases. PhD thesis, Case Western Reserve University, 1980.
20. J. Lee, D. Kim, and C. Chung. Multi-dimensional selectivity estimation using compressed histogram information. ACM SIGMOD, pages 205-214, 1999.
21. S. Leutenegger, M. Lopez, and J. Eddington. STR: A simple and efficient algorithm for r-tree packing. ICDE, pages 497-506, 1997.
22. M. Muthukrishnan and D. Dewitt. Equi-depth histograms for estimating selectivity factors for multi-dimensional queries. ACM SIGMOD, pages 28-36, 1988.
23. S. Muthukrishnan, V. Poosala, and T. Suel. Partitionings in two dimensions: Algorithms, complexity, and applications. ICDT, pages 236-256, 1999.
24. G. Peano. Sur une courbe, qui remplit toute une aire plane. Mathematische Annalen, 36(1):157-160, 1890.
25. G. Piatetsky-Shapiro and C. Connell. Accurate estimation of the number of tuples satisfying a condition. ACM SIGMOD, pages 256-276, 1984.
26. V. Poosala and Y. Ioannidis. Selectivity estimation without the attribute value independence assumption. VLDB, pages 486-495, 1997.
27. V. Poosala, Y. Ioannidis, P. Haas, and E. Shekita. Improved histograms for selectivity estimation of range predicates. ACM SIGMOD, pages 294-305, 1996.
28. N. Roussopoulos and D. Leifker. Direct spatial search on pictorial databases using packed r-trees. In ACM SIGMOD, pages 17-31, 1985.
29. T. Sellis, N. Roussopoulos, and C. Faloutsos. The r+-tree - a dynamic index for multidimensional objects. VLDB, pages 507-518, 1987.
30. J. Spiegel and N. Polyzotis. Graph-based synopses for relational selectivity estimation. In ACM SIGMOD, pages 205-216, 2006.
31. U. Srivastava, P. Haas, V. Markl, M. Kutsch, and T. Tran. Consistent histogram construction using query feedback. ICDE, pages 39-51, 2006.
32. N. Thaper, S. Guha, P. Indyk, and N. Koudas. Dynamic multidimensional histograms. In ACM SIGMOD, pages 428-439, 2002.
33. J. Vitter, M. Wang, and B. Iyer. Data cube approximation and histograms via wavelets. CIKM, pages 96-104, 1998.