Implementing an LRU Cache with Redis

Caching Policy

When using Redis to cache database query results, we need an efficient memory management strategy. Simply storing results indefinitely can lead to excessive RAM usage over time.

LRU (Least Recently Used) Solution

LRU caching policy provides an optimal solution by removing the least recently accessed items when memory limits are reached.

Redis LRU Implementation

Redis includes built-in LRU functionality. To enable it, configure Redis with two key parameters:

redis-server --maxmemory 10mb --maxmemory-policy allkeys-lru

Configuration Parameters

• maxmemory: Sets memory limit (e.g., 10MB)
• maxmemory-policy: Defines eviction policy (allkeys-lru)

Available Memory Policies

• allkeys-lru: Evict any key using LRU
• volatile-lru: Evict keys with expiry using LRU
• allkeys-random: Evict random keys
• volatile-random: Evict random keys with expiry
• volatile-ttl: Evict keys with shortest TTL first

Benefits

• Automatic memory management
• Improved cache efficiency
• Better resource utilization
• No manual cache cleanup required