Clustering and failover processing of Redis as a cache database

With the rapid development of the Internet and big data, the amount of data and access has increased exponentially. How to efficiently handle massive data requests has become an urgent problem for enterprises to solve. Caching technology is a widely used solution that can improve data access efficiency and response speed to a certain extent. As an in-memory database with excellent performance, Redis has become the cache solution of choice for many enterprises. However, due to the single point of failure problem of Redis itself, clustering and failover processing are particularly important. This article will discuss how Redis is used as a cache database from two aspects: Redis cluster and failover.

1. Overview of Redis Cluster

Redis cluster is a highly scalable, high-availability, and distributed Redis deployment method. It improves the performance and availability of Redis by storing data shards on multiple nodes, and through data synchronization and load balancing between nodes. Redis cluster can be expanded and reduced by adding and removing nodes to meet business needs.

Redis cluster distributes data through Hash slots. The number of Hash slots is fixed, and each Hash slot can store a key-value pair. By performing Hash calculations on the keys, Redis stores the data in the corresponding Hash slots.

The Redis cluster will automatically generate a hash ring. Each node on the ring is a Redis instance. They use the Hash slot as a mark for hash sharding and use the Gossip protocol for state synchronization between nodes. and fault detection. When a Redis instance goes down, the cluster will automatically perform failover and elect a new master node to take over the hash slot data of the original master node.

2. Redis failover processing

Redis failover refers to how to automatically elect a new master node to take over the data of the original master node when the master node fails in the Redis cluster. And ensure system availability and data consistency. The failover method used in Redis cluster is Automatic Failover (AOF).

The principle of Redis AOF failover is that each node votes on its own status and elects a new master node by judging the voting results. When a node detects that the primary node has been disconnected for a long time, it begins the failover election process. Each node participating in the election will vote for itself and elect a new master node through a certain algorithm (such as Raft algorithm, Paxos algorithm, etc.). After the new master node is successfully elected, the remaining slave nodes will automatically switch to the new master node and remap their respective hash slots.

However, AOF failover also has some shortcomings. For example:

1. Failover takes a certain amount of time. During this period, the Redis cluster cannot provide services to the outside world.
2. During the failover process, data loss may occur.
3. When the Redis cluster scale is large, the election process of AOF failover will become complicated and the performance will decrease.

In order to solve the problem of failover, Redis officially launched a new solution, Redis Sentinel, and integrated it into Redis version 2.4.0. Redis Sentinel provides the function of automatically detecting the status of Redis nodes and automatically performs failover. When the master node fails, Sentinel will automatically elect a new master node and switch it to the new master node. The slave nodes that need to be changed will also automatically switch to the new master node. At the same time, Redis Sentinel also provides the function of monitoring the status of the Redis cluster, which can monitor the operation of the cluster in real time and make corresponding adjustments. Because Sentinel has better stability and reliability than AOF failover, it is widely used in Redis clusters.

3. Summary

Redis, as a high-performance in-memory database, is increasingly favored by enterprises. In terms of Redis clustering and failover processing, through the use of Redis cluster and Redis Sentinel and other technical means, the single point of failure problem of Redis can be effectively solved and the performance and availability of Redis can be improved. However, when using a Redis cluster, you also need to pay attention to issues such as cluster size, number of nodes, and data synchronization. In some application scenarios, reasonable data distribution and node planning can also improve the performance of Redis.

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