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Optimization of Column-oriented Storage Compression Strategy Based on Hbase

机译:基于HBase的面向柱储存压缩策略的优化

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In order to solve the problem of high learning cost and low compression efficiency caused by large data dispersion, this paper presents a sorted-based compression strategy selection method for HBase. Firstly, a method to sort the data in each column is designed according to the characteristics of HBase to strengthen the data compaction. Secondly, according to the characteristics of the data, a column-based compression strategy is proposed to recommend the compression scheme. Experiments on TPC-DS standard dataset show its competitive performance as compared with the other state-of-the-art methods.
机译:为了解决大数据色散引起的高学习成本和低压缩效率的问题,本文提出了一种用于HBase的基于分类的压缩策略选择方法。首先,根据HBase的特性设计一个对每个列中的数据进行排序的方法,以增强数据压缩。其次,根据数据的特征,提出了一种基于列的压缩策略以推荐压缩方案。与其他最先进的方法相比,TPC-DS标准数据集的实验表明其竞争性能。

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