Investigation in Recommendations for Troubleshooting of Ineffectiveness of Queries to Database Tables

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Ali Mohammed Saleh Ahmed

Abstract

 One of the ways to increase work output of the applications connected with a database is the optimization of queries to database tables. Importance of query optimization issue increases with the growth of records number to decades and hundreds of thousands of tables which the query is referring for. There are various recommendations on troubleshooting of queries performance deceleration. However, there are no results of experimental investigations on the effectiveness of applying other recommendations given in scientific literature. The authors have conducted numerical experiments for the investigation of recommendations, both existing and proposed by the authors, to determine the quantitative values of the effectiveness of applying recommendations. A number of recommendations are illustrated by means of examples of applying recommendations including several alternative variations. The work describes the differences in the effectiveness of applying recommendations in different systems of database management considered in this article. The work describes relative values of the effectiveness of applying recommendations compared with source queries. As a result of the article, the authors have developed the algorithm of query text analysis and applying recommendations. Investigation results expand knowledge on practical applying both known and new recommendations for optimization of queries to database tables. The article has a practical orientation and it is methodically useful for first-time programmers in a field of structured queries language.

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How to Cite
[1]
“Investigation in Recommendations for Troubleshooting of Ineffectiveness of Queries to Database Tables”, JUBPAS, vol. 26, no. 10, pp. 273–280, Dec. 2018, doi: 10.29196/jubpas.v26i10.1885.
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Articles

How to Cite

[1]
“Investigation in Recommendations for Troubleshooting of Ineffectiveness of Queries to Database Tables”, JUBPAS, vol. 26, no. 10, pp. 273–280, Dec. 2018, doi: 10.29196/jubpas.v26i10.1885.

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