Implementation of massive data processing architecture for electric enterprise groups

  • Linli Wu
  • , Zhangyi Shen*
  • , Xiang Feng
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In the past three decades, with the fast development of China's economy, the business data of electric power industry also showed rapid growth and the data size is continual expanding. Thus, the management systems of electric enterprise groups encountered the performance bottlenecks of massive data processing. Hadoop is an open-source software framework developed for reliable, scalable, and efficient distributed computing and storage, and is widely used in massive data processing. Based on the study of the proposed massive business data processing of electric industry, this paper introduces a novel architecture, which is based on Hadoop ecosystem, for management systems of electric enterprise groups to crack the present performance bottlenecks. First, the business logic and processing produce of management system is analyzed. Then new architecture with Hadoop based distributed processing model is introduced in detailed. At last, experimental results with actual business scenarios and data prove the architecture can effectively resolve present performance bottlenecks of massive business data processing, and greatly improve the performance and efficiency of the management system of electric enterprise groups.

Original languageEnglish
Title of host publication2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings
EditorsKuniaki Uehara, Masahide Nakamura
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509008063
DOIs
StatePublished - 23 Aug 2016
Event15th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2016 - Okayama, Japan
Duration: 26 Jun 201629 Jun 2016

Publication series

Name2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings

Conference

Conference15th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2016
Country/TerritoryJapan
CityOkayama
Period26/06/1629/06/16

Keywords

  • Hadoop
  • Hive
  • distributed processing
  • massive data processing

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