Big data needs large storage capacity and strong processing frameworks for cleaning, processing, and analysis. Fortunately, cloud computing offers many services and processing frameworks that facilitate storage and processing of big data. But the issue here is how to choose the best suited processing framework adequate to big data of the financial services.we used MCDM methods to solve this decision problem and to evaluate five big data processing frameworks (Spark, Hadoop, Flink, Storm, and Samza) based on twelve criteria. <div><p>Big data needs large storage capacity and strong processing frameworks for cleaning, processing, and analysis. Fortunately, cloud computing offers many services and processing frameworks that facilitate storage and processing of big data. But the issue here is how to choose the best suited processing framework adequate to big data of the financial services.we used MCDM methods to solve this decision problem and to evaluate five big data processing frameworks (Spark, Hadoop, Flink, Storm, and Samza) based on twelve criteria. </p></div>
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B.Sc. of Information Systems 2015, Pre-Master graduated 2017, Faculty of Computers and Information, Mansoura University.
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Taschenbuch. Zustand: Neu. Hybrid Approach for Cloud Services Selection Adequate to Big Data | Fuzzy Analytical Hierarchy Process (FAHP) Using Geometric Mean Method to Select Best Processing Framework | Saly Elbaz | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203029147 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Artikel-Nr. 120290644
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