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Economic effect of big data compressed storage technology in Rock burst experiment

机译:大数据压缩存储技术在岩爆实验中的经济效果

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State Key Laboratory for GeoMechanics and Deep Underground Engineering (GDLab) has accumulated more than 500 TB data of Rockburst experiment. But so far the amount of analysed data is less than 5% in GDLab. Data storage dilemma is restricting the study mechanism of Rockburst. In this paper, we applied big data technology into analyse of Rockburst, and makes deep analysis about characteristic of Rockburst data. Basing on this, a big data based data storage systems (BDSS) for Rockburst experiment was proposed. BDSS based on Hadoop for Rockburst 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 3.26%. Experimental analysis shows that the algorithm has excellent performance in Rockburst and solves the Data storage dilemma. Research work of this paper laid some foundation of Rockburst.
机译:地质力学和地下工程国家重点实验室(GDLab)已收集了超过500 TB的Rockburst实验数据。但是到目前为止,在GDLab中分析的数据量还不到5%。数据存储的困境限制了Rockburst的研究机制。本文将大数据技术应用于岩爆数据的分析,并对岩爆数据的特征进行了深入的分析。在此基础上,提出了用于岩爆实验的基于大数据的数据存储系统(BDSS)。基于Hadoop的BDSS for Rockburst,具有在线数据加载和数据快速检索功能。在BDSS的存储节点机器集群中,提出了大数据压缩存储算法。该算法可以提供约3.26%的平均压缩率。实验分析表明,该算法在Rockburst中具有优异的性能,解决了数据存储难题。本文的研究工作为Rockburst打下了基础。

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