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Cited 4 time in webofscience Cited 11 time in scopus
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Integrating of data using the Hadoop and R

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dc.contributor.authorUskenbayeva, R.-
dc.contributor.authorKuandykov, A.-
dc.contributor.authorCho, Y.I.-
dc.contributor.authorTemirbolatova, T.-
dc.contributor.authorAmanzholova, S.-
dc.contributor.authorKozhamzharova, D.-
dc.date.available2020-02-28T10:45:32Z-
dc.date.created2020-02-12-
dc.date.issued2015-
dc.identifier.issn1877-0509-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/10958-
dc.description.abstractThe article offers a data integration model, which must be supported by a unified view of disparate data sources, management of integrity constraints, management of data manipulation and query executing operations, matching data from various sources, the ability to expand and set up new data sources. The proposed approach is the integration of Hadoop-based data and R, which is popular for processing statistical information. Hadoop database contains libraries, Distributed File System (HDFS), and resource management platform and implements a version of the MapReduce programming model for processing large-scale data. This model allows us to integrate various data sources at any level, by setting arbitrary links between circuit elements, constraints and operations. © 2015 Published by Elsevier B.V.This is an open access article under the CC BY-NC-ND license.-
dc.language영어-
dc.language.isoen-
dc.publisherElsevier B.V.-
dc.relation.isPartOfProcedia Computer Science-
dc.subjectAcoustic streaming-
dc.subjectBig data-
dc.subjectData handling-
dc.subjectData integration-
dc.subjectDistributed computer systems-
dc.subjectDistributed database systems-
dc.subjectQuery processing-
dc.subjectDistributed file systems-
dc.subjectHadoop-
dc.subjectIntegrity constraints-
dc.subjectMap-reduce programming-
dc.subjectR-
dc.subjectRHadoop-
dc.subjectRhipe-
dc.subjectStatistical information-
dc.subjectInformation management-
dc.titleIntegrating of data using the Hadoop and R-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.wosid000373734500019-
dc.identifier.doi10.1016/j.procs.2015.07.187-
dc.identifier.bibliographicCitationProcedia Computer Science, v.56, no.1, pp.145 - 149-
dc.identifier.scopusid2-s2.0-84939199805-
dc.citation.endPage149-
dc.citation.startPage145-
dc.citation.titleProcedia Computer Science-
dc.citation.volume56-
dc.citation.number1-
dc.contributor.affiliatedAuthorCho, Y.I.-
dc.type.docTypeProceedings Paper-
dc.subject.keywordAuthorBig data-
dc.subject.keywordAuthorHadoop-
dc.subject.keywordAuthorR-
dc.subject.keywordAuthorRHadoop-
dc.subject.keywordAuthorRhipe-
dc.subject.keywordAuthorStreaming-
dc.subject.keywordPlusAcoustic streaming-
dc.subject.keywordPlusBig data-
dc.subject.keywordPlusData handling-
dc.subject.keywordPlusData integration-
dc.subject.keywordPlusDistributed computer systems-
dc.subject.keywordPlusDistributed database systems-
dc.subject.keywordPlusQuery processing-
dc.subject.keywordPlusDistributed file systems-
dc.subject.keywordPlusHadoop-
dc.subject.keywordPlusIntegrity constraints-
dc.subject.keywordPlusMap-reduce programming-
dc.subject.keywordPlusR-
dc.subject.keywordPlusRHadoop-
dc.subject.keywordPlusRhipe-
dc.subject.keywordPlusStatistical information-
dc.subject.keywordPlusInformation management-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Hardware & Architecture-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.description.journalRegisteredClassscopus-
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