Distributed Storage System for Electric Power Data Based on HBase
Managing massive electric power data is a typical big data application because electric power systems generate millions or billions of status, debugging, and error records every single day. To guarantee the safety and sustainability of electric power systems, massive electric power data need to be p...
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2018-12-01
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| Series: | Big Data Mining and Analytics |
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| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2018.9020026 |
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| _version_ | 1832568972583632896 |
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| author | Jiahui Jin Aibo Song Huan Gong Yingying Xue Mingyang Du Fang Dong Junzhou Luo |
| author_facet | Jiahui Jin Aibo Song Huan Gong Yingying Xue Mingyang Du Fang Dong Junzhou Luo |
| author_sort | Jiahui Jin |
| collection | DOAJ |
| description | Managing massive electric power data is a typical big data application because electric power systems generate millions or billions of status, debugging, and error records every single day. To guarantee the safety and sustainability of electric power systems, massive electric power data need to be processed and analyzed quickly to make real-time decisions. Traditional solutions typically use relational databases to manage electric power data. However, relational databases cannot efficiently process and analyze massive electric power data when the data size increases significantly. In this paper, we show how electric power data can be managed by using HBase, a distributed database maintained by Apache. Our system consists of clients, HBase database, status monitors, data migration modules, and data fragmentation modules. We evaluate the performance of our system through a series of experiments. We also show how HBase’s parameters can be tuned to improve the efficiency of our system. |
| format | Article |
| id | doaj-art-3f700f51e37e4aa68356e4c6c4936944 |
| institution | Kabale University |
| issn | 2096-0654 |
| language | English |
| publishDate | 2018-12-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj-art-3f700f51e37e4aa68356e4c6c49369442025-02-02T23:47:25ZengTsinghua University PressBig Data Mining and Analytics2096-06542018-12-011432433410.26599/BDMA.2018.9020026Distributed Storage System for Electric Power Data Based on HBaseJiahui Jin0Aibo Song1Huan Gong2Yingying Xue3Mingyang Du4Fang Dong5Junzhou Luo6<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>Southeast University</institution>, <city>Nanjing</city> <postal-code>211189</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>Southeast University</institution>, <city>Nanjing</city> <postal-code>211189</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>Southeast University</institution>, <city>Nanjing</city> <postal-code>211189</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>Southeast University</institution>, <city>Nanjing</city> <postal-code>211189</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>Southeast University</institution>, <city>Nanjing</city> <postal-code>211189</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>Southeast University</institution>, <city>Nanjing</city> <postal-code>211189</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>Southeast University</institution>, <city>Nanjing</city> <postal-code>211189</postal-code>, <country>China</country>.Managing massive electric power data is a typical big data application because electric power systems generate millions or billions of status, debugging, and error records every single day. To guarantee the safety and sustainability of electric power systems, massive electric power data need to be processed and analyzed quickly to make real-time decisions. Traditional solutions typically use relational databases to manage electric power data. However, relational databases cannot efficiently process and analyze massive electric power data when the data size increases significantly. In this paper, we show how electric power data can be managed by using HBase, a distributed database maintained by Apache. Our system consists of clients, HBase database, status monitors, data migration modules, and data fragmentation modules. We evaluate the performance of our system through a series of experiments. We also show how HBase’s parameters can be tuned to improve the efficiency of our system.https://www.sciopen.com/article/10.26599/BDMA.2018.9020026electric power datahbasedata storage |
| spellingShingle | Jiahui Jin Aibo Song Huan Gong Yingying Xue Mingyang Du Fang Dong Junzhou Luo Distributed Storage System for Electric Power Data Based on HBase Big Data Mining and Analytics electric power data hbase data storage |
| title | Distributed Storage System for Electric Power Data Based on HBase |
| title_full | Distributed Storage System for Electric Power Data Based on HBase |
| title_fullStr | Distributed Storage System for Electric Power Data Based on HBase |
| title_full_unstemmed | Distributed Storage System for Electric Power Data Based on HBase |
| title_short | Distributed Storage System for Electric Power Data Based on HBase |
| title_sort | distributed storage system for electric power data based on hbase |
| topic | electric power data hbase data storage |
| url | https://www.sciopen.com/article/10.26599/BDMA.2018.9020026 |
| work_keys_str_mv | AT jiahuijin distributedstoragesystemforelectricpowerdatabasedonhbase AT aibosong distributedstoragesystemforelectricpowerdatabasedonhbase AT huangong distributedstoragesystemforelectricpowerdatabasedonhbase AT yingyingxue distributedstoragesystemforelectricpowerdatabasedonhbase AT mingyangdu distributedstoragesystemforelectricpowerdatabasedonhbase AT fangdong distributedstoragesystemforelectricpowerdatabasedonhbase AT junzhouluo distributedstoragesystemforelectricpowerdatabasedonhbase |