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Skyline and reverse skyline query processing in SpatialHadoop

机译:SpatialHadoop中的地平线和反向天际线查询处理

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In this paper, we study the problem of skyline and reverse skyline computation using SpatialHadoop, an extension of Hadoop that enhances its capabilities with spatial awareness. The exploitation of spatial indexing structures and the spatial properties of data can exploit MapReduce-based methods by reducing the reading, writing, computational and communicational overhead. Through our study, we propose two methods for skyline and reverse skyline computation, which operates in the spatial aware environment that SpatialHadoop provides. This environment allows for performing filtering on the initial dataset to retrieve an answer efficiently by using existing state-of-the-art indexing approaches. The proposed algorithms make use of the full capabilities of the indexing mechanisms provided by the SpatialHadoop and have been tested against large-scale datasets including a real-life, large-scale OpenStreetMap dataset. To the best of our knowledge, this is the first work that studies reverse skyline over SpatialHadoop.
机译:在本文中,我们使用SpatialHadoop研究了地平线和反向天际线计算的问题,这是Hadoop的延伸,从而增强其具有空间意识的能力。空间索引结构的开发和数据的空间特性可以通过减少读数,写入,计算和通信开销来利用基于MapReduce的方法。通过我们的研究,我们提出了两种用于地平线和反向天际线计算的方法,它在SpatialHadoop提供的空间意识环境中运行。此环境允许通过使用现有的最先进的索引方法对初始数据集进行过滤以有效地检索答案。所提出的算法利用SpatialHadoop提供的索引机制的完整能力,并且已经针对大规模数据集进行测试,包括现实生活,大规模的大规模OpenStreetMap数据集。据我们所知,这是第一个研究倒车上的地平线的工作。

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