| 电能质量在线监测系统海量数据的双列族存储设计 |
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| 引用本文： | 屈志坚,袁慎高,范明明.电能质量在线监测系统海量数据的双列族存储设计[J].电力系统保护与控制,2019,47(2):154-160. |
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| 作者姓名： | 屈志坚 袁慎高 范明明 |
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| 作者单位： | 华东交通大学电气与自动化工程学院,江西 南昌,330013;华东交通大学电气与自动化工程学院,江西 南昌,330013;华东交通大学电气与自动化工程学院,江西 南昌,330013 |
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| 基金项目： | 国家自然科学基金项目资助(51567008,51867009);江西省杰出青年人才计划项目资助(20162BCB23045);江西省自然科学基金项目资助(20171BAB206044);江西省科技厅应用培育计划项目资助(GJJ160471) |
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| 摘 要： | 针对高效存储海量电能质量在线监测数据的问题,提出一种基于HBase的双列族电能质量在线监测系统数据库设计新方法。通过将HBase的列族存储架构应用到繁杂的电能质量在线监测数据的高效存储中,然后构造存储优化函数来寻找和设计最优的电能质量在线监测数据存储结构。最后进行几种不同列族数的数据读写时间的对比实验。实验证明:所提的电能质量监测数据双列族存储设计方法可以高效存储海量电能质量监测数据,具有较好的可行性。
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| 关 键 词： | 海量数据 电能质量 列族 HBase 存储结构 |
| 收稿时间： | 2018/1/31 0:00:00 |
| 修稿时间： | 2018/3/25 0:00:00 |
Double column family storage design for massive data of power quality online monitoring system |
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| QU Zhijian,YUAN Shengao and FAN Mingming.Double column family storage design for massive data of power quality online monitoring system[J].Power System Protection and Control,2019,47(2):154-160. |
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| Authors: | QU Zhijian YUAN Shengao and FAN Mingming |
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| Affiliation: | School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China,School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China and School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China |
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| Abstract: | Aiming at the problem of massively storing massive monitoring data of mass power quality, a new database design method based on HBase for dual-column power quality monitoring system is proposed. It finds and designs the optimal power quality online monitoring data storage structure by applying column family storage architecture of the HBase to the efficient storage of complex power quality online monitoring data and then building storage optimization functions. Finally, the reading and writing time of several different column families are compared. Experiments show that the proposed double-column family of power quality monitoring data storage design method can store massive power quality monitoring data efficiently and has good feasibility. This work is supported by National Natural Science Foundation of China (No. 51567008 and No. 51867009), Foundation Plan for Distinguished Young Scholars in Jiangxi Province (No. 20162BCB23045), Natural Science Foundation of Jiangxi Province (No. 20171BAB206044) and Science and Technology Research Project of Jiangxi Provincial Science and Technology Department (No. GJJ160471). |
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| Keywords: | massive data power quality column family Hbase storage structure |
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