How Good Are Modern Spatial Libraries?
Abstract 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...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer Singapore
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/1721.1/136863 |
| _version_ | 1826197101463207936 |
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| author | Pandey, Varun van Renen, Alexander Kipf, Andreas Kemper, Alfons |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Pandey, Varun van Renen, Alexander Kipf, Andreas Kemper, Alfons |
| author_sort | Pandey, Varun |
| collection | MIT |
| description | Abstract
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. |
| first_indexed | 2024-09-23T10:42:49Z |
| format | Article |
| id | mit-1721.1/136863 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T10:42:49Z |
| publishDate | 2021 |
| publisher | Springer Singapore |
| record_format | dspace |
| spelling | mit-1721.1/1368632023-09-19T18:44:16Z How Good Are Modern Spatial Libraries? Pandey, Varun van Renen, Alexander Kipf, Andreas Kemper, Alfons Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Computer Science Applications Computational Mechanics Abstract 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. 2021-11-01T14:33:51Z 2021-11-01T14:33:51Z 2020-11-7 2021-05-23T03:16:45Z Article http://purl.org/eprint/type/JournalArticle 2364-1185 2364-1541 https://hdl.handle.net/1721.1/136863 PUBLISHER_CC en https://doi.org/10.1007/s41019-020-00147-9 Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf Springer Singapore Springer Singapore |
| spellingShingle | Computer Science Applications Computational Mechanics Pandey, Varun van Renen, Alexander Kipf, Andreas Kemper, Alfons How Good Are Modern Spatial Libraries? |
| title | How Good Are Modern Spatial Libraries? |
| title_full | How Good Are Modern Spatial Libraries? |
| title_fullStr | How Good Are Modern Spatial Libraries? |
| title_full_unstemmed | How Good Are Modern Spatial Libraries? |
| title_short | How Good Are Modern Spatial Libraries? |
| title_sort | how good are modern spatial libraries |
| topic | Computer Science Applications Computational Mechanics |
| url | https://hdl.handle.net/1721.1/136863 |
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