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How Good Are Modern Spatial Libraries?

机译:现代空间图书馆有多好?

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Many applications today like Uber, Yelp, Tinder, etc. rely on spatial data or locations from its users. These applications and services either build their own spatial data management systems or rely on existing solutions. JTS Topology Suite (JTS), its C++ port GEOS, Google S2, ESRI Geometry API, and Java Spatial Index (JSI) are some of the spatial processing libraries that these systems build upon. These applications and services depend on indexing capabilities available in these libraries for high-performance spatial query processing. In this work, we compare these libraries qualitatively and quantitatively based on four different spatial queries using two real world datasets. We also compare these libraries with an open-source implementation of the Vantage Point Tree—an index structure that has been well studied in image retrieval and nearest-neighbor search algorithms for high-dimensional data. We found that Vantage Point Trees are very competitive and even outperform the aforementioned libraries in two queries.
机译:今天许多应用程序如优步,yelp,火种等依赖于其用户的空间数据或位置。这些应用程序和服务要么建立自己的空间数据管理系统,要么依赖于现有解决方案。 JTS拓扑套件(JTS),其C ++端口GEOS,Google S2,ESRI几何API和Java Spatial Index(JSI)是这些系统构建的一些空间处理库。这些应用程序和服务取决于这些库中可用的索引功能,用于高性能空间查询处理。在这项工作中,我们基于使用两个真实世界数据集的四个不同空间查询来比较这些库。我们还将这些库与Vantage Point Tree的开源实现进行了比较 - 在​​图像检索和最近的邻近搜索算法中进行了很好地研究的索引结构,用于高维数据。我们发现,有利的角度树是非常竞争力的,甚至优于两个查询中上述图书馆。

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