Real-time data Analytics Apache Druid

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dc.contributor.authorFODIL et MOKRAN, Youssouf Islam et Abde lrr ahim
dc.date.accessioned2020-12-06T14:29:59Z
dc.date.available2020-12-06T14:29:59Z
dc.date.issued2020
dc.description.abstractThe development of social media creates a multitude of new Real-Time Analytics (RTA) application possibilities. However, already the topic of big data forced the use of analytical solutions and among them, there are some decent near real-time solutions but using them in the social media analytics domain will reveal some other flaws especially in the context of the real-time analytics where the social media analytics native tools can’t be challenged in general and in real-time analytics specifically. This work aims to address this gap by exposing a decent tool (Technology stack) excels at handling real-time social media analytics by providing abilities like fast processing of data, real-time data aggregation, ingestion, interactive, and effective data exploration, and visualization. We describe our experiments for the architecture in Twitter use case and evaluate the functional and non-functional tests such as real-time update performance and time taken for data flow among components. All components were able to handle their functionalities properly.en_US
dc.identifier.urihttps://repository.univ-msila.dz/handle/123456789/21706
dc.language.isoenen_US
dc.publisherFACULTY: Mathematics and Computer Science DEPARTMENT: Computer Science - OPTION: SI-GLen_US
dc.subjectReal-time data : Analytics Apache Druiden_US
dc.titleReal-time data Analytics Apache Druiden_US
dc.typeThesisen_US

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