A Study of Performance Optimization Method for Massive Spaito-temporal Data Based on Spatio-temporal Partition Clustering
基于时空分区聚簇的海量时空数据性能优化方法研究

Integrative management of massive spatio-temporal data and the relevant capabilities for time series analysis are important research targets of new generation GIS software architecture.At present,access efficiency of spatial and spatio-temporal data based on seamless massive table mechanism needs solid improvement.For managing massive spatio-temporal data effectively and improving spatio-temporal search performance,partitioning and clustering method of large object-relational database platform are extended to spatio-temporal dimension,and performance optimization method for massive spaito-temporal data based on spatio-temporal partition clustering is presented,which is based on extended relational spatio-temporal data model.The search efficiency test on single table of 2GB to 60GB shows that STPC provides better spaito-temporal search performance(about 10.1%) than the normal data organization methods.