Research on Distributed Machine Learning Methods in Databases

• Published in: 2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT) pp. 128 - 131
• Main Authors: Klymash, Mykhailo, Kyryk, Marian, Demydov, Ivan, Hordiichuk-Bublivska, Olena, Kopets, Halyna, Pleskanka, Nazar
• Format: Conference Proceeding
• Language: English
• Published: IEEE 21-09-2021
• Subjects: Big data; Computer architecture; Data analysis; Database systems; Distributed databases; Machine learning; Machine learning algorithms; Software
• DOI: 10.1109/AICT52120.2021.9628949

This article discusses the problems of processing large amounts of information in databases to more efficiently execute user queries. The methods of distributed machine learning were described in this research, which allow a faster analysis of large data. A modification of the distributed database system architecture was proposed, which ensures the effective application of machine learning methods. Software modeling of data arrays processing using distributed machine learning has been carried out. The obtained results indicate an increase in the efficiency of processing large amounts of information in databases using distributed machine learning methods.