Research on Distributed Machine Learning Methods in Databases
- Resource Type
- Conference
- Authors
- Klymash, Mykhailo; Kyryk, Marian; Demydov, Ivan; Hordiichuk-Bublivska, Olena; Kopets, Halyna; Pleskanka, Nazar
- Source
- 2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT) Advanced Information and Communication Technologies (AICT), 2021 IEEE 4th International Conference on. :128-131 Sep, 2021
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Machine learning algorithms
Data analysis
Distributed databases
Machine learning
Computer architecture
Software
Database systems
Big data
databases
machine learning
- Language
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.