基于桶的大数据存储系统重复数据删除技术

N. Kumar, R. Rawat, S. C. Jain
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引用次数: 13

摘要

本文提出了基于桶的重复数据删除技术。在该技术中,大数据流被赋予固定大小的分块算法来创建固定大小的块。当获得数据块后,这些数据块将被提供给MD5算法模块以生成数据块的哈希值。然后应用MapReduce模型来查找哈希值是否重复。为了检测重复的哈希值,MapReduce模型将这些哈希值与桶存储中已经存储的哈希值进行比较。如果这些哈希值已经存在于桶存储中,那么它们可以被识别为重复的。如果哈希值重复,则不要将数据存储到HDFS中,否则将数据存储到HDFS中。利用Hadoop工具对实际数据集进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bucket based data deduplication technique for big data storage system
In this paper proposed bucket based data deduplication technique is presented. In proposed technique bigdata stream is given to the fixed size chunking algorithm to create fixed size chunks. When the chunks are obtained then these chunks are given to the MD5 algorithm module to generate hash values for the chunks. After that MapReduce model is applied to find whether hash values are duplicate or not. To detect the duplicate hash values MapReduce model compared these hash values with already stored hash values in bucket storage. If these hash values are already present in the bucket storage then these can be identified as duplicate. If the hash values are duplicated then do not store the data into the Hadoop Distributed File System (HDFS) else then store the data into the HDFS. The proposed technique is analyzed using real data set using Hadoop tool.
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