Redis is single-threaded. Single-threaded means that the network request module uses one thread (so there is no need to consider concurrency security), that is, one Threads handle all network requests, and other modules still use multiple threads.
The reasons why redis can execute quickly:
(1) Most requests are pure memory operations (very fast)
(2) Use a single thread to avoid Eliminate unnecessary context switching and race conditions
(3) Non-blocking IO-IO multiplexing (What does IO multiplexing mean?)
There are three methods in IO multiplexing ：select,poll,epoll. It should be noted that select and poll are thread-unsafe, while epoll is thread-safe.
The internal implementation of redis uses epoll, using a simple event framework implemented by epoll itself. Read, write, close, and connect in epoll are all converted into events, and then use the multiplexing feature of epoll to never waste any time on io. These three conditions are not independent of each other, especially the first one, if the request All are time-consuming, and the throughput and performance of using a single thread can be imagined. It should be said that redis has chosen the appropriate technical solution for special scenarios.
Internal implementation of redis:
The internal implementation uses epoll, using a simple event framework implemented by epoll itself. Read, write, close, and connect in epoll are all converted into events, and then use the multiplexing feature of epoll to never waste any time on io. These three conditions are not independent of each other, especially the first one, if the request All are time-consuming, and the throughput and performance of using a single thread can be imagined. It should be said that redis has chosen the appropriate technical solution for special scenarios.
Redis on thread safety issues:
Redis actually adopts the concept of thread closure, closing tasks in one thread, which naturally avoids thread safety issues, but for those who need to rely on multiple redis For composite operations, locks are still required, and they may be distributed locks.
What are the benefits of using Redis?
(1) It is fast because the data is stored in memory, similar to HashMap. The advantage of HashMap is that the time complexity of search and operation is O(1)
(2) Rich support Data type, supports string, list, set, sorted set, hash
(3) Supports transactions, operations are all atomic. The so-called atomicity means that all changes to the data are either executed or not executed at all
(4) Rich features: can be used for caching, messaging, setting expiration time by key, it will be automatically deleted after expiration
Redis common performance problems and solutions:
(1) Master is best not to do any persistence work, such as RDB memory snapshots and AOF log files; (Master writes memory snapshots, and the save command schedules the rdbSave function, which will block the work of the main thread. When the snapshot is relatively large, the impact on performance is: If the data is very large, the service will be suspended intermittently, so it is best not to write memory snapshots on the Master; if the AOF file is too large, it will affect the recovery speed of the Master restart)
(2) If the data is important, a certain Slave should enable AOF backup Data, policy is set to synchronize once per second
(3) For the speed of master-slave replication and the stability of the connection, it is best for the Master and Slave to be in the same LAN
(4) Try to Avoid adding slave libraries to the master library that is under great pressure
(5) Do not use a graph structure for master-slave replication. It is more stable to use a one-way linked list structure, that is: Master <- Slave1 <- Slave2 <- Slave3...; This structure facilitates solving the single point of failure problem and realizing the replacement of the Master by the Slave. If the Master hangs up, you can immediately enable Slave1 as the Master, leaving everything else unchanged.
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