Mathematical Model of the Mechanism for Generating SQL Questions in the ORM Layer of the Hibernate Framework

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Problem statement. Modern ORM frameworks, such as Hibernate, automate the process of interaction with databases, which significantly simplifies development. However, their performance, in particular the speed of generating SQL queries, can significantly depend on the structure of the input data, its volume, and caching settings. Insufficient understanding of these factors can lead to unreasonable delays in application operation. Goal. To study the influence of the structure and size of the input data on the process of generating SQL queries in the ORM layer of the Hibernate framework, and to evaluate the role of caching in optimizing execution time. Results. The study identified the key components involved in generating SQL queries. A mathematical model was developed that describes the query generation time depending on the input data and caching settings. The model allows predicting the performance of the ORM layer for various configurations. Practical significance. The results can be used to optimize the operation of applications using Hibernate, as well as to select optimal caching parameters and data organization. This is especially important for highly loaded systems where performance is critical.

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作者简介

Boris Goryachkin

Bauman Moscow State Technical University

编辑信件的主要联系方式.
Email: bsgor@mail.ru
ORCID iD: 0000-0002-0852-4162
SPIN 代码: 5465-3012

Cand. Sci. (Eng.), Associate Professor

俄罗斯联邦, Moscow

Yulia Svetasheva

Bauman Moscow State Technical University

Email: svetasheva2001@gmail.com
ORCID iD: 0009-0002-0470-0998
俄罗斯联邦, Moscow

参考

  1. Goryachkin B.S., Hanmurzin T.I. Improving the efficiency of working with a web resource due to the tools of a system programmer. Dynamics of Complex Systems – 21st Century. 2022. Vol. 16. No. 3. Pp. 26–39. doi: 10.18127/j19997493-202203-03.
  2. Grigoriev Yu.A. Estimation of execution time of SQL queries to databases. Mechanical Engineering and Computer Technologies. 2012. No. 01.
  3. Gudilin D.S., Zvonarev A.E., Goryachkin B.S., Lychagin D.A. Relational database performance comparation. In: 5th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE). IEEE, 2023. Vol. 5. Pp. 1–5.
  4. Eliseeva E.A., Goryachkin B.S., Vinogradova M.V. Research of DBMS performance when working with cluster databases based on ergonomic analysis. StudNet. 2022. Vol. 5. No. 4. Pp. 2888–2910.

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1. JATS XML
2. Fig. 1. Interaction with a database through an ORM layer

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3. Fig. 2. Dependence of generation time on the number of fields in the table

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4. Fig. 3. Dependence of generation time on complex filtering conditions

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5. Fig. 4. Dependence of generation time on the number of subqueries

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6. Fig. 5. Dependence of query generation time on the number of fields

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7. Fig. 6. Dependence of query generation time on the number of complex filters

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8. Fig. 7. Dependence of query generation time on the number of subqueries

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9. Fig. 8. Dependence of query generation time on the number of fields

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10. Fig. 9. Dependence of query generation time on the number of complex filters

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11. Fig. 10. Dependence of query generation time on the number of subqueries

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