Within a specified time, a specified number of write operations -> Data in memory will be written to disk (dump.rdb file)
Redis will reboot to load the disk has been persistent data
Advantages: recovery speed, suitable for most scenes
Disadvantages: data integrity, consistency is not high (because before if data in memory is written to disk, the program hung up or down, will lead the new data is not persistent)
1.2 AOF
mechanism
Will each write operation by way of the log record and append to a file
Restart Redis will read the log file for recovery
Advantages: data integrity, higher consistency
Disadvantages: more logging, recovery is slow
2. Expiration mechanism
2.1 deleting data according to expiration policies
Regularly delete: low memory usage and high CPU consumption. Once every 100ms random sample (100 key), delete the expired key. If you remove the key more than 25% of the total sample (ie, 25), then the next immediately a spot check.
Inert Delete: high memory footprint and low CPU consumption. When the key is accessed, it checks whether the key expires, if you delete this key expired, and return empty.
Periodic Delete: Delete the timing and inert deleted binding version. If you delete a higher frequency, into the timing. If deletion low frequency, into inert deleted.
2.2 When the memory is too large fit new data, will enable the elimination mechanism
In order to prevent general Redis memory footprint is too large, affecting the entire server, sets the maximum memory values that maxmemory
When the memory above maxmemory, will release the memory according to maxmemory_policy
noeviction: when new data is written directly to an error
allkeys-lru: when writing new data, delete all the key data in the least recently used
allkeys-lfu: when writing new data, delete all data in the frequency of use minimal key
allkeys-random: when writing new data, delete the random key data for all
volatile-lru: when writing new data, deleting data expiration time set in the key of the least recently used
volatile-lfu: when writing new data, deleting data set expiration time of the rarest frequency key
volatile-random: when new data is written randomly delete data expiration time set in the key
volatile-ttl: When writing new data, delete the expired time earlier priority key
supplement
LRU -> least recently used
LFU -> least frequently used
other
The reason fast Redis
Pure memory operation
epoll is single-threaded, not multi-threaded and locking switch
