How to solve redis cache penetration

Redis cache penetration means that keys that do not exist in the cache will be directly queried in the database every time. The following measures can be taken to solve this problem: 1. Use Bloom filters to quickly determine whether the key exists; 2. Use null values. Cache values that do not exist; 3. Apply cache penetration protection algorithms (funnel algorithm, sliding window counter) to limit query frequency; 4. Optimize database query statements; 5. Strengthen data verification to avoid illegal key query cache.

How to solve Redis cache penetration

What is cache penetration

Cache penetration means that when querying a key that does not exist in the cache, the database will be directly queried every time, causing excessive pressure on the database.

Solution

1. Bloom filter

The Bloom filter is a bit array used to Quickly determine whether an element exists in the collection. In Redis, cached keys can be mapped into Bloom filters. When querying for a key, Bloom filters are first checked. If it does not exist, it will be returned directly to avoid querying the database; if it exists, it will continue to query Redis.

2. Null value caching

Null value caching refers to caching values that do not exist. When querying for a key, if the key does not exist, a null value is cached and expires after a period of time. In this way, the next time you query this key, the null value will be returned directly from the cache to avoid querying the database.

3. Cache penetration protection algorithm

Funnel algorithm:Record the keys with higher query frequency in the funnel. When querying for a key, the funnel is checked first. If it exists, limit the query frequency to avoid excessive queries to the database.

Sliding window counter:Record the number of times a key is queried within a period of time. If the number exceeds the threshold, the query will be rejected to avoid excessive pressure on the database.

4. Database query optimization

Optimize database query statements as much as possible to reduce database query time. For example, use indexes, avoid full table scans, etc.

5. Strengthen data verification

Before the data is entered into the database, verify the data to prevent illegal or non-existent keys from being queried into the cache.

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