Caching common problems and solutions: Cache penetration: Use bloom filters or default values to avoid invalid queries when they do not exist in the cache and database. Cache breakdown: When accessing expired keys with high concurrency, use mutex locks or never-expired hotspot data to solve the problem. Cache avalanche: When a large number of keys expire at the same time, set different expiration times, diversion and current limiting, cache preheating, and disaster recovery solutions to deal with it.
Redis cache penetration, breakdown, avalanche solution
What is cache penetration, Breakdown, avalanche?
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Cache penetration: Occurs when the requested data does not exist in the cache and database.
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Cache breakdown: Occurs when high concurrent requests simultaneously access an expired key in the cache.
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Cache avalanche: Occurs when a large number of cache keys expire at the same time, causing the cache failure rate to increase dramatically.
Solution:
Cache Penetration
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Use Bloom Filter : Determine whether the data exists in the database to avoid unnecessary database queries.
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Set default values: Set default values for non-existent data to avoid querying the database directly.
Cache breakdown
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Mutex lock: When the cache key expires, use the mutex lock to control concurrency. Only one request is allowed to query the database and update the cache.
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Hotspot data never expires: For hotspot data, set a cache time that never expires.
Cache Avalanche
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Set different expiration times: Set different expiration times for different keys to avoid a large number of keys at the same time Expired.
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Diversion and current limiting: Through current limiting measures, the number of concurrent requests is controlled to avoid a large number of requests accessing the cache at the same time.
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Cache preheating: Preload popular data into the cache when the server starts or periodically.
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Disaster recovery plan: Establish a failover mechanism to automatically switch to an alternate cache or database when the cache is unavailable.
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