What is cache eviction, and what are some common eviction policies?
What is cache eviction, and what are some common eviction policies?
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Khushi Singh
20-Apr-2025The process of removing data from cache becomes necessary when the cache reaches its storage limit through cache eviction procedures. Cache memory has a restricted storage capacity which restricts the long-term storage of entire data sets. Eviction ensures valuable and contemporary data remains in cache by automatically deleting unneeded or less important or older entries.
The methodology which decides which data to eliminate follows the name of cache eviction policy. Each application demands a specific policy for its cache because usage patterns determine appropriate actions. These are the typical eviction policies that must be considered:
Least Recently Used (LRU): This policy removes the data that hasn't been used for the longest time. This approach works by predicting that data which remains unaccessed for a while will be unused in the near future. LRU stands as the most popular policy among data eviction systems.
Most Recently Used (MRU): In contrast to LRU, MRU removes the most recently accessed item first. The most recently accessed items do not have sufficient likelihood of being requested soon which makes this policy a suitable choice in these scenarios.
First In, First Out (FIFO): This policy evicts the oldest data, regardless of how frequently or recently it has been accessed. The system is basic to set up yet the technique fails to deliver peak performance results.
Last In, First Out (LIFO): This approach removes the most recently added data first. Effective caching implementations avoid this method because its real-world outcome shows inferior efficiency.
Least Frequently Used (LFU): This strategy removes the data that has been accessed the least number of times. The system maintains items that are frequently accessed because it assumes the items possess higher value.
Random Replacement: An item is chosen at random to be evicted. The simple approach lacks data usage consideration which results in inefficient operation.