What techniques and approaches do you use to improve caching efficiency as data volume grows?

To improve caching efficiency as data volume grows, I apply the following techniques:

• Choosing the right eviction algorithm: for example, LRU (Least Recently Used) or LFU (Least Frequently Used) help keep the most demanded data in cache.
• Cache sharding: splitting the cache into multiple parts (shards) to reduce contention and increase parallelism.
• Using TTL (Time To Live): setting a lifespan for cached objects to automatically clear outdated data.
• Compression caching: applying compression for large data volumes to reduce space usage.
• Hierarchical caching: combining multiple cache levels (e.g., in-memory + distributed cache) to optimize speed and capacity.
• Avoiding over-caching: caching only data that is frequently requested and expensive to compute.

Example of using an LRU cache in Java with LinkedHashMap:

import java.util.LinkedHashMap;
import java.util.Map;

public class LRUCache<K, V> extends LinkedHashMap<K, V> {
    private final int capacity;

    public LRUCache(int capacity) {
        super(capacity, 0.75f, true);
        this.capacity = capacity;
    }

    @Override
    protected boolean removeEldestEntry(Map.Entry<K, V> eldest) {
        return size() > capacity;
    }
}

// Usage:
LRUCache<String, String> cache = new LRUCache<>(1000);
cache.put("key1", "value1");