Redis cache implementation principle

Redis caching mechanism is implemented through key-value storage, memory storage, expiration policy, data structure, replication and persistence. It follows the steps of obtaining data, cache hit, cache miss, writing to cache, and updating cache to provide fast data access and high-performance caching services.

Redis cache implementation principle

Redis is a widely used open source memory database that uses memory as storage media, providing fast data reading and writing operations. Its caching mechanism is key to building high-performance applications.

Redis cache implementation principle

Redis cache implementation principle is mainly based on the following key points:

• Key-value pair Storage: Redis uses key-value pairs to store data. Keys are unique identifiers, and values ​​can be different data types such as strings, lists, sets, hashes, etc.
• Memory storage: Unlike relational databases, Redis stores all data in memory, which provides extremely fast read and write speeds and low latency.
• Expiration policy: Redis allows setting the expiration time for each cache item. When the expiration time arrives, Redis will automatically delete the item and release memory resources.
• Data structure: Redis uses efficient data structures such as jump tables and dictionaries to organize and index data, providing fast data retrieval.
• Replication and persistence: In order to ensure data security and high availability, Redis provides a replication and persistence mechanism to synchronize data to multiple servers and store it persistently on the hard disk.

Caching mechanism

Redis caching mechanism is mainly implemented through the following steps:

1. Get data: When an application needs to access data, it first sends a query request to Redis.
2. Cache hit: If there is a cache item for the data in Redis, the result will be read directly from the cache and returned. This process is very fast.
3. Cache miss: If the cache entry for the data does not exist in Redis, the application needs to obtain the data from the original data source (such as a database).
4. Write cache: Write the obtained data into the Redis cache and set the appropriate expiration time.
5. Update cache: When the data in the original data source changes, Redis will update the data in the cache through an invalidation strategy (such as LRU).

Through this mechanism, Redis achieves fast data access and high-performance caching services.

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