frappe-core-cache

To prevent stale Frappe cache data, apply targeted cache invalidation using frappe.clear_document_cache() and frappe.cache.delete_value() after updates. This removes specific Redis keys, ensuring cached documents remain consistent with database changes.

Distributed locking in Frappe uses 'with frappe.lock()' to restrict critical code sections to one worker at a time. This prevents race conditions and concurrent stampedes by guaranteeing the lock is released safely upon completion.

The best way to avoid cache stampedes in Frappe is using the generator parameter with frappe.cache.get_value() or the @redis_cache decorator. This automatically populates the cache on a miss, preventing repeated expensive database queries from concurrent requests.

Yes, you can use Redis hashes for structured caching in Frappe using hset, hget, hgetall, hdel, and hexists helpers. This groups related fields under one cache name, organizing complex data efficiently within a single Redis key.

frappe.get_cached_doc can cause shared-reference mutations because it returns a shared cached object. If multiple requests modify this object directly, they mutate the cached instance, leading to inconsistent application data and unpredictable behavior.

Yes, this Frappe caching and distributed locking approach works across Frappe v14 to v16. It safely applies cache-aside reads, structured Redis hashes, and concurrency control using standard frappe.cache APIs and redis_cache patterns.