CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Novel Distributed Query Optimization Model and Hybrid Query Optimization Algorithm

by Deepak Sukheja, Umesh Kumar Singh
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 75 - Number 17
Year of Publication: 2013
Authors: Deepak Sukheja, Umesh Kumar Singh
10.5120/13203-0461

Deepak Sukheja, Umesh Kumar Singh . Novel Distributed Query Optimization Model and Hybrid Query Optimization Algorithm. International Journal of Computer Applications. 75, 17 ( August 2013), 22-32. DOI=10.5120/13203-0461

@article{ 10.5120/13203-0461,
author = { Deepak Sukheja, Umesh Kumar Singh },
title = { Novel Distributed Query Optimization Model and Hybrid Query Optimization Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { August 2013 },
volume = { 75 },
number = { 17 },
month = { August },
year = { 2013 },
issn = { 0975-8887 },
pages = { 22-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume75/number17/13203-0461/ },
doi = { 10.5120/13203-0461 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:44:31.232025+05:30
%A Deepak Sukheja
%A Umesh Kumar Singh
%T Novel Distributed Query Optimization Model and Hybrid Query Optimization Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 75
%N 17
%P 22-32
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Query optimization is the most critical phase in query processing. Query optimization in distributed databases explicitly needed in many aspects of the optimization process, this is not only increases the cost of optimization, but also changes the trade-offs involved in the optimization process significantly . This paper describes the synthetically evolution of query optimization methods from uniprocessor relational database systems to parallel database systems. We point out a set of parameters to characterize and compare query optimization methods, mainly: (i) type of algorithm (static or dynamic), (ii) working environments (re-optimization or re-scheduling) and (iii) level of modification. The major contributions of this paper are: (I) Understanding the mechanisms of query optimization methods with respect to the considered environments and their constraints (e. g. parallelism, distribution, heterogeneity, large scale, dynamicity of nodes). (ii) Study the problem of query optimization particular in term of heterogeneously environment and pointing out their main characteristics, which allow comparing them and help to Implement new query optimization algorithm and model. These contributions is led to performance enhancement of query optimization in distributed database system through classify by different QEPs and minimize the response time.

References
  1. M. T. Ozsu and P. Valduriez. "Distributed Database Systems: Where Are We Now?", IEEE Computer, 24(8): 68 - 78, August 1991.
  2. Sanjib Kumar Das, Sayantan Das gupta,"Middle Layer Java Software for the Implementation of a Homogeneous Distributed Database System",DBMS LAB – 2007.
  3. A. V. Aho, Y. Sagiv, and J. D. Ullman. efficient Optimization of a Class of Relational Expressions. Transactions on Database Systems, 4(4):435–454, 1979.
  4. P. Selinger, M. Astrahan, D. Chamberlin, R. Lorie, and T. Price. Access Path Selection in a Relational Database Management System, In Proceedings of ACM SIGMOD International Conference on Management of Data, Boston, Massachusetts, USA, May 1979.
  5. P. M. G. Apers, A. R. Hevner, and S. B. Yao. Optimization Algorithms for Distributed Queries. IEEE Transaction on Software Engineering, 9(1), PP 57-68 1983.
  6. L. F. Mackert andG. M. Lohman. R*Optimizer Validation and Performance Evaluation for Local Queries. Technical report, IBM Research Division, January 1986. IBM Research Report RJ 4989.
  7. M. T. Ozsu and P. Valduriez. Principles of Distributed Database Systems, 2nd edition englewood cliffs, NJ: PrenticeHall, 1991.
  8. H. Lu, M-C. Shan, K-L Tan, "Optimization of Multi-Way Join Queries for Parallel Execution" Proceedings of the 17th International Conference on Very Large Databases, Barcelona, PP: 550-560. September 1991
  9. K-L Tan, H. Lu, "On Resource Scheduling of Multi-Join Queries in Parallel Database Systems", Information Processing Letters 48,1993.
  10. G. Hallmark, "Oracle Parallel Warehouse Server", IEEE 1997.
  11. W. Hong andM. Stonebraker. Optimization of ParallelQuery Execution Plans inXPRS. In Proceedings of the First International Conference on Parallel and Distributed Information Systems, December 1991.
  12. Donald D. Chamberlin, Morton M. Astrahan, Mike W. Blasgen, Jim Gray, W. Frank King III, Bruce G. Lindsay, Raymond A. Lorie, James W. Mehl, Thomas G. Price, Gianfranco R. Putzolu, Patricia G. Selinger, Mario Schkolnick, Donald R. Slutz, Irving L. Traiger, Bradford W. Wade, Robert A. Yost: A History and Evaluation of System R. Commun. ACM 24(10): 632-646 (1981).
  13. STONEBRAKER, M. , AOKI, P. M. , DEVINE, R. , LITWIN, W. , AND OLSON, M. A. 1994. Mariposa: A new architecture for distributed data. In Proceedings of the 10th International Conference on Data Engineering (Houston, TX, Feb. 14–18). IEEE Computer Society Press, Los Alamitos, CA, 54–65.
  14. STONEBRAKER, M. , AOKI, P. M. , LITWIN, W. , PFELLER, A. , SAH, A. , SIDELL, J. , STAELIN, C. , AND YU, A Mariposa, "A wide-area distributed database system", VLDB journal ,vol. 1, 48–63, 1996.
  15. Michael Steinbrun, "Heuristic and randomized optimization for the join ordering problem", The VLDB Journal vol: 6, PP: 191–208, 1997 .
  16. Prasan Roy, Multi-Query Optimization and Applications, Ph. D. Thesis, Dept. of Computer Science and Engineering, IIT-Bombay, December 2000.
  17. Kossmann D. "The State of Art in Distributed Query Optimization", ACM Computing Surveys, September 2000
Index Terms

Computer Science
Information Sciences

Keywords

Query optimization distributed query optimization query optimization algorithm.

Powered by PhDFocusTM