Data compression method, equipment and system

Abstract

The embodiment of the invention discloses a data compression method. The method comprises the following steps: acquiring target network data; setting a data segmentation parameter of the target network data according to the redundancy rate of a network application data stream to which the target network data belongs; performing data segmentation on the target network data according to the set data segmentation parameter to obtain at least one target data block; comparing the at least one target data block with data blocks in a database in sequence; and deleting the target data blocks which are the same as the data blocks in the database. The embodiment of the invention also discloses equipment and a system. The embodiment of the invention further discloses equipment and a system. Through adoption of the method, the equipment and the system, the data block partitioning granularity can be set according to the redundancy rate corresponding to the network application data stream, so that the data deduplication rate is increased under the situation of not influencing the throughput rate.

Description

technical field [0001] The present invention relates to the field of communication technology, in particular to a data compression method, device and system. Background technique [0002] Data deduplication technology is based on the principle of deduplication, and eliminates duplicate data between the same file or similar files through a certain algorithm. Data block-level deduplication refers to first dividing the file into data blocks and calculating the data fingerprints of each data block. By comparing the data fingerprints of the data blocks, it is judged whether the same data blocks are stored in the database. If the target data is detected If the data fingerprint of the block is the same as that in the database, delete the target data block. [0003] CDC (Content-Defined Chunking, content-based data chunking) algorithm is a variable-length chunking algorithm, which uses data fingerprints (such as Rabin fingerprints) to divide files into chunks of different lengths. ...

AI Technical Summary

Problems solved by technology

However, the granularity of the data blocks divided by the CDC algorithm mostly depends on the settings of the data blocks. If the set data blocks are smaller, the granularity will be finer, and the duplicate data search will be more accurate, but the overhead of data block indexing and comparison of data blocks will be relatively high. Large; if the set data block is larger, the granularity will be coarser, and the data deduplication efficiency will be lower

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