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Bitmap-Based On-line Analytical Processing of Time Interval Data

机译:基于位图的时间间隔数据在线分析处理

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On-line analytical processing is in the focus of research over the last couple decades. Several papers dealing with summarizability problems, cube computations, query languages, fact-dimension relationships or different types of hierarchies have been published. Nowadays, analyzing time interval data became ubiquitous. Nevertheless, the use of established, reliable, and proven technologies like OLAP is desirable in this respect. In this paper, we present an OLAP system capable to process time interval data. The system is based on bitmaps, enabling perform ant selection and fast aggregation. Moreover, we introduce a two-step aggregation technique, which enables the calculation of relevant measures in the context of time interval data. We evaluate the performance of our system using different bitmap implementations and a real-world data set. To our knowledge, there are no other systems available enabling OLAP and providing correct results considering the summarizability of time interval data.
机译:在过去的几十年中,在线分析处理一直是研究的重点。已经发表了几篇有关可概括性问题,多维数据集计算,查询语言,事实维度关系或不同类型的层次结构的论文。如今,分析时间间隔数据变得无处不在。尽管如此,在这方面,仍需要使用已建立的,可靠的和经过验证的技术,例如OLAP。在本文中,我们提出了一种能够处理时间间隔数据的OLAP系统。该系统基于位图,可以执行蚂蚁选择和快速聚合。此外,我们引入了两步聚合技术,该技术可以在时间间隔数据的上下文中计算相关度量。我们使用不同的位图实现方式和实际数据集来评估系统的性能。据我们所知,考虑到时间间隔数据的可汇总性,没有其他可用的系统可以启用OLAP并提供正确的结果。

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