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Statistical Analysis of DSS Query Optimizer for a Five Join DSS Query

by Manik Sharma, Gurvinder Singh, Rajinder Singh, Sarbjit Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 141 - Number 6
Year of Publication: 2016
Authors: Manik Sharma, Gurvinder Singh, Rajinder Singh, Sarbjit Singh
10.5120/ijca2016909627

Manik Sharma, Gurvinder Singh, Rajinder Singh, Sarbjit Singh . Statistical Analysis of DSS Query Optimizer for a Five Join DSS Query. International Journal of Computer Applications. 141, 6 ( May 2016), 1-4. DOI=10.5120/ijca2016909627

@article{ 10.5120/ijca2016909627,
author = { Manik Sharma, Gurvinder Singh, Rajinder Singh, Sarbjit Singh },
title = { Statistical Analysis of DSS Query Optimizer for a Five Join DSS Query },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 141 },
number = { 6 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume141/number6/24785-2016909627/ },
doi = { 10.5120/ijca2016909627 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:42:42.938910+05:30
%A Manik Sharma
%A Gurvinder Singh
%A Rajinder Singh
%A Sarbjit Singh
%T Statistical Analysis of DSS Query Optimizer for a Five Join DSS Query
%J International Journal of Computer Applications
%@ 0975-8887
%V 141
%N 6
%P 1-4
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Statistics is a multidisciplinary subject which is used in different domains to mine decisive information from phenomenal volume of data. The aspiration of this paper is to examine the results of two different DSS query optimizers. The design of DSS query optimizer is based upon restricted exhaustive enumeration and a fusion of entropy and genetic algorithm called DSQ_REA and DSQ_ERGA. A five join DSS query is considered for assessing the results of DSQ_REA and DSQ_ERGA. The output of query optimizers is the plan that determine the location where the sub operations of the query would be executed. The objective of query optimizer is to select a query execution path that uses least amount of system resources. The outcomes of DSQ_REA and DSQ_ERGA are statistically analyzed by using different measures of descriptive statistics. Moreover, outlier analysis of the results has been carried out. In addition, the distribution of the results is also examined to reveal the deviation in the different query execution plans generated by DSQ_EA and DSQ_ERGA. With this statistical analysis, one is able to recognize the nature and distribution of different query execution paths generated with DSQ_REA and DSQ_ERGA.

References
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  4. Manik Sharma, Gurvinder Singh, Rajinder Singh. “Design and Analysis of Stochastic DSS Query Optimizer in a Distributed Database System”. Egypitan Informatics Journal. doi:10.1016/j.eij.2015.10.003.
  5. Manik Sharma, Gurvinder Singh, Rajinder Singh and Gurdev Singh. 2015. “Analysis of DSS Queries using Entropy based Restricted Genetic Algorithm”. Applied Mathematics and Information Science. Vol. 9, Issue 5.
  6. Clark D. French. One Size Fits All- Database Architecture Do Not Work for DSS. ACM SIGMOD Newsletter1995:24-2:449-450.
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  10. Sangkyu Rho, Salvatore T. March. Optimizing Distributed Join Queries: A GA Approach. Annals of Operation Research 1997; 71:199-228.
  11. Manik Sharma, Gurdev Singh. Analysis of Joins and Semi Joins in Centralized and Distributed Database Queries. IEEE Xplore 2012; 978-1-4673-2647-6:15-20.
  12. TPC Benchmark DS, Version 1.1.0, April 2002 http://www.tpc.org (Accessed on June 2013).
Index Terms

Computer Science
Information Sciences

Keywords

Statistical Analysis DSS Query Optimizer Entropy Genetic Algorithm.

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