How to solve Redis cache penetration and cache avalanche problems

How to solve Redis cache penetration and cache avalanche problems

Cache avalanche: Since the cache layer carries a large number of requests, the storage layer is effectively protected, but if the cache layer cannot provide services for some reasons, such as The Redis node hangs up and all hotspot keys are invalid. In these cases, all requests will be directly made to the database, which may cause database downtime.

To prevent and solve cache avalanche problems, you can start from the following three aspects:

1. Use Redis high-availability architecture: Use Redis cluster to ensure that the Redis service will not hang up

2. Inconsistent cache time: Add a random value to the cache expiration time to avoid collective failure

3. Current limiting and downgrading strategy: There are certain filings, such as the personalized recommendation service is unavailable. Change to hot data recommendation service

Cache penetration: Cache penetration refers to querying data that does not exist at all. Such data is definitely not in the cache, which will cause all requests to fall on the database, which may occur. Database downtime.

To prevent and solve cache penetration problems, you can consider the following two methods:

1. Cache empty objects: Cache empty values, but there is a problem, a large number of invalid empty objects The value will take up space and is very wasteful.

2. Bloom filter interception: Map all possible query keys to the Bloom filter first. When querying, first determine whether the key exists in the Bloom filter, and then continue to execute downwards if it exists. If it does not exist, it will be returned directly. Bloom filters have certain misjudgments, so your business needs to allow a certain degree of fault tolerance.

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