LEaCRS:基于线性化的高维数据可扩展数组压缩方案

Md. Rakibul Islam, K. Hasan, T. Tsuji
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引用次数: 1

摘要

大型多维数组作为基础数据结构广泛应用于科学、统计和工程等领域。随着数据仓库规模的不断扩大和数据的高度稀疏,为了获得更好的性能,需要开发一些压缩方案。针对大型多维稀疏阵列,提出了一种新的压缩方案——基于线性化可扩展阵列的压缩行存储(LEaCRS)方案。该方案的主要思想是从现有可扩展数组中找到的每个子数组进行线性化,然后使用CRS方法对子数组进行独立压缩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
LEaCRS: An Extendible Array Based Compression Scheme for High Dimensional Data Using Linearization
Large multidimensional arrays are extensively used as the basic data structure in scientific, statistical and engineering applications. Increasing size of Data warehouses and high degree of sparsity makes demand for developing some compression schemes in order to obtain better performance. In this paper, we propose a new compression scheme namely Linearized Extendible array based Compressed Row Storage (LEaCRS) scheme for large multidimensional sparse array. The main idea of this scheme is to linearize each sub array found from the existing extendible array and then compresses the sub arrays independently using the CRS method.
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