A Distributed Spatial Data Warehouse for AIS Data (DIPAAL)
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866918296790499328 |
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| author | Klitgaard, Alex S. Josefsen, Lau E. Mikkelsen, Mikael V. Torp, Kristian |
| author_facet | Klitgaard, Alex S. Josefsen, Lau E. Mikkelsen, Mikael V. Torp, Kristian |
| contents | AIS data from ships is excellent for analyzing single-ship movements and monitoring all ships within a specific area. However, the AIS data needs to be cleaned, processed, and stored before being usable. This paper presents a system consisting of an efficient and modular ETL process for loading AIS data, as well as a distributed spatial data warehouse storing the trajectories of ships. To efficiently analyze a large set of ships, a raster approach to querying the AIS data is proposed. A spatially partitioned data warehouse with a granularized cell representation and heatmap presentation is designed, developed, and evaluated. Currently the data warehouse stores ~312 million kilometers of ship trajectories and more than +8 billion rows in the largest table. It is found that searching the cell representation is faster than searching the trajectory representation. Further, we show that the spatially divided shards enable a consistently good scale-up for both cell and heatmap analytics in large areas, ranging between 354% to 1164% with a 5x increase in workers |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_13795 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Distributed Spatial Data Warehouse for AIS Data (DIPAAL) Klitgaard, Alex S. Josefsen, Lau E. Mikkelsen, Mikael V. Torp, Kristian Databases AIS data from ships is excellent for analyzing single-ship movements and monitoring all ships within a specific area. However, the AIS data needs to be cleaned, processed, and stored before being usable. This paper presents a system consisting of an efficient and modular ETL process for loading AIS data, as well as a distributed spatial data warehouse storing the trajectories of ships. To efficiently analyze a large set of ships, a raster approach to querying the AIS data is proposed. A spatially partitioned data warehouse with a granularized cell representation and heatmap presentation is designed, developed, and evaluated. Currently the data warehouse stores ~312 million kilometers of ship trajectories and more than +8 billion rows in the largest table. It is found that searching the cell representation is faster than searching the trajectory representation. Further, we show that the spatially divided shards enable a consistently good scale-up for both cell and heatmap analytics in large areas, ranging between 354% to 1164% with a 5x increase in workers |
| title | A Distributed Spatial Data Warehouse for AIS Data (DIPAAL) |
| topic | Databases |
| url | https://arxiv.org/abs/2601.13795 |