Redis内存回收策略_Redis

概述

Redis也会因为内存不足而产生错误，也可能因为回收过久而导致系统长期的停顿，因此掌握执行回收策略十分有必要。在 Redis 的配置文件中，当 Redis 的内存达到规定的最大值时，允许配置 6 种策略中的一种进行淘汰键值，并且将一些键值对进行回收。

maxmemory-policy 参数

				?

									# Set a memory usage limit to the specified amount of bytes.

									# When the memory limit is reached Redis will try to remove keys

									# according to the eviction policy selected (see maxmemory-policy).

									#

									# If Redis can't remove keys according to the policy, or if the policy is

									# set to 'noeviction', Redis will start to reply with errors to commands

									# that would use more memory, like SET, LPUSH, and so on, and will continue

									# to reply to read-only commands like GET.

									#

									# This option is usually useful when using Redis as an LRU or LFU cache, or to

									# set a hard memory limit for an instance (using the 'noeviction' policy).

									#

									# WARNING: If you have slaves attached to an instance with maxmemory on,

									# the size of the output buffers needed to feed the slaves are subtracted

									# from the used memory count, so that network problems / resyncs will

									# not trigger a loop where keys are evicted, and in turn the output

									# buffer of slaves is full with DELs of keys evicted triggering the deletion

									# of more keys, and so forth until the database is completely emptied.

									#

									# In short... if you have slaves attached it is suggested that you set a lower

									# limit for maxmemory so that there is some free RAM on the system for slave

									# output buffers (but this is not needed if the policy is 'noeviction').

									#

									# maxmemory <bytes>

									# MAXMEMORY POLICY: how Redis will select what to remove when maxmemory

									# is reached. You can select among five behaviors:

									#

									# volatile-lru -> Evict using approximated LRU among the keys with an expire set.

									# allkeys-lru -> Evict any key using approximated LRU.

									# volatile-lfu -> Evict using approximated LFU among the keys with an expire set.

									# allkeys-lfu -> Evict any key using approximated LFU.

									# volatile-random -> Remove a random key among the ones with an expire set.

									# allkeys-random -> Remove a random key, any key.

									# volatile-ttl -> Remove the key with the nearest expire time (minor TTL)

									# noeviction -> Don't evict anything, just return an error on write operations.

									#

									# LRU means Least Recently Used

									# LFU means Least Frequently Used

									#

									# Both LRU, LFU and volatile-ttl are implemented using approximated

									# randomized algorithms.

									#

									# Note: with any of the above policies, Redis will return an error on write

									#       operations, when there are no suitable keys for eviction.

									#

									#       At the date of writing these commands are: set setnx setex append

									#       incr decr rpush lpush rpushx lpushx linsert lset rpoplpush sadd

									#       sinter sinterstore sunion sunionstore sdiff sdiffstore zadd zincrby

									#       zunionstore zinterstore hset hsetnx hmset hincrby incrby decrby

									#       getset mset msetnx exec sort

									#

									# The default is:

									#

									# maxmemory-policy noeviction

主动清理策略

主动清理策略在Redis 4.0 之前一共实现了 6 种内存淘汰策略，在 4.0 之后，又增加了 2 种策略，总共8种：

【针对设置了过期时间的key做处理】

volatile-ttl：在筛选时，会针对设置了过期时间的键值对，根据过期时间的先后进行删除，越早过期的越先被删除。
volatile-random：就像它的名称一样，在设置了过期时间的键值对中，进行随机删除。
volatile-lru：会使用 LRU 算法筛选设置了过期时间的键值对删除。
volatile-lfu：会使用 LFU 算法筛选设置了过期时间的键值对删除

【针对所有的key做处理】

allkeys-random：从所有键值对中随机选择并删除数据。
allkeys-lru：使用 LRU 算法在所有数据中进行筛选删除。
allkeys-lfu：使用 LFU 算法在所有数据中进行筛选删除。

【不处理（默认）】

noeviction：不会剔除任何数据，拒绝所有写入操作并返回客户端错误信息"(error) OOM command not allowed when used memory"，此时Redis只响应读操作。

Redis 在默认情况下会采用 noeviction 策略。换句话说，如果内存己满，则不再提供写入操作，而只提供读取操作。显然这往往并不能满足我们的要求，因为对于互联网系统而言，常常会涉及数以百万甚至更多的用户，所以往往需要设置回收策略。

策略选择

LRU 算法（Least Recently Used，最近最少使用）：淘汰很久没被访问过的数据，以最近一次访问时间作为参考

LFU 算法（Least Frequently Used，最不经常使用）：淘汰最近一段时间被访问次数最少的数据，以次数作为参考

需要指出的是： LRU 算法或者 TTL 算法都是不是很精确算法，而是一个近似的算法。 Redis 不会通过对全部的键值对进行比较来确定最精确的时间值，从而确定删除哪个键值对，因为这将消耗太多的时间，导致回收垃圾执行的时间太长，造成服务停顿.

当存在热点数据时，LRU的效率很好，但偶发性的、周期性的批量操作会导致LRU命中率急剧下降，缓存污染情况比较严重。这时使用LFU可能更好点

根据自身业务类型，配置好maxmemory-policy(默认是noeviction)，推荐使用volatile-lru。

maxmemory-sample

而在Redis 的默认配置文件中，存在着参数 maxmemory-sample

				?

									# LRU, LFU and minimal TTL algorithms are not precise algorithms but approximated

									# algorithms (in order to save memory), so you can tune it for speed or

									# accuracy. For default Redis will check five keys and pick the one that was

									# used less recently, you can change the sample size using the following

									# configuration directive.

									#

									# The default of 5 produces good enough results. 10 Approximates very closely

									# true LRU but costs more CPU. 3 is faster but not very accurate.

									#

									# maxmemory-samples 5