Caching is an essential part of modern applications. By using caching, applications can significantly improve response time and throughput, and reduce the load on backend servers. However, the use of cache also brings some problems, such as cache penetration, cache breakdown, and cache avalanche. In this blog, we'll dive into these issues and their solutions.
cache penetration
Cache penetration means that when an application requests data that does not exist in the cache, the request passes through the cache layer to the backend database. Since the data is not in the cache, each request needs to query the backend database, which will increase the pressure on the backend server and may even cause the service to be unavailable.
The reason for cache penetration may be malicious attacks or business requirements. For example, when the requested parameters are illegal or the queried data does not exist, cache penetration will be triggered.
solution:
- Check the parameters: You can check the parameters to judge the legitimacy of the parameters. For example, use a Bloom filter to filter invalid requests, add non-existing keys to the Bloom filter, and return directly when the request key is not in the Bloom filter.
- Cache empty objects: You can set the value corresponding to a non-existent key to an empty object, so that in subsequent requests, when an empty object is queried, there is no need to query the backend database.
- Use the fast failure mechanism: You can set a short time interval. When the corresponding data does not exist in the cache, the query to the back-end database is suspended to avoid multiple requests from penetrating to the back-end database.
cache breakdown
Cache breakdown means that when a cache key expires or is deleted, the next request will penetrate the cache layer and directly request the backend database. If a large number of requests penetrate to the back-end database at the same time, it may cause the back-end database to be unavailable.
The reason for cache breakdown is that a large number of requests penetrate to the backend database at the same time due to the expiration of hot data.
solution:
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Set the hotspot data to never expire: You can set the expiration time of the hotspot data to never expire, which can ensure that the hotspot data will not be deleted due to expiration.
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Use a locking mechanism: Distributed locks or mutexes can be used to solve the problem of cache breakdown. When multiple requests request an expired hotspot data at the same time, only one request can acquire the lock, query the backend database and update the cache, and other requests wait until the lock is released. This method requires attention to the implementation of locks to avoid deadlocks and waste of resources.
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Use cache warming: You can load hotspot data into the cache when the application starts to avoid cache penetration during the request process.
cache avalanche
Cache avalanche refers to when a large amount of cached data in the cache layer expires or is deleted at the same time, causing a large number of requests to directly access the back-end database, resulting in a sharp increase in the load on the back-end database, and may even cause the service to be unavailable.
The reason for the cache avalanche is that a large amount of data in the cache expires or is deleted at the same time, causing a large number of requests to directly access the back-end database, which cannot be responded in a timely manner, resulting in increased pressure on the back-end database.
solution:
- Set different expiration times: You can set the expiration time in the cache to be random, which can avoid the situation that a large number of caches are invalidated at the same time.
- Use multi-level cache architecture: The cache layer can be designed as a multi-level cache architecture, for example, using multiple types of caches such as local cache, distributed cache, and CDN cache. This ensures that even if one caching tier fails, the other caching tiers will still be able to provide service.
- Set different caches for different requests: You can set different caches according to different requests to avoid hot data from being concentrated in a certain cache, thereby reducing the risk of cache avalanche.
Summarize:
Cache penetration, cache breakdown, and cache avalanche are common cache issues that can cause performance issues or unavailability of the application. To address these problems, we can use different solutions, such as: using Bloom filters, caching empty objects, locking mechanisms, cache warming, setting different expiration times, and using multi-level cache architectures. Through reasonable cache design and optimization, these problems can be effectively solved and the performance and availability of applications can be improved.
From:
How to avoid the impact of cache penetration on application performance? - Nuggets