Analysis method and device of memory cache service node and server

Abstract

The invention provides a memory cache service node analysis method and device and a server, and the method comprises the steps: determining a to-be-analyzed target data node from at least one data node contained in a memory cache service if a node analysis request for the memory cache service is received; wherein each data node comprises one or more key value data objects; generating an RDB backup file corresponding to the target data node; analyzing the RDB backup file to obtain a node analysis result corresponding to the target data node; wherein the node analysis result at least comprises statistical information of a target key value data object in the target data node; and sending the node analysis result to a specified associated terminal so as to provide the node analysis result through a graphical user interface of the specified associated terminal. According to the method, the user can be effectively assisted in splitting the large key through the node analysis result, and the dependence of splitting the large key on user experience and the splitting difficulty are remarkably reduced.

Description

Technical field [0001] The present invention relates to the field of data storage, in particular, to an analysis method, apparatus, and server of a memory cache service node. Background technique [0002] The user may generate large KEY in the process of using Redis (Remote Dictionary Server, That is, the remote dictionary service). When the user queries large KEY corresponding data, it will lead to a large amount of query data, and may even result in a serious impact. user experience. Currently, users typically splitize large KEY to avoid querying timeout, but the process of splitting big keys is more dependent on user experience, resulting in a large decimal KEY difficulty. Inventive content [0003] In view of this, it is an object of the present invention to provide an analysis method, apparatus, and server of a memory cache service node, which can effectively secure user-splitting large KEY through node analysis results, significantly reduce the dependence of the split larg...

AI Technical Summary

Problems solved by technology

[0002] Users may generate large keys in the process of using Redis (Remote Dictionary Server, that is, remote dictionary service). When users query the data corresponding to large keys, it will lead to a large amount of query data, and may even cause query timeouts, seriously affecting user experience

At present, users usually need to manually split large keys to avoid query timeouts. However, the process of splitting large keys is more dependent on user experience, making it difficult to split large keys.

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