Potential bottleneck of redis

Redis Single threaded processing IO Request performance bottlenecks

1、 Any request in server Once it happens, it takes time , Will affect the whole server Performance of , In other words, the subsequent requests have to wait for the previous time-consuming request to be processed , To be dealt with by oneself . Time consuming operations include the following ：
a、 operation bigkey： Write a bigkey It takes more time to allocate memory , Again , Delete bigkey Freeing memory can also take time ;
b、 Using overly complex commands ： for example SORT/SUNION/ZUNIONSTORE, perhaps O(N) command , however N It's big , for example lrange key 0 -1 Query the full amount of data at a time ;
c、 A lot of key Concentration expired ：Redis The expiration mechanism is also executed in the main thread , A lot of key The expiration of a set can result in the processing of a request , Time consuming to delete expired key, It takes longer ;
d、 Elimination strategy ： The elimination strategy is also executed in the main thread , When memory exceeds Redis After the memory limit , Each write needs to be eliminated key, It will also take longer ;
e、AOF The brush plate is on always Mechanism ： Every time you write, you need to brush this operation to disk , Writing to disk is much slower than writing to memory , Will slow down Redis Performance of ;
f、 Master slave total synchronous generation RDB： Although fork Child processes generate data snapshots , but fork This moment will also block the whole thread , The larger the instance , The longer the blocking time ;
2、 When the amount of concurrency is very large , Single thread read-write client IO Data has performance bottlenecks , Although IO Multiplexing mechanism , But read and write client data is still synchronized IO, Only a single thread can read the client data in turn , Can't make use of CPU Multicore .

Aiming at problems 1, On the one hand, it needs business personnel to avoid , One side Redis stay 4.0 Launched lazy-free Mechanism , hold bigkey Time consuming operations to free memory are executed in asynchronous threads , Reduce the impact on the main thread .

Aiming at problems 2,Redis stay 6.0 Multithreading has been introduced , It can be used in high concurrency scenarios CPU Multi core multi thread read and write client data , Further improve server performance , Of course , Only the read and write to the client are parallel , The real operation of each command is still single threaded .