[1]李恩洲,况立群*,张 元,等.智慧供热大数据监测平台研究及应用[J].计算机技术与发展,2021,31(11):176-182.[doi:10. 3969 / j. issn. 1673-629X. 2021. 11. 029]
　LI En-zhou,KUANG Li-qun*,ZHANG Yuan,et al.Research and Application of Big Data Monitoring Platform for Intelligent Heating[J].,2021,31(11):176-182.[doi:10. 3969 / j. issn. 1673-629X. 2021. 11. 029]
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智慧供热大数据监测平台研究及应用()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
31
期数:
2021年11期
页码:
176-182
栏目:
应用前沿与综合
出版日期:
2021-11-10

文章信息/Info

Title:
Research and Application of Big Data Monitoring Platform for Intelligent Heating
文章编号:
1673-629X(2021)11-0176-07
作者:
李恩洲; 况立群* ; 张 元; 韩 燮; 熊风光
中北大学 大数据学院,山西 太原 030051
Author(s):
LI En-zhou; KUANG Li-qun* ; ZHANG Yuan; HAN Xie; XIONG Feng-guang
School of Big Data,North University of China,Taiyuan 030051,China
关键词:
智慧供热; 监测; React; 可视化; B / S; kafka; Spark Streaming
Keywords:
intelligent heating; monitor; React; visualization; B / S; kafka; Spark Streaming
分类号:
TP311. 5
DOI:
10. 3969 / j. issn. 1673-629X. 2021. 11. 029
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。
Abstract:
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 equipment,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.

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更新日期/Last Update: 2021-11-10