Method and device for storing file in self-adaption mode

Abstract

The invention discloses a method and device for storing a file in a self-adaption mode. The method comprises the steps that the cold and hot degree attribute of a file is determined, and the cold and hot degree attribute of the file represents the access frequency of the file; according to the cold and hot degree attribute of the file, the file is subjected to coding storage or transcoding storage. Therefore, according to the method and device for storing the file in the self-adaption mode, the file can be stored through the corresponding coding and decoding technology according to the cold and hot degree attribute of the file, the needs of the cold and hot degree attribute of the file for storage expenses and the restoration cost can be fully considered, and the adopted coding and decoding technology is high in reliability and high in coding and decoding speed. Therefore, the multi-dimensional comprehensive performance of the storage expenses, the restoration cost, reliability and the coding speed can be improved.

Description

technical field [0001] The present invention relates to the field of storage, and more particularly, to a method and device for adaptively storing files. Background technique [0002] In a distributed file system, in order to reduce storage overhead, Erasure Code (EC) technology can be used to encode and decode data instead of multi-copy replication. Each EC technology has its own advantages, and some reliability High, some have low recovery costs, and some have low storage overhead. For example, the dot product codec (Product Code, PC) algorithm uses both horizontal and vertical coding methods, and only performs XOR operations to obtain high codec speed and low recovery cost, but the storage overhead is high, and local reconstruction codec (Locally Reconstruction Code, LRC) algorithm has low storage overhead, but the recovery cost is high when multiple nodes fail. Therefore, the comprehensive performance of the existing EC technology still needs to be improved. Contents...

AI Technical Summary

Problems solved by technology

For example, the dot product codec (Product Code, PC) algorithm uses both horizontal and vertical coding methods, and only performs XOR operations to obtain high codec speed and low recovery cost, but the storage overhead is high, and local reconstruction codec (Locally Reconstruction Code, LRC) algorithm has low storage overhead, but the recovery cost is high when multiple nodes fail

Therefore, the comprehensive performance of the existing EC technology still needs to be improved.

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