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Big Data Processing with Apache Spark in Tertiary Institutions: Spark Streaming

机译:高校使用Apache Spark进行大数据处理:Spark流

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In tertiary institutions, different set of information are derived from the various department and other functional sections. Individual departments and other functional sections in the institutions manage their data separately. This situation has resulted in huge number of different set of data across the various departments in tertiary institutions. There is no centralized data centre where data/information can be retrieved for the management committee when the need arises. In academic institution data captured is restricted to the institution which collected it but centralisation of the various data in the various functional sections does not exist. This makes it difficult for the management committee to take decisions based on relevant information needed. In order to address this problem, we proposed Spark Streaming. Spark Streaming is an element which facilitates processing of live flows of data. Spark streaming will able to capture data in real time, process it and make it available to the management committee when the need arises
机译:在大专院校中,来自各个部门和其他职能部门的信息不同。机构中的各个部门和其他职能部门分别管理其数据。这种情况已导致大专院校各个部门的大量不同数据集。没有集中式数据中心,可以在需要时为管理委员会检索数据/信息。在学术机构中,捕获的数据仅限于收集它的机构,但是不存在各种功能部分中各种数据的集中化。这使得管理委员会难以根据所需的相关信息做出决策。为了解决这个问题,我们提出了Spark Streaming。 Spark Streaming是有助于处理实时数据流的元素。 Spark流媒体将能够实时捕获数据,对其进行处理并在需要时将其提供给管理委员会

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