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HomeDatabaseRedisWhat are the redis caching mechanisms?

What are the redis caching mechanisms?

Nov 16, 2023 am 11:40 AM
rediscaching mechanism

Redis caching mechanism includes memory storage, data expiration, cache elimination strategy, data operation atomicity, persistence, publish and subscribe model, transaction processing, Lua script execution, distributed cache, monitoring and management tools, etc. Detailed introduction: 1. Memory storage, Redis uses memory to store data, which makes read and write operations very fast. It stores data in memory so that it can be quickly retrieved and operated when needed; 2. Data expiration, Redis supports Set the expiration time of the data. When the data expires, Redis will automatically delete the data and so on.

What are the redis caching mechanisms?

The operating system for this tutorial: Windows 10 system, DELL G3 computer.

Redis is a high-performance in-memory data structure storage that supports the storage of multiple types of data structures, such as strings, hash tables, lists, sets, and ordered sets. The Redis caching mechanism mainly includes the following aspects:

1. Memory storage: Redis uses memory to store data, which makes read and write operations very fast. It stores data in memory so that it can be quickly retrieved and manipulated when needed. This memory storage mechanism enables Redis to provide high-performance caching services.

2. Data expiration: Redis supports setting the expiration time of data. When the data expires, Redis will automatically delete the data. This avoids the need to manually clean up expired cached data and reduces developer workload. When setting the expiration time, you can set an appropriate expiration time based on actual needs to avoid data occupying memory for a long time.

3. Cache elimination strategy: When Redis memory is insufficient to accommodate newly written data, existing data needs to be eliminated to release memory. Redis supports a variety of cache elimination strategies, such as LRU (least recently used), LFU (least frequently used), etc. These policies can be configured based on actual needs so that the least commonly used data can be retired when needed.

4. Data operation atomicity: All data operations in Redis are atomic, which means that there will be no race conditions or concurrency issues when executing multiple operations. This enables Redis to ensure data consistency and security when processing concurrent requests.

5. Persistence: Although Redis mainly uses memory to store data, it also supports persisting data to disk. By persisting data to disk, data can be recovered after a system crash. Redis provides two persistence options: RDB (Redis DataBase) and AOF (Append Only File). RDB saves data snapshots to disk, while AOF records all write operations. The two methods can be selected according to actual needs to balance performance and data security.

6. Publish-subscribe model: Redis supports the publish-subscribe model, which enables developers to push and receive messages in real time. With the publish-subscribe model, messages can be published to one or more channels and received by clients subscribed to the channel. This model can be used to implement application scenarios such as real-time communication and message push.

7. Transaction processing: Redis supports transaction processing, which can package multiple commands into one transaction and ensure the atomicity and consistency of the transaction. A transaction can contain multiple commands, and the results are returned to the client only after all commands have been executed successfully. This enables Redis to ensure data consistency when processing key business logic.

8. Lua script execution: Redis supports executing customized commands and operations through Lua scripts. Lua script can execute a Lua script on the server side and return the results to the client. This enables developers to implement complex business logic and data processing operations.

9. Distributed cache: Redis can be used as a distributed cache system, which can disperse data to multiple Redis instances. Distributed caching allows you to scale cache capacity and performance to meet the needs of large applications.

10. Monitoring and management tools: Redis provides a wealth of monitoring and management tools, such as Redis Sentinel and Redis Cluster, which can be used to monitor the status and performance indicators of Redis instances, and implement automatic failover and load Balance and other functions. These tools can help developers better manage and maintain the Redis cache system.

To sum up, the Redis caching mechanism includes memory storage, data expiration, cache elimination strategy, data operation atomicity, persistence, publish and subscribe model, transaction processing, Lua script execution, distributed cache, monitoring and Management tools and many other aspects. These mechanisms enable Redis to provide high-performance, high-availability caching services that can be configured and expanded according to actual needs.

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