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DETECTING DATA DEDUPLICATION OPPORTUNITIES USING ENTROPY-BASED DISTANCE
DETECTING DATA DEDUPLICATION OPPORTUNITIES USING ENTROPY-BASED DISTANCE
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机译:使用基于熵的距离检测数据重复数据删除机会
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摘要
Techniques for processing data may include: receiving a candidate data block; computing a distance using a distance function, wherein the distance is an entropy-based distance and denotes a measurement of similarity between the candidate data block and a target data block; and determining, using the distance, whether to perform data deduplication of the candidate data block with respect to the target data block to identify at least one sub-block of the candidate data block that is a duplicate of at least one sub-block of the target data block. If the distance is less than a threshold, it may be expected to have a matching sub-block between the candidate and target data blocks. The distance may be a difference between entropy values for the candidate and target data blocks. The first entropy value may be used to determine whether to compress or perform partial deduplication for the candidate data block.
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