How to solve redis cache breakdown

Methods to solve Redis cache breakdown: use distributed locks to prevent concurrent cache queries, allowing lock-holding requests to obtain data and update the cache; limit current to reduce database pressure and prevent too many concurrent queries; cache empty Value to prevent direct access to the database and force retry later; preload hotspot data in advance to ensure availability; start an asynchronous task to load data asynchronously to avoid simultaneous database access.

How to solve Redis cache breakdown

Redis cache breakdown

When the key to be queried does not exist in the cache, and multiple requests concurrently query the key, cache breakdown will occur. This will cause all requests to directly access the database, causing excessive pressure on the database.

Solution

1. Mutex lock

• Use distributed lock (such as Redis'sSETNX) to establish mutually exclusive access between multiple requests.
• When a request acquires the lock, it is responsible for loading data from the database and updating the cache.
• Other requests wait for the lock to be released before querying.

2. Current limiting

• Limit the number of concurrent requests to reduce database pressure.
• You can use the token bucket algorithm or the leaky bucket algorithm to implement current limiting.

3. Cache empty value

• When the key does not exist in the cache, you can add a null value (such as NULL or "") is written to the cache.
• This will prevent other requests from accessing the database directly and force them to retry later.

4. Hotspot data preloading

• For hotspot data, they can be loaded into the cache in advance.
• You can perform this operation when the application starts or in a scheduled task.

5. Asynchronous loading

• When a request finds that a key does not exist in the cache, an asynchronous task can be initiated to load data from the database and refresh cache.
• This will avoid all requests accessing the database at the same time.

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