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基于大数据和QT的农机配件供应链云平台系统设计 预览

Design of Cloud Platform System for Supply Chain of Agricultural Machinery Parts Based on Large Data and QT
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摘要 随着农业现代化水平的不断提高,农业机械被广泛的应用在耕种作业过程中,农机配件的需求量也不断增加,但当前农机配件产品的生产流通环节的监控力度很小,容易造成农机配件的质量安全问题。为了解决这个问题,保证农机配件供应链的可溯源性,基于大数据和QT软件界面开发工具,提出了农机配件供应链数据存储和查询的云平台系统,旨在提高农机配件供应链的数据存储和查询效率,保证农机配件的可溯源性。为了验证平台的可行性,搭建了农机配件供应链的大数据云平台,在平台的底层的Hadoop集群上搭建了8台服务器,以搜索查询农机配件的各种参数数据为测试目的,对平台进行了测试,并将其与传统的MySQL服务器进行了对比。测试结果表明:在搜索数据较少时,云平台和传统服务器的速度相当;但在大数据搜索条件下,云平台的数据处理速度是传统服务器的数倍,从而验证了云平台系统的优越性,为保证农机配件的安全和可溯源性提供了可靠的技术保障。 With the continuously improve the level of agricultural modernization,agricultural machinery is widely used in the farming operation process,demand for agricultural machinery parts are also increasing,but it is very small efforts to monitor the production and circulation of the agricultural machinery accessories products,easy to cause the quality safety problems of agricultural machinery parts.In order to solve this problem,ensure agricultural machinery parts supply chain traceability,it introduced the big data and QT software interface development tool based on the proposed cloud platform system of agricultural machinery parts supply chain data storage and query,thereby improving the agricultural machinery parts supply chain data storage and query efficiency,ensure the traceability of agricultural machinery parts.In order to verify the feasibility of the platform,to build a large data cloud platform of agricultural machinery parts of the supply chain,to build 8 servers in the Hadoop cluster platform at the bottom,to search various parameters of parts of agricultural machinery for testing purposes,the platform is tested,and the traditional MySQL server are compared.The test results indicate that the search in less data,cloud platforms and traditional server speed,but the search conditions in big data,the data processing speed of cloud platform is the traditional server several times,so as to verify the superiority of cloud platform system,in order to ensure the safety of agricultural machinery parts and traceability technology provides reliable guarantee.
作者 周倩 周林妹 康丽军 Zhou Qian;Zhou Linmei;Kang Lijun(Changsha Commerce&Tourism College,Changsha 410016,China;Department of Computer Science and Engineering,Taiyuan University,Taiyuan 030032,China)
出处 《农机化研究》 北大核心 2019年第7期207-211,共5页 Journal of Agricultural Mechanization Research
基金 湖南省科技厅科技创新计划项目(湘科发{2017}28号) 山西省教育厅教育科学规划项目(GH-13147).
关键词 农机配件 QT开发工具 供应链 大数据 云平台 agricultural machinery accessories QT development tools supply chain large data cloud platform
作者简介 周倩(1984-),女,长沙人,讲师,硕士,(E-mail)qzhou1818@21cn.com。
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