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dc.contributor.authorTalakh, M. V.en
dc.contributor.authorTomka, Yu. Ya.en
dc.contributor.authorUshenko, Yu. O.en
dc.contributor.authorSoltys, I. V.en
dc.date.accessioned2023-03-30T13:05:44Z
dc.date.available2023-03-30T13:05:44Z
dc.date.issued2022
dc.identifier.citationPossibilities of using Hadoop and R to analyze large arrays of geospatial data [Text] / M. V. Talakh, Yu. Ya. Tomka, Yu. O. Ushenko, I. V. Soltys // Оптико-електронні інформаційно-енергетичні технології. – 2022. – № 2. – С. 49-54.en
dc.identifier.issn1681-7893
dc.identifier.urihttp://ir.lib.vntu.edu.ua//handle/123456789/36598
dc.description.abstractThe main problems associated with the processing of Big Data, in particular arrays containing geospatial data, are analyzed. The Hadoop platform is considered one of the basic approaches to the analysis of large data arrays and the possibility of its integration with the R environment. The potential possibilities of using the Hadoop platform for solving practical problems in the process of analyzing geospatial and spatiotemporal data are analyzed.en
dc.description.abstractПроаналізовані основні проблеми пов’язані з обробкою Big Data, зокрема масивів, що містять геопросторові дані. Розглянуто платформу Hadoop, як один з базових підходів до аналізу великих масивів даних та можливості її інтеграції з середовищем R. Проаналізовано потенційні можливості використання платформи Hadoop для вирішення практичних задач в процесі аналізу геопросторових та просторово-часових даних.uk
dc.language.isoenen
dc.publisherВНТУuk
dc.relation.urihttps://oeipt.vntu.edu.ua/index.php/oeipt/article/view/620
dc.relation.uriОптико-електронні інформаційно-енергетичні технології. № 2 : 49-54.uk
dc.subjectBig Dataen
dc.subjectgeospatial dataen
dc.subjectлогічна операціяuk
dc.subjectHadoopen
dc.subjectR languageen
dc.subject«великі дані»uk
dc.subjectгеопросторові даніuk
dc.subjectлогічна операціяuk
dc.subjectHadoopen
dc.subjectмова Ruk
dc.titlePossibilities of using Hadoop and R to analyze large arrays of geospatial dataen
dc.typeArticle
dc.identifier.udc004.75
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dc.identifier.doi10.31649/1681-7893-2022-44-2-49-54


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