Research on Distributed Machine Learning Methods in Databases

M. Klymash, M. Kyryk, I. Demydov, O. Hordiichuk-Bublivska, H. Kopets, N. Pleskanka
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Abstract

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.
数据库中分布式机器学习方法的研究
本文讨论了在数据库中处理大量信息以更有效地执行用户查询的问题。本研究描述了分布式机器学习的方法,它可以更快地分析大数据。提出了一种改进的分布式数据库体系结构,保证了机器学习方法的有效应用。使用分布式机器学习进行数据阵列处理的软件建模。所得结果表明,使用分布式机器学习方法可以提高处理数据库中大量信息的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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