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A spatial grid index based on inverted index and its query method

机译:基于倒排索引的空间网格索引及其查询方法

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With the rapid development of the internet technology and sensor technology, the global spatial data, along with its large-volume and multi-scale features, demonstrates higher requirements for data organization. The spatial grid has been widely used in many map index. However, when spatial objects have multi-scale, the spatial grid index with equivalent grids has been critized for its low-efficiencies. To solve this problem, we proposed a logical index as well as inverted index based on GeoSOT subdivision grids. A logical index is established for detailing the inside information of spatial objects and it is organized as inverted index which is an index data structure storing a mapping from content. By means of this index, we can achieve query operation efficiently regardless of the scales of spatial objects. A series of experiments are conducted to authenticate the advantages of the proposed method. In the experiment, we perform our model on MySQL database and randomly generate 50 thousand spatial object(polygons) as simulated data. Moreover, we compare our model to spatial grid index model with equivalent grids to verify its efficiency. Experimental results show that our approach performs 2 times faster than traditional method.
机译:随着互联网技术和传感器技术的飞速发展,全球空间数据及其大容量和多尺度特征对数据组织提出了更高的要求。空间网格已在许多地图索引中得到广泛使用。但是,当空间对象具有多尺度时,具有等效网格的空间网格索引因其低效率而受到批评。为了解决这个问题,我们提出了基于GeoSOT细分网格的逻辑索引和倒排索引。建立逻辑索引以详细说明空间对象的内部信息,并将其组织为倒排索引,该倒排索引是存储来自内容的映射的索引数据结构。借助此索引,​​无论空间对象的规模如何,我们都可以高效地实现查询操作。进行一系列实验以验证所提出方法的优点。在实验中,我们在MySQL数据库上执行模型,并随机生成5万个空间对象(多边形)作为模拟数据。此外,我们将模型与具有等效网格的空间网格索引模型进行比较,以验证其效率。实验结果表明,我们的方法比传统方法快2倍。

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