Efficient creation of statistics over query expressions

Proceedings - International Conference on Data Engineering

Volumn , Issue , 2003, Pages 201-213

  Bruno, Nicolas ^a   Chaudhuri, Surajit ^b  

^a Och Spine at New York Presbyterian Hospitals   (United States)

^b MICROSOFT RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

QUERY EXPRESSIONS; QUERY OPTIMIZERS;

ESTIMATION; OPTIMIZATION; QUERY LANGUAGES; STATISTICS;

RELATIONAL DATABASE SYSTEMS;

EID: 0344065598     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDE.2003.1260793     Document Type: Conference Paper

References (19)

1. S. Acharya, P. B. Gibbons, V. Poosala, and S. Ramaswamy. Joint synopses for approximate query answering. In Proceedings of the 1999 ACM International Conference on Management, 1999.
2. N. Bruno and S. Chaudhuri. Exploiting statistics on query expressions for optimization. In Proceedings of the 2002 ACM International Conference on Management of Data, 2002.
3. S. Chaudhuri, R. Motwani, and V. Narasayya. Random sampling for histogram construction: How much is enough? In Proceedings of the 1998 ACM International Conference on Management of Data, 1998.
4. S. Chaudhuri, R. Motwani, and V. Narasayya. On random sampling over joins. In Proceedings of the 1999 ACM International Conference on Management of Data, 1999.
5. S. Chaudhuri and V. Narasayya. Automating statistics management for query optimizers. In Proceedings of the Sixteenth International Conference on Data Engineering, 2000.
6. G. Graefe. The cascades framework for query optimization. Data Engineering Bulletin, 18(3), 1995.
7. L. M. Haas, J. C. Freytag, G. M. Lohman, and H. Pirahesh. Extensible query processing in starburst. In Proceedings of the 1989 ACM International Conference on Management of Data, 1989.
8. D. Maier. The complexity of some problems on subsequences and supersequences. In Journal of the ACM, Springer-Verlag, 2001.
9. G. Nicosia and G. Oriolo. Solving the shortest common supersequence problem. In Operation Research. Springer-Verlag, 2001.
10. N. J. Nilsson. Problem solving methods in artificial intelligence. McGraw-Hill, 1971.
11. F. Olken and D. Rotem. Random sampling from database files: A survey. In Statistical and Scientific Database Management, 5th International Conference (SSDBM), 1990.
12. G. Piatetsky-Shapiro and C. Connell. Accurate estimation of the number of tuples satisfying a condition. In Proceedings of the 1984 ACM International Conference on Management of Data, 1984.
13. V. Poosala and Y. Ioannidis. Selectivity estimation without the attribute value independence assumption. In Proceedings of the Twenty-third International Conference on Very Large Databases, 1997.
14. V. Poosala, Y. Ioannidis, P. Haas, and E. Shekita. Improved histograms for selectivity estimation of range predicates. In Proceedings of the 1996 ACM International Conference on Management of Data, 1996.
15. P. Roy, S. Seshadri, S. Sudarshan, and S. Bhobe. Efficient algorithms for multi query optimization. In Proceedings of the 2000 ACM International Conference on Management of Data, 2000.
16. P. G. Selinger et al. Access path selection in a relational database management system. In Proceedings of the 1979 ACM International Conference on Management of Data, 1979.
17. M. Stillger, G. M. Lohman, V. Markl, and M. Kandil. LEO - DB2's learning optimizer. In Proceedings of the Twenty-seventh International Conference on Very Large Databases, 2001.
18. V. G. Timkovskii. Complexity of common subsequences and supersequence and related problems. In Journal of Cybernetics, 25, 1990.
19. J. S. Vitter. Random sampling with a reservoir. In ACM Trans. Mathematical Software, 11, 1985.