ISOMER: Consistent histogram construction using query feedback

Proceedings - International Conference on Data Engineering

Volumn 2006, Issue , 2006, Pages 39-

  Srivastava, U ^a   Haas, P J ^b   Markl, V ^b   Megiddo, N ^b   Kutsch, M ^c   Tran, T M ^b  

^a STANFORD UNIVERSITY   (United States)

^b IBM ALMADEN RESEARCH CENTER   (United States)

^c IBM   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ISOMER; MAXIMUM ENTROPY PRINCIPLE; MULTIDIMENSIONAL HISTOGRAMS; QUERY FEEDBACK;

ALGORITHMS; CORRELATION METHODS; DATA REDUCTION; DATABASE SYSTEMS; ESTIMATION; PROBLEM SOLVING; QUERY LANGUAGES;

FEEDBACK CONTROL;

EID: 33749605988     PISSN: 10844627     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDE.2006.84     Document Type: Conference Paper

References (19)

1. A. Aboulnaga and S. Chaudhuri. Self-tuning histograms: building histograms without looking at data. In SIGMOD 1999.
2. E. Amaldi and V. Kann. The complexity and approximability of finding maximum feasible subsystems of linear relations. Theoretical Computer Science, pages 181-210, 1995.
3. S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, 2004.
4. N. Bruno, S. Chaudhuri, and L. Gravano. STHoles: A multi-dimensional workload-aware histogram. In SIGMOD 2001.
5. S. Chaudhuri, R. Motwani, and V. Narasayya. Random sampling for histogram construction: How much is enough? In SIGMOD 1998.
6. C. Chen and N. Roussopoulos. Adaptive selectivity estimation using query feedback. In SIGMOD 1994.
7. A. Deshpande, M. Garofalakis, and R. Rastogi. Independence is good: dependency-based histogram synopses for high-dimensional data. In SIGMOD 2001.
8. S. Guha, K. Shim, and J. Woo. REHIST: Relative Error Histogram Construction Algorithms. In VLDB 2004.
9. D. Gunopulos, G. Kollios, V. Tsotras, and C. Domeniconi. Approximating multi-dimensional aggregate range queries over real attributes. In SIGMOD 2000.
10. E. Jaynes. Information theory and statistical mechanics. Physical Reviews, 1957.
11. L. Lim, M. Wang, and J. Vitter. SASH: A self-adaptive histogram set for dynamically changing workloads. In VLDB 2003.
12. V. Markl et al. Consistently estimating the selectivity of conjuncts of predicates. In VLDB 2005.
13. Y. Matias, J. Vitter, and M. Wang. Wavelet-based histograms for selectivity estimation. In SIGMOD 1998.
14. M. Muralikrishna and D. DeWitt. Equi-depth histograms for estimating selectivity factors for multidimensional queries. In SIGMOD 1988.
15. V. Poosala and Y. Ioannidis. Selectivity estimation without the attribute value independence assumption. In VLDB 1997.
16. J. Shore and R. Johnson. Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy. IEEE Trans. Information Theory, 26(1):26-37, Jan. 1980.
17. M. Stillger, G. Lohman, V. Markl, and M. Kandil. LEO - DB2's Learning Optimizer. In VLDB 2001.
18. Computational Infrastructure for Operations Research. http://www.coin-or.org/.
19. N. Thaper, S. Guha, P. Indyk, and N. Koudas. Dynamic multidimensional histograms. In SIGMOD 2002.