Big data compressed storage algorithm in rock burst experiment

Yu Zhang, Yan Ping Bai*, Zhao Yong Lv, Yongzhen Li, Zong Lei Mu

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

摘要

State Key Laboratory for GeoMechanics and Deep Underground Engineering (GDLab) has accumulated more than 500 TB data of rock burst experiment. But so far the amount of analyzed data is less than 5%. Data storage dilemma is restricting the study mechanism of rock burst. In this paper, we applied big data technology into analyze of rock burst, and makes deep analysis about characteristic of rock burst data. Basing on this, a big data based data storage systems (BDSS) for rock burst experiment was proposed. BDSS based on Hadoop for rock burst with online data loading and rapid retrieval of data. In Storage node machine cluster in BDSS, Big Data Compressed Storage Algorithm was proposed. The algorithm can provide average compressed ratio about 2.91%, which is as good as WinRAR. And at the same time, considered time for compress data, Big Data Compressed Storage Algorithm is much better than WinRAR. In one word, Experimental analysis shows that the algorithm have excellent performance in rock burst and solve the Data storage dilemma. Research work of this paper laid some foundation of rock burst.

源语言英语
页(从-至)111-122
页数12
期刊International Journal of Grid and Distributed Computing
10
1
DOI
出版状态已出版 - 2017
已对外发布

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引用此

Zhang, Y., Bai, Y. P., Lv, Z. Y., Li, Y., & Mu, Z. L. (2017). Big data compressed storage algorithm in rock burst experiment. International Journal of Grid and Distributed Computing, 10(1), 111-122. https://doi.org/10.14257/ijgdc.2017.10.1.11