Big Data Storage Index Mechanism Based on Spatiotemporal Information Cloud Platform

Abstract

In order to study the storage and management mechanism of raster data and vector data for different purposes in data services, a research method of big data storage and indexing mechanism based on spatiotemporal information cloud platform is proposed. This paper discusses the application of big data storage index in virtualization platform, cloud management software, and storage management, so that Hadoop cluster can use the dynamic expansion ability of cloud platform to obtain better expansion ability. High performance statistical applications for geographical conditions are constructed. A high performance geostatistical analysis system Hadoop-Geostatistics is designed and implemented. A variety of spatial statistics index calculation, flow, and MapReduce algorithm was realized. The experimental results show that in the cluster environment, the time consumption is basically the same as that of the single index calculation, while in the single computer environment, when the comprehensive index is calculated in parallel for 10,000 statistical objects, the system performance drops rapidly and reaches an early inflection point. In the comprehensive statistical concurrent calculation, when the time consumption reaches 5 × 10^7, the amount of calculation data is as high as 7000, which increases linearly. The experimental data show that the designed spatiotemporal information cloud platform model can store spatial big data, and the storage method is very accurate. By establishing a spatiotemporal information cloud platform, cloud computing technology can provide higher spatial information services.