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Polystore Data Management Systems for Managing Scientific Data-sets in Big Data Archives

机译:用于管理大数据档案中的科学数据集的多宇数据管理系统

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Large scale scientific data sets are often analyzed for the purpose of supporting workflow and querying. User need to query over different data sources. These systems manage intermediate results. Most prototypes are complex and have an ad hoc design. These require extensive modifications in case of growth of data and change of scale, in terms of data or number of users. New data sources may arise to further complicate the ad hoc design. The polystore data management approach provides 'data independence' for changes in data profile, including addition of cloud data resources. The users are often provided a quasi-relational query language. In many cases, the polystore systems support distinct tasks that are user defined workflow activity, in addition to providing a common view of data resources.
机译:通常分析大规模的科学数据集以支持工作流程和查询。用户需要在不同的数据源上查询。这些系统管理中间结果。大多数原型都很复杂,并且具有临时设计。在数据或用户数量方面,这些要求在数据和规模变化的情况下进行大量修改。可能出现新的数据源以进一步复杂化AD Hoc设计。 PolyStore数据管理方法为数据配置文件的变化提供“数据独立性”,包括添加云数据资源。用户通常提供了一种准关系查询语言。在许多情况下,除了提供数据资源的公共视图之外,PolyStore Systems还支持用户定义的工作流程活动的不同任务。

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