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Data Storage Architecture and Retrieval Based on Water Conservancy Data and Computer Technologies
Abstract
The reasonable storage and retrieval of spatial data in rivers and lakes can promote the development of river and lake management and protection projects. In order to efficiently store and retrieve river and lake spatial data, this study adopts river and lake data and computer technology to design a data storage architecture and retrieval method based on river and lake spatial data types. The design of the structured data storage architecture adopts relational databases and document databases with spatial indexing characteristics. Use a geospatial data abstraction library to read and write raster image data from unstructured data, and use Elasticsearch to retrieve metadata. The test results show that the minimum latency of this architecture is 13ms, the average response time is 78ms, the maximum throughput is 14000 req/s, and the average failure rate is 0.106%. The designed architecture and database performance are excellent, providing technical support for efficient storage and retrieval of river and lake spatial data.
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