A Map Tile Data Access Model Based on the Jump Consistent Hash Algorithm

Author:

Wang WeiORCID,Yao XiaojingORCID,Chen Jing

Abstract

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.

Funder

Tianjin Natural Science Foundation

Publisher

MDPI AG

Subject

Earth and Planetary Sciences (miscellaneous),Computers in Earth Sciences,Geography, Planning and Development

Reference34 articles.

1. Digital twin modeling;Tao;J. Manuf. Syst.,2022

2. On Geospatial Information Science in the Era of IoE;Li;Acta Geod. Cartogr. Sin.,2022

3. Characterising the Digital Twin: A systematic literature review;Jones;CIRP J. Manuf. Sci. Technol.,2020

4. Development and Prospect of GIS Platform Software Technology System;Song;J. Geo-Inf. Sci.,2021

5. Big Data GIS;Li;Geomat. Inf. Sci. Wuhan Univ.,2014

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