陈真玄 1，王 琳 1，张 怡 2，孟庆学 3

　　(1.水利部信息中心，北京 100053;

　　2.北京金水信息技术发展有限公司，北京 100053;

　　3.北京沛海科技有限公司，北京 100083)

　　摘 要：如何更加高效地存储和处理海量非结构化数据，已成为水利行业信息化建设亟待解决的难题，水文预报业务作为水利行业的核心业务，选择合适的数据库是首要任务。对目前国产主流数据库进行梳理，将非结构化数据库分为数据库结合 NAS、数据库大字段、多模数据库 3 种类型，针对每种类型，分析原理、特点、数据处理时效性、支持的数据量、数据查询效率等多个方面，对部分类型进行压力测试，获取量化性能指标，使选型者可以结合自身应用场景进行比较分析选择合适类型，并基于水文预报业务数据库选型经验，提出水利非结构化数据库选型建议。通过分析认为不同的业务需求适合不同的数据库类型，对于水文预报业务这类海量非结构化数据存储管理、且数据处理能力要求高的场景建议选用数据库大字段或多模数据库。

　　关键词：水文预报业务;非结构化数据;数据库选型;NAS;数据库大字段;多模数据库

　　Discussion on selection of unstructured database for hydrological forecasting

　　CHEN Zhenxuan 1，WANG Lin 1，ZHANG Yi 2，MENG Qingxue 3

　　(1.Information Center，Ministry of Water Resources，Beijing 100053，China;

　　2.Beijing Jinshui Information Technology Development Co.，Ltd.，Beijing 100053，China;

　　3.Beijing PowehiDB Technology Co.，Ltd.，Beijing 100083，China)

　　Abstract：How to store and process massive unstructured data more efficiently has become an urgent problem to be solved in the information development of the water conservancy industry. As the core business of the water conservancy industry, hydrological forecasting is the fundamental task to select an appropriate database. By researching on the current domestic mainstream databases, the unstructured databases are categorized into three types: database combined with NAS, database with large fields and multi-mode database. For each type, this paper analyzes its principle, features, effectiveness of data processing, supported data size, efficiency of data query and other aspects. Pressure tests are conducted on some types to obtain quantitative performance indicators, so that the users can select the appropriate type through comparative analysis in combination with their own application scenarios, and propose suggestions on unstructured database selection of water conservancy based on the database selection experience of hydrological forecasting business. The analysis shows that, different database types are suitable for different business needs. For hydrological forecasting business with high requirements for storage and management of massive unstructured data, as well as for data processing capacity, it is recommended to select database with large fields or multi-mode database.

　　Key words：hydrological forecasting;unstructured data;database selection;NAS;database with large fields;multi-mode database