The official FAQ states that because Redis is a memory-based operation, the CPU is not the bottleneck of Redis. The bottleneck of Redis is most likely the size of the machine memory or the network bandwidth. Since single-threading is easy to implement and the CPU will not become a bottleneck, it is logical to adopt the single-threaded solution (Recommended learning: Redis video tutorial)
See By this point, you may cry! I thought there would be some major technical points that make Redis so fast using a single thread, but I didn't expect an official answer that seemed to fool us! However, we can already clearly explain why Redis is so fast, and precisely because it is already fast in single-threaded mode, there is no need to use multi-threading!
However, our single-threaded approach cannot take advantage of multi-core CPU performance, but we can improve it by opening multiple Redis instances on a single machine!
Warning 1:The single thread we have been emphasizing here only has one thread to process our network requests. When a formal Redis Server is running, there must be more than one thread. It’s a thread, everyone needs to pay clear attention here! For example, when Redis is persisted, it will be executed as a sub-process or sub-thread (the specific sub-thread or sub-process needs to be studied in depth by the reader); for example, I checked the Redis process on the test server weapon, and then found the thread under the process:
The "-T" parameter of the ps command indicates Show threads, possibly with SPID column. The "SID" column indicates the thread ID, and the "CMD" column Thread name is shown.
Warning 2: The last paragraph in the FAQ in the above picture states that multi-threading will be supported starting from Redis 4.0 version, but only multi-threading is performed on certain operations. operation! Therefore, whether this article will still be single-threaded in future versions requires readers to verify!
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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.

RedisisclassifiedasaNoSQLdatabasebecauseitusesakey-valuedatamodelinsteadofthetraditionalrelationaldatabasemodel.Itoffersspeedandflexibility,makingitidealforreal-timeapplicationsandcaching,butitmaynotbesuitableforscenariosrequiringstrictdataintegrityo

Redis improves application performance and scalability by caching data, implementing distributed locking and data persistence. 1) Cache data: Use Redis to cache frequently accessed data to improve data access speed. 2) Distributed lock: Use Redis to implement distributed locks to ensure the security of operation in a distributed environment. 3) Data persistence: Ensure data security through RDB and AOF mechanisms to prevent data loss.

Redis's data model and structure include five main types: 1. String: used to store text or binary data, and supports atomic operations. 2. List: Ordered elements collection, suitable for queues and stacks. 3. Set: Unordered unique elements set, supporting set operation. 4. Ordered Set (SortedSet): A unique set of elements with scores, suitable for rankings. 5. Hash table (Hash): a collection of key-value pairs, suitable for storing objects.

Redis's database methods include in-memory databases and key-value storage. 1) Redis stores data in memory, and reads and writes fast. 2) It uses key-value pairs to store data, supports complex data structures such as lists, collections, hash tables and ordered collections, suitable for caches and NoSQL databases.

Redis is a powerful database solution because it provides fast performance, rich data structures, high availability and scalability, persistence capabilities, and a wide range of ecosystem support. 1) Extremely fast performance: Redis's data is stored in memory and has extremely fast read and write speeds, suitable for high concurrency and low latency applications. 2) Rich data structure: supports multiple data types, such as lists, collections, etc., which are suitable for a variety of scenarios. 3) High availability and scalability: supports master-slave replication and cluster mode to achieve high availability and horizontal scalability. 4) Persistence and data security: Data persistence is achieved through RDB and AOF to ensure data integrity and reliability. 5) Wide ecosystem and community support: with a huge ecosystem and active community,

Key features of Redis include speed, flexibility and rich data structure support. 1) Speed: Redis is an in-memory database, and read and write operations are almost instantaneous, suitable for cache and session management. 2) Flexibility: Supports multiple data structures, such as strings, lists, collections, etc., which are suitable for complex data processing. 3) Data structure support: provides strings, lists, collections, hash tables, etc., which are suitable for different business needs.

The core function of Redis is a high-performance in-memory data storage and processing system. 1) High-speed data access: Redis stores data in memory and provides microsecond-level read and write speed. 2) Rich data structure: supports strings, lists, collections, etc., and adapts to a variety of application scenarios. 3) Persistence: Persist data to disk through RDB and AOF. 4) Publish subscription: Can be used in message queues or real-time communication systems.


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