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Big data compression processing and verification based on Hive for smart substation

机译:基于Hive的智能变电站大数据压缩处理与验证

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The capacity and the scale of smart substation are expanding constantly, with the characteristics of information digitization and automation, leading to a quantitative trend of data. Aiming at the existing processing shortages in the big data processing, the query and analysis of smart substation, a data compression processing method is proposed for analyzing smart substation and Hive. Experimental results show that the compression ratio and query time of RCFile storage format are better than those of TextFile and SequenceFile. The query efficiency is improved for data compressed by Deflate, Gzip and Lzo compression formats. The results verify the correctness of adjacent speedup defined as the index of cluster efficiency. Results also prove that the method has a significant theoretical and practical value for big data processing of smart substation.
机译:智能变电站的容量和规模不断扩大,具有信息数字化和自动化的特点,导致数据的定量趋势。针对大数据处理,智能变电站的查询和分析中存在的处理不足,提出了一种分析智能变电站和Hive的数据压缩处理方法。实验结果表明,RCFile存储格式的压缩率和查询时间优于TextFile和SequenceFile。通过Deflate,Gzip和Lzo压缩格式压缩的数据提高了查询效率。结果验证了定义为集群效率指标的相邻加速的正确性。结果也证明该方法对智能变电站的大数据处理具有重要的理论和实用价值。

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