What are the methods of handling high concurrency in Redis?

There are several ways in which Redis handles high concurrency.

1. Vertical scaling: increasing the memory and CPU resources of Redis servers to improve the performance of a single Redis instance.
2. Horizontal scaling: Utilize a Redis cluster to shard data across multiple Redis nodes, achieving load balancing and high availability.
3. Implementing master-slave replication: By setting up Redis master-slave replication, distributing read operations to the slave nodes helps alleviate the load on the master node.
4. Utilize the Sentinel mode: Monitor the nodes in the cluster through Redis Sentinel mode to achieve failover and automatic fault recovery.
5. Utilizing a persistence mechanism: By configuring Redis’s persistence mechanism, data is stored on disk to ensure the safety and reliability of the data.
6. Preheat the cache: preload hot data into the Redis cache at system startup to improve data hit rate.
7. Design data structures effectively: Choose appropriate data structures and storage methods based on business needs to optimize data access and operational efficiency.