Distributed cache method based on Redis

Abstract

The invention provides a distributed cache method based on Redis. The method comprises the following steps: 1, a client establishes a connection with a healthy access point; 2, the client initiates aread / write request to a certain access point, and the access point forwards the read / write request to a target data slicing node after receiving the read / write request; 3, the target data slicing nodeprocesses the read / write request and returns result information to an access machine, and then the access machine returns the result information to the client; 4, an application center, an access machine cluster and a Redis cluster aggregate monitoring indicator data into a monitoring data storage center, a monitoring module analyzes and reports the data to a monitoring center of an external component. 5, a management module provides management configuration for a configuration cluster, the access machine cluster and the Redis cluster, and provides a unified management portal and a visible page; and 6, a synchronization center obtains the data through a unified data access layer and synchronizes the data to the Redis cluster through the access machine cluster. The distributed cache method provided by the invention has the advantages of facilitating the distribution of applications.

Description

technical field [0001] The invention relates to the technical field of communication, in particular to a Redis-based distributed cache method. Background technique [0002] With the continuous development of the software system platform business, the demand for cached data storage is increasing. The data cached in the traditional system has reached more than T. These data are currently deployed in the shared memory of the minicomputer, and the data scale has reached a single The memory bottleneck of one host, and the subsequent expansion costs are high. At present, it is urgent to introduce distributed caching technology to solve the following key problems: [0003] 1. The data is deployed in the shared memory of the minicomputer, the memory capacity has reached the upper limit, and the storage capacity is small; [0004] 2. The demand for real-time expansion of business data and the bottleneck of system elastic scalability; [0005] 3. The performance bottleneck of large-...

AI Technical Summary

Problems solved by technology

[0004] 2. The demand for real-time expansion of business data and the bottleneck of system elastic scalability;

[0005] 3. Large-scale concurrent data I / O performance bottleneck, high load pressure on the database, low transaction throughput, and long system delay

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