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作 者:李恩洲 况立群[1] 张元[1] 韩燮[1] 熊风光[1] LI En-zhou;KUANG Li-qun;ZHANG Yuan;HAN Xie;XIONG Feng-guang(School of Big Data,North University of China,Taiyuan 030051,China)
出 处:《计算机技术与发展》2021年第11期176-182,188,共8页Computer Technology and Development
基 金:国家重点研发计划(2018YFB2101504)
摘 要:针对供热环境在城市间一体化程度的提高而引发的设备种类繁多、采集信息量大、数据类型多样化、处理和分析困难以及各设备数据信息展示不直观的问题,研发并实现了一种智慧供热大数据监测平台,并在山西省供热体系中进行了应用。平台以云计算为基础架构,采用基于React的前端技术,将开发模块组件化,并通过构建虚拟DOM(虚拟文档对象)机制解决了因复杂和频繁的DOM操作引发的性能瓶颈问题。针对供热设备产生数据的结构特点,研发基于kafka+Spark Streaming的数据清洗方案,解决了因数据量大、种类多样化而产生的数据处理效率、存储设备压力以及实时数据传输问题。此外,平台还提供了定制化的可视化界面,并且通过数据分批处理机制,解决了实时数据和大数据量展示过程中响应慢的问题。Aiming at the problems of various types of equipment,large amount of collected information,diversification of data types,difficulties in processing and analysis,and unintuitive display of data information of various equipment caused by the increase in the degree of integration of thermal companies in various regions,we research and implement a smart heating big data monitoring platform,which is applied in the heating system of Shanxi Province.Based on cloud computing and React front-end technology,the platform componentizes development modules and solves performance bottlenecks caused by complex and frequent DOM operations by building a virtual DOM(virtual document object)mechanism.In view of the structural characteristics of data generated by heating equipmen,a data cleaning solution based on kafka+Spark Streaming is developed to solve the problems of data processing efficiency,storage equipment pressure and real-time data transmission caused by the large amount of data and the diversification of types.In addition,the platform also provides a customized visualization interface and solves the problem of slow response during real-time data and large data presentation through the data batch processing mechanism.
关 键 词:智慧供热 监测 React 可视化 B/S kafka Spark Streaming
分 类 号:TP311.5[自动化与计算机技术—计算机软件与理论]
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