关键词: 农业农村大数据, 混合云架构, 云边端协同, 数据资源池, Hadoop, 农业数据要素

Abstract:

With the advancement of the digital rural strategy, the agricultural and rural sectors are increasingly demanding data resource integration, business collaboration, and intelligent services. This paper proposes a design scheme for an agricultural and rural data fusion service platform based on Hadoop, emphasizing the aggregation and service needs of agricultural and rural data resources. It indicatively constructs a hybrid deployment platform model that combines "cloud-edge-end" with centralized management areas and its key technical solutions. The platform relies on advanced privacy protection and data security technologies, such as "blockchain + privacy computation," to build the technical foundation that supports the value realization of agricultural and rural data elements. It provides management capabilities and integrated services throughout the entire life cycle of data collection, governance, fusion, and application, targeting the value-added needs of agricultural and rural data elements. The platform has aggregated over 30 categories of agricultural and rural data, totaling approximately 500GB, covering multiple dimensions such as production, management, and services. Research has been conducted around the platform architecture, deployment architecture, key technologies, and application scenarios to build a data fusion service platform for agricultural and rural modernization. This explores solutions to challenges such as clear ownership of agricultural data, unambiguous value recognition, and trustworthy transaction processes. Leveraging the big data technology system, it promotes the circulation and sharing of agricultural data elements, deep value mining, and efficient asset transformation. In typical query scenarios, the platform achieves a performance of average response latency below 100 milliseconds for multi-dimensional data retrieval. The platform significantly enhances data security and full-chain traceability during the transaction process, effectively addressing the deficiencies in performance, capacity, and multi-purpose support of massive agricultural and rural data. It also provides a standardized paradigm for cross-departmental government collaboration and data sharing, accelerates the cultivation of the agricultural and rural data element market, and empowers the high-quality development of the rural digital economy.

Key words: agricultural and rural big data, hybrid cloud architecture, cloud edge collaboration, data resource pool, Hadoop, agricultural data elements