Efficient Index and Query Algorithm Based on Geospatial Big Data

In recent years, with the rapid development of advanced technologies such as intelligent target recognition, electronic sensors, collaborative control and computer networks, intelligent transportation systems have achieved qualitative leapfrogging. Modern intelligent transportation systems can realize intelligent transportation of vehicles, roads and clouds management platform. However, the intelligent transportation system relies on a large amount of two-dimensional geospatial information data generated every day. Therefore, how to efficiently store and query large-scale geospatial data is of great significance for the future popularization and development of the intelligent transportation system. However, due to the complexity of urban traffic information, large amount of data, and fast update speed, the current spatial indexing technology is difficult to efficiently search for two-dimensional geospatial information data. In order to optimize the storage organization structure of two-dimensional geospatial information data under spatial big data and improve retrieval efficiency, this paper proposes a spatial index tree construction algorithm for multi-layer slice recursion of two-dimensional geospatial information data (multi-layer slice recursive, MSR). The proposed algorithm first sorts and divides the first dimension of the map data to generate FD slices. Then, the second dimension of the map data in the FD slice is sorted to generate SD slices, and in the SD slice, the current slice and the adjacent slices are divided into spatial objects. Finally, data clustering operation is performed on the comparison between the length of the spatial object and the node capacity, and the MSR Tree is recursively generated from the bottom up by judging whether all the slices complete the clustering operation. Experimental results show that the query performance of the 2-dimensional space storage structure constructed by the MSR algorithm is better than the most representative spatial indexing technology based on the R-tree batch-loading algorithm (sort tile recursive, STR), STR-grid hybrid algorithm (str-grid), and efficient geometric range query (EGRQ).