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Towards a New Model of Storage and Access to Data in Big Data and Cloud Computing

机译:建立大数据和云计算中数据存储和访问的新模型

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>The technological revolution integrating multiple information sources and extension of computer science in different sectors led to the explosion of the data quantities, which reflects the scaling of vo-lumes, numbers and types. These massive increases have resulted in the development of new location techniques and access to data. The final steps in this evolution have emerged new technologies: Cloud and Big Data. The reference implementation of the Clouds and Big Data storage is incontestably the Hadoop Distributed File System (HDFS). This latter is based on the separation of metadata to data that consists in the centralization and isolation of the metadata of storage servers. In this paper, the authors propose an approach to improve the service metadata for Hadoop to maintain consistency without much compromising performance and scalability of metadata by suggesting a mixed solution between centralization and distribution of metadata to enhance the performance and scalability of the model.
机译:>整合多种信息源和计算机科学在不同领域的技术革命导致数据量激增,这反映了卷,数量和类型的缩放比例。这些巨大的增长导致了新的定位技术和数据访问的发展。这种演进的最终步骤已经出现了新技术:云和大数据。云和大数据存储的参考实现无疑是Hadoop分布式文件系统(HDFS)。后者基于元数据与数据的分离,这包括存储服务器元数据的集中和隔离。在本文中,作者提出了一种方法,通过提出元数据集中化和分布之间的混合解决方案以增强模型的性能和可伸缩性,从而在不大大损害元数据的性能和可伸缩性的情况下改善Hadoop的服务元数据,以保持一致性。 >

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