The Design And Implementatiton Of Distributed Cache System Based On Redis

With the rapid expansion of the Internet scale,the amount of data generated by Internet application services has grown exponentially,the data storage structure has become increasingly complex,and relational databases have been under tremendous pressure in terms of reliable and scalable.Because NoSQL has many advantages in dynamic storage efficiency and horizontal expansion,configuring a distributed NoSQL cache system based on a relational database cluster can solve the above problems.This thesis designs a scalable and highly available distributed cache system based on Redis technology.The main research contents of the thesis are as follows:1)Based on the analysis of data processing requirements,a system architecture based on proxy is designed.The architecture divides the distributed cache system into an access layer,a proxy layer and a storage layer.The proxy layer can shield the difference between the upper processing interface and the lower distributed database processing process,the asynchronous interaction process between the layers and the dynamic management ensures that all layers of server clusters are scalable.2)According to the data access characteristics of Internet service,a data replacement algorithm based on the latest access time and access frequency is designed.The thesis designs and implements multiple modules such as Redis request parsing,system state management,dynamic processing,etc..And optimizes the Redis request processing process through load balancing distribution and coroutine processing.3)Design and implement related service components such as consistency coordination service,status monitoring service,and high availability service.The consistency coordination service cluster based on ZooKeeper can ensure the visibility of the system state.The state monitoring service realizes the visual management of the system running state based on InfluxDB and Granafa.The high available service provides a failover solution without manual intervention through heartbeat mechanisms,master-slave backup,and single point of failure handling.4)Deploy and test the system.The system's functions are verified,including: message processing,dynamic maintenance,and exception handling.And compared with the performance of the Redis Cluster cluster management solution,the results show that the system performance is expected.For the client,the cache service behaves as a stand-alone cache database with unlimited capacity.The system guarantees high availability through a master-multiple slave and data synchronization model to achieve redundant backup of data,and supports dynamic processing with support clusters of processing nodes and storage nodes to support high concurrency,effectively solves the problem of access and maintenance of the cache service,and satisfies the cache usage requirements under large-scale data.