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Approximate Query Answering Using Data Warehouse Striping

机译:使用数据仓库条带进行近似查询回答

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This paper presents an approach to implement large data warehouses on an arbitrary number of computers, achieving very high query execution performance and scalability. The data is distributed and processed in a potentially large number of autonomous computers using our technique called data warehouse striping (DWS). The major problem of DWS technique is that it would require a very expensive cluster of computers with fault tolerant capabilities to prevent a fault in a single computer to stop the whole system. In this paper, we propose a radically different approach to deal with the problem of the unavailability of one or more computers in the cluster, allowing the use of DWS with a very large number of inexpensive computers. The proposed approach is based on approximate query answering techniques that make it possible to deliver an approximate answer to the user even when one or more computers in the cluster are not available. The evaluation presented in the paper shows both analytically and experimentally that the approximate results obtained this way have a very small error that can be negligible in most of the cases.
机译:本文提出了一种在任意数量的计算机上实现大型数据仓库的方法,可实现非常高的查询执行性能和可伸缩性。使用我们称为数据仓库条带化(DWS)的技术,可以在大量潜在的自治计算机中分发和处理数据。 DWS技术的主要问题在于,它将需要非常昂贵的具有容错功能的计算机集群,以防止单个计算机中的故障来停止整个系统。在本文中,我们提出了一种截然不同的方法来解决群集中一台或多台计算机不可用的问题,从而允许将DWS与大量廉价计算机一起使用。所提出的方法基于近似查询回答技术,即使在群集中的一台或多台计算机不可用的情况下,该技术也可以将近似答案传递给用户。本文中提出的评估在分析和实验上均表明,以这种方式获得的近似结果具有很小的误差,在大多数情况下可以忽略不计。

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