Redis Eviction: Time to Clear the Cache.(redisevict)
Redis is a popular and in-memory data store. It’s used for caching and storing data. However, not all data remains in the redis cache forever. In some cases, when memory becomes scarce, unwanted data is evicted from the cache — and this eviction process is called Redis Eviction.
Redis provides customizable eviction policies. It allows you to define the strategy which will be used when an eviction occurs. If you’re not careful, you can end up with data that is both out of date and difficult to retrieve.
One popular eviction policy is the “least recently used” (LRU) policy. With this policy, Redis will always try to evict the data that hasn’t been accessed for the longest time. For example, if your redis cache was full, and you hadn’t accessed some data for weeks, then the LRU policy may choose to evict the oldest data first.
The eviction process can be handled manually, or you can set it up to run automatically. If you decide to set up an automated process, you can use a Redis client library. The client library will allow you to schedule predetermined tasks and configure the type of eviction policy used.
It is important to keep an eye on the memory usage of your redis cache. If it suddenly increases, you may need to set up a purge policy or manually delete unwanted data. If left unchecked, the memory usage could eventually exceed the limits set by your system and cause the eviction process to kick in.
Redis Eviction can also be used to remove outdated data. As data changes, it is not always wise to keep the outdated version. This data can be safely evicted from the redis cache, allowing newer and more appropriate data to take its place.
Finally, Redis can be used to expire data after a set period of time. This data will be automatically evicted from the redis cache and replaced with fresh data. This type of expiration can be configured at the client level, and the length of time is typically determined by the application.
Redis Eviction is an essential part of managing your redis cache. By configuring an appropriate policy, as well as scheduling regular purges and expirations, you can ensure that your data remains up to date and relevant.
const policy = new Redis.EvictionPolicy.LRU(maxMemory)
client.setEvictionPolicy(policy)
server.expire(key, seconds)