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What difficulties can arise when working with caching?
sobes.tech AI
Answer from AI
- Data inconsistency (Cache Invalidation): The most common problem. When the source data in the database or other source changes, the cache may contain outdated information. Invalidation strategies are required (TTL eviction, event-based, manual).
- Concurrency issues: Multiple threads or processes may attempt to update or read the same cache entry simultaneously, leading to data races or inconsistency. Synchronization or thread-safe caches are needed.
- Cache thrashing: With insufficient memory or improper eviction policies, the cache may constantly fill up and empty out with new data, providing no significant performance gain.
- Management overhead: Configuring, monitoring, and maintaining the cache, especially distributed ones, require additional effort and resources.
- Cold cache problem: On the first startup of an application or after cache clearing, requests will take longer as data is not yet loaded.
- Serialization/deserialization overhead: Caching objects requires serialization for storage and deserialization for use, which can add overhead.
- Key strategy: Choosing the right key for caching data can be challenging. An incorrect key can lead to low efficiency or collisions.
- Infrastructure cost: Using distributed caches or dedicated servers for caching can increase infrastructure expenses.