In actual projects, the MySQL database server is sometimes located on another host and needs to access the database through the network; even if the application and the MySQL database are on the same host, accessing MySQL also involves disk IO operations (MySQL also has some Data pre-reading technology can reduce disk IO reading and writing, this part will be studied later).
#In short, reading data directly from MySQL is not as efficient as reading data directly from memory. In order to improve the efficiency of database access, people have adopted various methods, one of which is to use a memory-based cache system placed between the database and the application. (Recommended learning: Redis Video Tutorial)
When looking for data, first search it from the memory, if it is found, use it, if not found, then actually access the database. This method can improve the overall efficiency of the system in some scenarios (for example, frequently searching for the same data).
Use the redis nosql database as the cache of the Mysql database. When searching, first search the redis cache, and if found, return the result; if not found in redis, then search the Mysql database, If the flower is found, the result is returned and redis is updated; if not found, empty is returned.
In the case of writing, write directly to the mysql database, and the mysql database automatically updates the changed content to redis through triggers and UDF mechanisms.
Block diagram:
##Reading steps:
1. The client reads redis, and if there is a hit, the result is returned. If there is no hit, go to 2.2. The client reads the database, and if it is not found in the database, it returns empty; if it is found in the database, it returns the found result. Result and update Redis.Writing steps:
1. The client modifies/delete or adds data to MySQL. 2. MySQL trigger calls user-defined UDF. 3. UDF updates modified/deleted or newly added data to redis.The above is the detailed content of How to use redis to cache mysql. For more information, please follow other related articles on the PHP Chinese website!

Redis is a memory data structure storage system, mainly used as a database, cache and message broker. Its core features include single-threaded model, I/O multiplexing, persistence mechanism, replication and clustering functions. Redis is commonly used in practical applications for caching, session storage, and message queues. It can significantly improve its performance by selecting the right data structure, using pipelines and transactions, and monitoring and tuning.

The main difference between Redis and SQL databases is that Redis is an in-memory database, suitable for high performance and flexibility requirements; SQL database is a relational database, suitable for complex queries and data consistency requirements. Specifically, 1) Redis provides high-speed data access and caching services, supports multiple data types, suitable for caching and real-time data processing; 2) SQL database manages data through a table structure, supports complex queries and transaction processing, and is suitable for scenarios such as e-commerce and financial systems that require data consistency.

Redisactsasbothadatastoreandaservice.1)Asadatastore,itusesin-memorystorageforfastoperations,supportingvariousdatastructureslikekey-valuepairsandsortedsets.2)Asaservice,itprovidesfunctionalitieslikepub/submessagingandLuascriptingforcomplexoperationsan

Compared with other databases, Redis has the following unique advantages: 1) extremely fast speed, and read and write operations are usually at the microsecond level; 2) supports rich data structures and operations; 3) flexible usage scenarios such as caches, counters and publish subscriptions. When choosing Redis or other databases, it depends on the specific needs and scenarios. Redis performs well in high-performance and low-latency applications.

Redis plays a key role in data storage and management, and has become the core of modern applications through its multiple data structures and persistence mechanisms. 1) Redis supports data structures such as strings, lists, collections, ordered collections and hash tables, and is suitable for cache and complex business logic. 2) Through two persistence methods, RDB and AOF, Redis ensures reliable storage and rapid recovery of data.

Redis is a NoSQL database suitable for efficient storage and access of large-scale data. 1.Redis is an open source memory data structure storage system that supports multiple data structures. 2. It provides extremely fast read and write speeds, suitable for caching, session management, etc. 3.Redis supports persistence and ensures data security through RDB and AOF. 4. Usage examples include basic key-value pair operations and advanced collection deduplication functions. 5. Common errors include connection problems, data type mismatch and memory overflow, so you need to pay attention to debugging. 6. Performance optimization suggestions include selecting the appropriate data structure and setting up memory elimination strategies.

The applications of Redis in the real world include: 1. As a cache system, accelerate database query, 2. To store the session data of web applications, 3. To implement real-time rankings, 4. To simplify message delivery as a message queue. Redis's versatility and high performance make it shine in these scenarios.

Redis stands out because of its high speed, versatility and rich data structure. 1) Redis supports data structures such as strings, lists, collections, hashs and ordered collections. 2) It stores data through memory and supports RDB and AOF persistence. 3) Starting from Redis 6.0, multi-threaded I/O operations have been introduced, which has improved performance in high concurrency scenarios.


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