A Map Tile Data Access Model Based on the Jump Consistent Hash Algorithm
Tiled maps are one of the key GIS technologies used in the development and construction of WebGIS in the era of big data; there is an urgent need for high-performance tile map services hosted on big data GIS platforms. To address the current inefficiency of massive tile map data management and acces...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-12-01
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| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/11/12/608 |
| _version_ | 1797457366921248768 |
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| author | Wei Wang Xiaojing Yao Jing Chen |
| author_facet | Wei Wang Xiaojing Yao Jing Chen |
| author_sort | Wei Wang |
| collection | DOAJ |
| description | Tiled maps are one of the key GIS technologies used in the development and construction of WebGIS in the era of big data; there is an urgent need for high-performance tile map services hosted on big data GIS platforms. To address the current inefficiency of massive tile map data management and access, this paper proposes a massive tile map data access model that utilizes the jump consistent hash algorithm. Via the uniformity and consistency of a certain seed of a pseudo-random function, the algorithm can generate a storage slot for each tile data efficiently. By recording the slot information in the head of a row key, a uniform distribution of the tiles on the physical cluster nodes is achieved. This effectively solves the problem of hotspotting caused by the monotonicity of tile row keys in the data access process, thereby maximizing the random-access performance of a big data platform and greatly improving concurrent database access. Experiments show that this model can significantly improve the efficiency of tile map data access by more than 39% compared to a direct storage method, thereby confirming the model’s advantages in accessing massive tile map data on a big data GIS platform. |
| first_indexed | 2024-03-09T16:21:12Z |
| format | Article |
| id | doaj.art-ee17a011b6464e6ea992e631f586e9df |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-09T16:21:12Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-ee17a011b6464e6ea992e631f586e9df2023-11-24T15:21:09ZengMDPI AGISPRS International Journal of Geo-Information2220-99642022-12-01111260810.3390/ijgi11120608A Map Tile Data Access Model Based on the Jump Consistent Hash AlgorithmWei Wang0Xiaojing Yao1Jing Chen2College of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin 300391, ChinaThe Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaCollege of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin 300391, ChinaTiled maps are one of the key GIS technologies used in the development and construction of WebGIS in the era of big data; there is an urgent need for high-performance tile map services hosted on big data GIS platforms. To address the current inefficiency of massive tile map data management and access, this paper proposes a massive tile map data access model that utilizes the jump consistent hash algorithm. Via the uniformity and consistency of a certain seed of a pseudo-random function, the algorithm can generate a storage slot for each tile data efficiently. By recording the slot information in the head of a row key, a uniform distribution of the tiles on the physical cluster nodes is achieved. This effectively solves the problem of hotspotting caused by the monotonicity of tile row keys in the data access process, thereby maximizing the random-access performance of a big data platform and greatly improving concurrent database access. Experiments show that this model can significantly improve the efficiency of tile map data access by more than 39% compared to a direct storage method, thereby confirming the model’s advantages in accessing massive tile map data on a big data GIS platform.https://www.mdpi.com/2220-9964/11/12/608hotspottingjump consistent hash algorithmmap tilesNoSQL database |
| spellingShingle | Wei Wang Xiaojing Yao Jing Chen A Map Tile Data Access Model Based on the Jump Consistent Hash Algorithm ISPRS International Journal of Geo-Information hotspotting jump consistent hash algorithm map tiles NoSQL database |
| title | A Map Tile Data Access Model Based on the Jump Consistent Hash Algorithm |
| title_full | A Map Tile Data Access Model Based on the Jump Consistent Hash Algorithm |
| title_fullStr | A Map Tile Data Access Model Based on the Jump Consistent Hash Algorithm |
| title_full_unstemmed | A Map Tile Data Access Model Based on the Jump Consistent Hash Algorithm |
| title_short | A Map Tile Data Access Model Based on the Jump Consistent Hash Algorithm |
| title_sort | map tile data access model based on the jump consistent hash algorithm |
| topic | hotspotting jump consistent hash algorithm map tiles NoSQL database |
| url | https://www.mdpi.com/2220-9964/11/12/608 |
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