Standard

Optimization of Database Operations in the Application for Text Corpus Analysis. / Barakhnin, Vladimir B.; Karpov, Matvey V.; MacHikina, Elena P. et al.

Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024. Institute of Electrical and Electronics Engineers Inc., 2024. p. 1-6 (Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Harvard

Barakhnin, VB, Karpov, MV, MacHikina, EP & Musasbayev, RR 2024, Optimization of Database Operations in the Application for Text Corpus Analysis. in Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024. Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024, Institute of Electrical and Electronics Engineers Inc., pp. 1-6, 20th International Asian School-Seminar on Optimization Problems of Complex Systems, Новосибирск, Russian Federation, 19.07.2024. https://doi.org/10.1109/OPCS63516.2024.10720387

APA

Barakhnin, V. B., Karpov, M. V., MacHikina, E. P., & Musasbayev, R. R. (2024). Optimization of Database Operations in the Application for Text Corpus Analysis. In Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024 (pp. 1-6). (Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/OPCS63516.2024.10720387

Vancouver

Barakhnin VB, Karpov MV, MacHikina EP, Musasbayev RR. Optimization of Database Operations in the Application for Text Corpus Analysis. In Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024. Institute of Electrical and Electronics Engineers Inc. 2024. p. 1-6. (Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024). doi: 10.1109/OPCS63516.2024.10720387

Author

Barakhnin, Vladimir B. ; Karpov, Matvey V. ; MacHikina, Elena P. et al. / Optimization of Database Operations in the Application for Text Corpus Analysis. Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024. Institute of Electrical and Electronics Engineers Inc., 2024. pp. 1-6 (Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024).

BibTeX

@inproceedings{3397e3f9859a450d8bb0e281757ca700,
title = "Optimization of Database Operations in the Application for Text Corpus Analysis",
abstract = "The user's comfortable work with large volumes of text is ensured by optimizing the web application. This optimization is primarily focused on optimizing work with the database. The SQL query language is an example of a declarative language that allows for effective query optimization.The article formalizes the optimization problem as improving the quality of application usage by increasing the user's productivity in the system. This is achieved by reducing the reaction time of the system in response to user actions.There are three main strategies for query optimization: modifying the source code of the program that interacts with the database, modifying the structure of queries, and modifying the structure of the database itself. The technologies used to create the optimized software system include: the application was written in Python using the Flask web framework. Work with the database was done using the SQLAlchemy library and PostgreSQL was chosen as the DBMS (Database Management System). To test the functionality of the optimized queries, the pytest library was used.Specific optimization examples were presented for the following situations: long execution time for any stage of a data request can be solved by changing the query structure by adding an index. Long execution time for any stage of data change can be solved by deleting the index from the query. A large number of queries within a cycle can be replaced with an equivalent query outside the loop to improve performance.The results of the computational experiments demonstrate the high efficiency of the optimization technique.",
keywords = "query optimization, text corpus analysis, web application optimization",
author = "Barakhnin, {Vladimir B.} and Karpov, {Matvey V.} and MacHikina, {Elena P.} and Musasbayev, {Rustam R.}",
note = "This research was funded by the Committee of Science under the Ministry of Science and Higher Education of the Republic of Kazakhstan, grant BR21882268.; 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024 ; Conference date: 19-07-2024 Through 30-07-2024",
year = "2024",
doi = "10.1109/OPCS63516.2024.10720387",
language = "English",
isbn = "9798331517625",
series = "Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--6",
booktitle = "Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024",
address = "United States",

}

RIS

TY - GEN

T1 - Optimization of Database Operations in the Application for Text Corpus Analysis

AU - Barakhnin, Vladimir B.

AU - Karpov, Matvey V.

AU - MacHikina, Elena P.

AU - Musasbayev, Rustam R.

N1 - Conference code: 20

PY - 2024

Y1 - 2024

N2 - The user's comfortable work with large volumes of text is ensured by optimizing the web application. This optimization is primarily focused on optimizing work with the database. The SQL query language is an example of a declarative language that allows for effective query optimization.The article formalizes the optimization problem as improving the quality of application usage by increasing the user's productivity in the system. This is achieved by reducing the reaction time of the system in response to user actions.There are three main strategies for query optimization: modifying the source code of the program that interacts with the database, modifying the structure of queries, and modifying the structure of the database itself. The technologies used to create the optimized software system include: the application was written in Python using the Flask web framework. Work with the database was done using the SQLAlchemy library and PostgreSQL was chosen as the DBMS (Database Management System). To test the functionality of the optimized queries, the pytest library was used.Specific optimization examples were presented for the following situations: long execution time for any stage of a data request can be solved by changing the query structure by adding an index. Long execution time for any stage of data change can be solved by deleting the index from the query. A large number of queries within a cycle can be replaced with an equivalent query outside the loop to improve performance.The results of the computational experiments demonstrate the high efficiency of the optimization technique.

AB - The user's comfortable work with large volumes of text is ensured by optimizing the web application. This optimization is primarily focused on optimizing work with the database. The SQL query language is an example of a declarative language that allows for effective query optimization.The article formalizes the optimization problem as improving the quality of application usage by increasing the user's productivity in the system. This is achieved by reducing the reaction time of the system in response to user actions.There are three main strategies for query optimization: modifying the source code of the program that interacts with the database, modifying the structure of queries, and modifying the structure of the database itself. The technologies used to create the optimized software system include: the application was written in Python using the Flask web framework. Work with the database was done using the SQLAlchemy library and PostgreSQL was chosen as the DBMS (Database Management System). To test the functionality of the optimized queries, the pytest library was used.Specific optimization examples were presented for the following situations: long execution time for any stage of a data request can be solved by changing the query structure by adding an index. Long execution time for any stage of data change can be solved by deleting the index from the query. A large number of queries within a cycle can be replaced with an equivalent query outside the loop to improve performance.The results of the computational experiments demonstrate the high efficiency of the optimization technique.

KW - query optimization

KW - text corpus analysis

KW - web application optimization

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85208969955&origin=inward&txGid=c5992ff6a52e9b02ae65c5590d9da34e

UR - https://www.mendeley.com/catalogue/1520a927-04b6-344d-a2be-2592b15c57e4/

U2 - 10.1109/OPCS63516.2024.10720387

DO - 10.1109/OPCS63516.2024.10720387

M3 - Conference contribution

SN - 9798331517625

T3 - Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024

SP - 1

EP - 6

BT - Proceedings - 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems, OPCS 2024

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 20th International Asian School-Seminar on Optimization Problems of Complex Systems

Y2 - 19 July 2024 through 30 July 2024

ER -

ID: 61421634