标题:Multi-sourced data storage and index construction for equipment condition assessment
作者:Ma, Yan ;Guo, Zhihong ;Chen, Yufeng ;Zou, Lida
作者机构:[Ma, Yan ;Guo, Zhihong ;Chen, Yufeng ] State Grid Shandong Electric Power Research Institute, Jinan 250002, China;[Zou, Lida ] School of Computer Scie 更多
会议名称:2014 6th International Conference on Computational Intelligence and Communication Networks, CICN 2014
会议日期:14 November 2014 through 16 November 2014
来源:Proceedings - 2014 6th International Conference on Computational Intelligence and Communication Networks, CICN 2014
出版年:2014
页码:681-685
DOI:10.1109/CICN.2014.150
关键词:condition assessment; Hbase; metadata; multi-sourced data; secondary index
摘要:With constant promotion and deepening of smart power grids, the data volume of power grid operation and equipment monitoring gain exponential growth and the environment of big data in electric system forms. Many platforms are deployed to meet different demands of equipment operation and maintenance. Since these platforms are independent and cannot be used in coordination, multi-sourced heterogeneous data become mainstream. Integrated storage and performance optimization of multi-sourced heterogeneous data are critical for condition assessment of power transmission and transformation equipment and security operation of power systems. In the paper, it focuses on the integration and optimization of multi-sourced data and design a storage schema of big data which can distributedly process and analyze data. It presents the storage schema of multi-sourced data based on HBase and a description method of metadata, which achieve the lossless and scalable integration of multi-sourced data. To solve the problem of low query efficiency due to the nonsupport of HBase for secondary index, it also proposes a constructing approach of secondary index for the attributes which are often used in the query tree of condition assessment. Extensive experiments show that the proposed storage schema of multi-sourced data and secondary index constructing approach have better query performance and index updating efficiency. © 2014 IEEE.
收录类别:EI;SCOPUS
Scopus被引频次:4
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946692331&doi=10.1109%2fCICN.2014.150&partnerID=40&md5=c30f78b9b8a6d4bd7624d407a1049f00
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