[1] Tom W. Hadoop权威指南:中文版[M]. 周敏奇,王晓玲,金澈清, 译. 北京: 清华大学出版社, 2010:51-55.
[2] DEAN J, GHEMAWAT S.MapReduce: simplified data processing on large clusters[C]//6th Conference on Symposium on Opearting Systems Design & Implementation. Berkeley:USENIX Association, 2004:137-150.
[3] AGNEESWARAN V S. Big data analytics beyond hadoop : real-time applications with storm, spark, and more hadoop alte[M]. New Jersey:Pearson Education, 2014:55-70.
[4] 孙大为, 张广艳, 郑纬民. 大数据流式计算:关键技术及系统实例[J].软件学报, 2014, 25(4):839-862.
SUN Dawei, ZHANG Guangyan, ZHENG Weimin. Big data stream computing: Technologies and instances[J]. Journal of Software, 2014, 25(4):839-862.
[5] 林子雨, 林琛, 冯少荣,等. MESHJOIN*:实时数据仓库环境下的数据流更新算法[J]. 计算机科学与探索, 2010, 04(10):927-939.
LIN Ziyu, LIN Chen, FENG Shaorong, et al. MESHJOIN*: An algorithm supporting streaming updates in a real-time data warehouse[J]. Journal of Frontiers of Computer Science and Technology, 2010, 4(10):927-939.
[6] SILVA B N, KHAN M, HAN K. Big data analytics embedded smart city architecture for performance enhancement through real-time data processing and decision-making[J/OL].Wireless Communications and Mobile Computing,2017, [2017-01-18].https://
DOI.org/10.1155/2017/9429676.
[7] 乔通, 赵卓峰, 丁维龙. 面向套牌甄别的流式计算系统[J]. 计算机应用, 2017, 37(1):153-158.
QIAO Tong, ZHAO Zhuofeng, DING Weilong. Stream computing system for monitoring copy plate vehicles[J]. Journal of Computer Applications, 2017, 37(1):153-158.
[8] 王德文, 杨力平. 智能电网大数据流式处理方法与状态监测异常检测[J]. 电力系统自动化, 2016, 40(14):122-128.
WANG Dewen, YANG Liping. Stream processing method and condition monitoring anomaly detection for big data in smart grid[J]. Automation of Electric Power Systems, 2016, 40(14): 122-128.
[9] 刘子英, 唐宏建, 肖嘉耀,等. 基于流式计算的Web实时故障诊断分析与设计[J]. 华东交通大学学报, 2014(1):119-123.
LIU Ziying, TANG Hongjian, XIAO Jiayao, et al. Analysis and design of web real-time fault diagnosis based on stream computing[J]. Journal of East China Jiaotong University, 2014(1):119-123.
[10] 高欢. 基于流式计算的网络舆情分析模型研究[J]. 情报学报, 2016, 35(7):723-729.
GAO Huan. Research on model of network public opinion analysis based on stream computing[J]. Journal of the China Society for Scientific and Technical Information, 2016, 35(7):723-729.
[11] 张丽岩, 马健. 流式计算在交通信息实时处理中的应用框架初探[J]. 物流科技, 2014, 37(9):8-9.
ZHANG Liyan, MA Jian. A preliminary application framework study of stream computing in traffic information real-time processing[J]. Logistics Sci-Tech, 2014, 37(9):8-9.
[12] 周建宁, 徐晓东, 蔡岗. 流式计算在交通管理中应用研究[J]. 中国公共安全:学术版, 2016(1):70-75.
ZHOU Jianning, XU Xiaodong, CAI Gang. Study on the application of steam computing in traffic management[J]. China Public Security, Academy Edition, 2016(1):70-75.
[13] SHRUTHI K, SIDDHARTH P. Easy, real-time big data analysis using storm [EB/OL]. [2012-12-04]. http://www.drdobbs.com/cloud/easy-real-time-big-data-analysis-using-s/240143874?pgno=1.
[14] 张少敏, 孙婕, 王保义. 基于Storm的智能电网广域测量系统数据实时加密[J]. 电力系统自动化, 2016, 40(21):123-127.
ZHANG Shaomin, SUN Jie, WANG Baoyi. Storm based real-time data encryption in wide area measurement system of smart grid[J]. Automation of Electric Power Systems, 2016, 40(21):123-127.
[15] 王铭坤, 袁少光, 朱永利,等. 基于Storm的海量数据实时聚类[J]. 计算机应用, 2014, 34(11):3078-3081.
WANG Mingkun, YUAN Shaoguang, ZHU Yongli, et al. Real-time clustering for massive data using storm[J]. Journal of Computer Applications, 2014, 34(11):3078-3081.
[16] 阿里云. 流计算产品特点[EB/OL]. [2017-02-28]. https://help.aliyun.com/document_detail/49930.html ?spm=5176.doc49929.6.550.DVbqvj.
[17] 阿里云. 阿里云DataHub[EB/OL]. [2016-11-21]. https://data.aliyun.com/product/datahub?spm=a2c0j.117599.588239.11.abJECp.
[18] 阿里云. DataV数据可视化[EB/OL]. [2016-09-15]. https://data.aliyun.com/visual/datav?spm=a2c0j.117599.416540.109.abJECp.
[19] 鲍永胜. 局部放电脉冲波形特征提取及分类技术[J]. 中国电机工程学报, 2013, 33(28):168-175.
BAO Yongsheng. Partial discharge pulse waveform feature extraction and classification techniques[J]. Proceedings of the CSEE, 2013, 33(28):168-175.
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