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A New Bitmap Index and a New Data Cube Compression Technology

机译:新的位图索引和新的数据多维数据集压缩技术

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This paper introduces a new kind of bitmap index. A tuple in the data cube is mapped to a sequential key (seqkey) determined by its value in each dimension. Furthermore, the quotient bit sequence is constructed according to whether the corresponding cell of a seqkey exists in the cover quotient cube or not, and the cover quotient cube is indexed by this quotient bit sequence (qcbit index). A compression method is presented for the seqkey cover quotient cube, which compress the cover quotient cube via omitting dimension attributes for all cells. To improve the storage and query of data cubes, based on these index and compression methods, algorithms are proposed to query the cover quotient cube and seqkey cover quotient cube. Experimental results on the dataset weather show that the volume of the qcbit index file is only 11 % of the value-list index file, and the volume of seqkey cover quotient cube is only 27.75% of the original cover quotient cube.
机译:本文介绍了一种新型的位图索引。数据多维数据集中的元组映射到由其在每个维度中的值所确定的顺序键(seqkey)。此外,根据seqkey的对应单元格是否在覆盖商立方体中构造商位序列,并通过该商位序列对覆盖商立方体进行索引(qcbit索引)。提出了一种用于seqkey覆盖商立方体的压缩方法,该方法通过忽略所有单元格的尺寸属性来压缩覆盖商立方体。为了改善数据立方体的存储和查询,基于这些索引和压缩方法,提出了一种查询覆盖商立方体和seqkey覆盖商立方体的算法。对数据集天气的实验结果表明,qcbit索引文件的容量仅为值列表索引文件的11%,而seqkey覆盖商立方的容量仅为原始覆盖商立方的27.75%。

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