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Optimization of river network representation data models for web?¢????based systems

机译:基于Web的系统的河网表示数据模型的优化

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Web?¢????based systems allow users to filter data and resources using river network structure on interactive map environments that use server side processing. With the increasing resolution of river networks, optimized methods for storage of river network representation in databases and efficient queries on the river network structure become critical. This paper presents a detailed study of widely used methods for representing generic networks in relational databases and benchmarking common queries on river network data using these methods. The analysis has been applied to a data set consisting of the river network of Iowa, with over 620,000 individual subwatershedsodes in the network. For typical river network queries (path to the outlet; contributing watersheds), two of considered data models (Adjacency List and Nested Set) guarantee response times below 1????s. This will allow users to carry out large?¢????scale analysis and visualizations tasks on the web for hydrological data sets. A new data model, Stream Network, is proposed based on Path Enumeration, stores directly additional hydrological information, enabling, for example, retrieval of the main stream.
机译:基于Web的系统允许用户在使用服务器端处理的交互式地图环境中使用River网络结构过滤数据和资源。随着河网分辨率的提高,用于在数据库中存储河网表示形式以及对河网结构进行有效查询的优化方法变得至关重要。本文介绍了广泛使用的方法的详细研究,这些方法在关系数据库中表示通用网络,并使用这些方法对河流网络数据的常见查询进行基准测试。该分析已应用于由爱荷华州河网组成的数据集,该网络中有超过620,000个单独的小流域/节点。对于典型的河网查询(到出口的路径;分水岭),两个考虑的数据模型(邻接表和嵌套集)保证响应时间小于1 s。这将使用户可以在网上针对水文数据集进行大规模的分析和可视化任务。提出了一种基于路径枚举的新数据模型“流网络”,该模型直接存储附加的水文信息,例如可以检索主流。

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