测绘地理信息统计准实时数据仓库架构的设计及应用

Design and Application of Quasi-Real-Time Data Warehouse Architecture for Surveying and Mapping Geographic Information Statistics

摘要:

随着测绘地理信息行业的发展，基础测绘产品体系和技术手段的不断升级完善对原有的测绘范围、内容和技术手段以及相关支撑服务都有新的要求。为满足测绘地理信息行业各项统计调查任务数据采集和分析需求，设计面向测绘地理信息统计业务的准实时数据仓库架构、业务主题以及存储模型等。其中，数据仓库架构包括两个加载触发器，将历史数据仓库加载数据的触发器放置在实时数据仓库规模达到5 000条时能够使得联合统计分析获得较高性能；根据测绘地理信息统计频率，基于季度、半年和年度3个主题域构建了3套多维数据模型；最后，对不同特征的数据采取不同策略经过抽取、清洗和转换之后加载到数据仓库并清空实时数据仓库。依托测绘地理信息统计准实时数据仓库，初步应用实践表明，测绘地理信息统计网络直报系统实现节点汇总、综合查询和批量分析功能，有效提高了数据采集、统计分析的效率和效果。未来，测绘地理信息统计工作应及时升级现有的数据仓库模型和分析手段，重点关注数据信息安全。

Abstract:

With the development of the surveying and mapping geographic information industry, the continuous upgrading and improvement of the basic surveying and mapping product system and technical means have new requirements for the original surveying and mapping scope, content, technical means, and related support services. To meet the data collection and analysis needs of various statistical survey tasks in the surveying and mapping geographic information industry, a quasi real-time data warehouse architecture, business themes, and storage models are designed for the surveying and mapping geographic information statistics. Among them, the data warehouse architecture includes two loading triggers. Placing the trigger for loading data from the historical data warehouse in a real-time data warehouse with a scale of 5000 can achieve high performance in joint statistical analysis; Based on the frequency of surveying and mapping geographic information statistics, three sets of multidimensional data models are constructed based on three thematic domains; Finally, different strategies are adopted for data with different features, which are extracted, cleaned, and transformed before being loaded into the data warehouse. Based on the quasi real-time data warehouse of surveying and mapping geographic information statistics, preliminary application practice has shown that the surveying and mapping geographic information statistics network reporting system realizes node summary, comprehensive query, and batch analysis functions, effectively improving the efficiency and effectiveness of data collection and statistical analysis. In the future, the statistical work of surveying and mapping geographic information should upgrade existing data warehouse models and analysis methods, with a focus on data information security.