OPTIMIZATION OF MYSQL DATABASE
Abstract
The performance of MySQL, a well-known open-source relational database management system used in a variety of sectors, including e-commerce, finance, and healthcare, can be improved through the use of physical programming and data tuning. While data tuning involves refining the database to increase efficiency, physical programming involves optimizing the physical storage of data. This article gives a general introduction of MySQL and its architecture, looks at the many methods and tools used in physical programming and data tuning, and talks about the advantages of these techniques and how they affect MySQL's performance.
References
Duan, S., Thummala, V., & Babu, S. (2009). Tuning database configuration parameters with ituned. Proceedings of the VLDB Endowment, 2(1), 1246-1257
DuBois, P. (2008). MySQL. Pearson Education.
Győrödi, C., Győrödi, R., Pecherle, G., & Olah, A. (2015, June). A comparative study: MongoDB vs. MySQL. In 2015 13th International Conference on Engineering of Modern Electric Systems (EMES) (pp. 1-6). IEEE.
Janjua, J. I., Khan, T. A., Zulfiqar, S., & Usman, M. Q. (2022, August). An Architecture of MySQL Storage Engines to Increase the Resource Utilization. In 2022 International Balkan Conference on Communications and Networking (BalkanCom) (pp. 68-72). IEEE.
Maesaroh, S., Gunawan, H., Lestari, A., Tsaurie, M. S. A., & Fauji, M. (2022). Query optimization in mysql database using index. International Journal of Cyber and IT Service Management, 2(2), 104-110.
Marathe, A. P., Lin, S., Yu, W., El Gebaly, K., Larson, P. Å., & Sun, C. (2022, March). Integrating the Orca Optimizer into MySQL. In EDBT (pp. 2-511).
Patil, M. M., Hanni, A., Tejeshwar, C. H., & Patil, P. (2017, February). A qualitative analysis of the performance of MongoDB vs MySQL database based on insertion and retriewal operations using a web/android application to explore load balancing—Sharding in MongoDB and its advantages. In 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC) (pp. 325-330). IEEE.
Rautmare, S., & Bhalerao, D. M. (2016, October). MySQL and NoSQL database comparison for IoT application. In 2016 IEEE international conference on advances in computer applications (ICACA) (pp. 235-238). IEEE.
Schwartz, B., Zaitsev, P., & Tkachenko, V. (2012). High performance MySQL: optimization, backups, and replication. " O'Reilly Media, Inc.".
Stjepanovic, D., Savic, M., Jokić, J., & Marić, S. (2015, November). Performance measurements of some aspects of multi-threaded access to key-value stores. In 2015 23rd Telecommunications Forum Telfor (TELFOR) (pp. 831-834). IEEE.
Tahaghoghi, S. M., & Williams, H. E. (2006). Learning MySQL: Get a Handle on Your Data. " O'Reilly Media, Inc.".
Van Aken, D., Pavlo, A., Gordon, G. J., & Zhang, B. (2017, May). Automatic database management system tuning through large-scale machine learning. In Proceedings of the 2017 ACM international conference on management of data (pp. 1009-1024).
Wahyudi, J., Asbari, M., Sasono, I., Pramono, T., & Novitasari, D. (2022). Database Management Education in MYSQL. Edumaspul: Jurnal Pendidikan, 6(2), 2413-2417.
Wang, B., Dai, L., & Liao, B. (2023). System architecture design of a multimedia platform to increase awareness of cultural heritage: A case study of sustainable cultural heritage. Sustainability, 15(3), 2504.