Abstract
Actual scientific and practical task of creating information technology for construction of distributed data warehouses of hybrid type taking into account the properties of data and statistics of queries to the storage is considered in the article. The analysis of the problem of data warehouses construction taking into account data properties and executable queries is carried out. The conceptual, logical and physical models of distributed storages and inter-level transitions procedures are proposed. Location of data on the nodes, data replication routes are determined by criterion of the minimum total cost of data storage and processing using a modified genetic algorithm.
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Prokhorov, I., Kolesnik, N.: Development of a master data consolidation system model (on the example of the banking sector). Procedia Comput. Sci. 145, 412–417 (2018)
Jovanovic, P., Romero, O., Simitsis, A., Abell, A.: Incremental consolidation of data-intensive multi-flows. Trans. Knowl. Data Eng. 28(5), 1203–1216 (2016)
Merendino, A., Dibb, S., Meadows, M., Quinn, L., Wilson, D., Simkin, L., Canhoto, A.: Big data, big decisions: the impact of big data on board level decision-making. J. Bus. Res. 93, 67–78 (2018)
Bomba, A., Nazaruk, M., Pasichnyk, V., Veretennikova, N., Kunanets, N.: Information technologies of modeling processes for preparation of professionals in smart cities. In: Advances in Intelligent Systems and Computing, vol. 754, pp. 702–712 (2018)
Kunanets, N., Lukasz, W., Pasichnyk, V., Duda, O., Matsiuk, O., Falat, P.: Cloud computing technologies in “smart city” projects. In: 9th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Romania, pp. 339–342 (2017)
Mavridis, I., Karatza, H.: Performance evaluation of cloud-based log file analysis with Apache Hadoop and Apache Spark. J. Syst. Softw. 125, 133–151 (2017)
Glushkova, D., Jovanovic, P., Abelló, A.: Mapreduce performance model for Hadoop 2.x. Inf. Syst. 79, 32–43 (2019)
Rzheuskyi, A., Kunanets, N., Kut, V.: Methodology of research the library information services: the case of USA university libraries. In: Advances in Intelligent Systems and Computing II, vol. 689, pp. 450–460 (2018)
Rzheuskiy, A., Veretennikova, N., Kunanets, N., Kut, V.: The information support of virtual research teams by means of cloud managers. Int. J. Intell. Syst. Appl. (IJISA) 10(2), 37–46 (2018). https://doi.org/10.5815/ijisa.2018.02.04
Ansari, M., Smith, J.S.: Warehouse Operations Data Structure (WODS): a data structure developed for warehouse operations modeling. Comput. Ind. Eng. 112, 11–19 (2017)
Bani, F.C.D., Suharjito, Diana, Girsang, A.S.: Implementation of database massively parallel processing system to build scalability on process data warehouse. Procedia Comput. Sci. 135, 68–79 (2018)
Peleshko, D., Rak, T., Izonin, I.: Image superresolution via divergence matrix and automatic detection of crossover. Int. J. Intell. Syst. Appl. (IJISA) 8(12), 1–8 (2016). https://doi.org/10.5815/ijisa.2016.12.01
Izonin, I., Trostianchyn, A., Duriagina, Z., Tkachenko, R., Tepla, T., Lotoshynska, N.: The combined use of the Wiener polynomial and SVM for material classification task in medical implants production. Int. J. Intell. Syst. Appl. (IJISA) 10(9), 40–47 (2018). https://doi.org/10.5815/ijisa.2018.09.05
Lytvyn, V., Vysotska, V., Peleshchak, I., Rishnyak, I., Peleshchak, R.: Time dependence of the output signal morphology for nonlinear oscillator neuron based on Van der Pol model. Int. J. Intell. Syst. Appl. (IJISA) 10(4), 8–17 (2018). https://doi.org/10.5815/ijisa.2018.04.02
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Tomashevskyi, V., Yatsyshyn, A., Pasichnyk, V., Kunanets, N., Rzheuskyi, A. (2020). Data Warhouses of Hybrid Type: Features of Construction. In: Hu, Z., Petoukhov, S., Dychka, I., He, M. (eds) Advances in Computer Science for Engineering and Education II. ICCSEEA 2019. Advances in Intelligent Systems and Computing, vol 938. Springer, Cham. https://doi.org/10.1007/978-3-030-16621-2_30
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DOI: https://doi.org/10.1007/978-3-030-16621-2_30
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