Redis内存淘汰和过期删除策略原理分析

Redis是一个内存键值对数据库，所以对于内存的管理尤为重要。Redis内部对于内存的管理主要包含两个方向，过期删除策略和数据淘汰策略。思考：

• 什么是数据淘汰？
• 数据过期和数据淘汰都是删除数据，两者有什么区别？
• 实际使用场景是多样化的，如何选择合适的淘汰策略？

淘汰策略原理

所谓数据淘汰是指在Redis内存使用达到一定阈值的时候，执行某种策略释放内存空间，以便于接收新的数据。内存可使用空间由配置参数maxmemory决定(单位mb/GB)。故又叫"最大内存删除策略"，也叫"缓存删除策略"。

maxmemory配置

# 客户端命令方式配置和查看内存大小
127.0.0.1:6379> config get maxmemory
"maxmemory"
"0"
127.0.0.1:6379> config set maxmemory 100mb
OK
127.0.0.1:6379> config get maxmemory
"maxmemory"
"104857600"

#通过redis.conf 配置文件配置
127.0.0.1:6379> info
# Server
#...
# 配置文件路径
config_file:/opt/homebrew/etc/redis.conf
#...


# 修改内存大小
> vim /opt/homebrew/etc/redis.conf
############################## MEMORY MANAGEMENT ################################

# 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).
#
#...
maxmemory 100mb
#...

注：若`maxmemory=0`则表示不做内存限制，但是对于windows系统来说，32位系统默认可使用空间是3G，因为整个系统内存是4G，需要留1G给系统运行。且淘汰策略会自动设置为noeviction，即不开启淘汰策略，当使用空间达到3G的时候，新的内存请求会报错。

淘汰策略分类

• 淘汰策略配置maxmemory-policy，表示当内存达到maxmemory时，将执行配置的淘汰策略，由redis.c/freeMemoryIfNeeded 函数实现数据淘汰逻辑。maxmemory-policy配置

# 命令行配置方式
127.0.0.1:6379> CONFIG GET maxmemory-policy
"maxmemory-policy"
"noeviction"
127.0.0.1:6379> CONFIG SET maxmemory-policy volatile-lru
OK
127.0.0.1:6379> CONFIG GET maxmemory-policy
"maxmemory-policy"
"volatile-lru"

#redis.conf文件配置方式
# MAXMEMORY POLICY: how Redis will select what to remove when maxmemory
# is reached. You can select one from the following behaviors:
#
# volatile-lru -> Evict using approximated LRU, only keys with an expire set.
# allkeys-lru -> Evict any key using approximated LRU.
# volatile-lfu -> Evict using approximated LFU, only keys with an expire set.
# allkeys-lfu -> Evict any key using approximated LFU.
# volatile-random -> Remove a random key having 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.
# The default is:
# ...
maxmemory-policy noeviction

    freeMemoryIfNeeded逻辑处理

int freeMemoryIfNeeded(void) {
  size_t mem_used, mem_tofree, mem_freed;
  int slaves = listLength(server.slaves);

  /* Remove the size of slaves output buffers and AOF buffer from the count of used memory.*/
  // 计算出 Redis 目前占用的内存总数，但有两个方面的内存不会计算在内：
  // 1）从服务器的输出缓冲区的内存
  // 2）AOF 缓冲区的内存
  mem_used = zmalloc_used_memory();
  if (slaves) {
    listIter li;
    listNode *ln;

    listRewind(server.slaves,&li);
    while((ln = listNext(&li))) {
      redisClient *slave = listNodeValue(ln);
      unsigned long obuf_bytes = getClientOutputBufferMemoryUsage(slave);
      if (obuf_bytes > mem_used)
        mem_used = 0;
      else
        mem_used -= obuf_bytes;
    }
  }
  if (server.aof_state != REDIS_AOF_OFF) {
    mem_used -= sdslen(server.aof_buf);
    mem_used -= aofRewriteBufferSize();
  }

  /* Check if we are over the memory limit. */
  // 如果目前使用的内存大小比设置的 maxmemory 要小，那么无须执行进一步操作
  if (mem_used eviction_pool;

        while(bestkey == NULL) {
          evictionPoolPopulate(dict, db->dict, db->eviction_pool);
          /* Go backward from best to worst element to evict. */
          for (k = REDIS_EVICTION_POOL_SIZE-1; k >= 0; k--) {
            if (pool[k].key == NULL) continue;
            de = dictFind(dict,pool[k].key);

            /* Remove the entry from the pool. */
            sdsfree(pool[k].key);
            /* Shift all elements on its right to left. */
            memmove(pool+k,pool+k+1,
              sizeof(pool[0])*(REDIS_EVICTION_POOL_SIZE-k-1));
            /* Clear the element on the right which is empty since we shifted one position to the left.  */
            pool[REDIS_EVICTION_POOL_SIZE-1].key = NULL;
            pool[REDIS_EVICTION_POOL_SIZE-1].idle = 0;

            /* If the key exists, is our pick. Otherwise it is a ghost and we need to try the next element. */
            if (de) {
              bestkey = dictGetKey(de);
              break;
            } else {
              /* Ghost... */
              continue;
            }
          }
        }
      }

      /* volatile-ttl */
      // 策略为 volatile-ttl ，从一集 sample 键中选出过期时间距离当前时间最接近的键
      else if (server.maxmemory_policy == REDIS_MAXMEMORY_VOLATILE_TTL) {
        for (k = 0; k < server.maxmemory_samples; k++) {
          sds thiskey;
          long thisval;

          de = dictGetRandomKey(dict);
          thiskey = dictGetKey(de);
          thisval = (long) dictGetVal(de);

          /* Expire sooner (minor expire unix timestamp) is better candidate for deletion */
          if (bestkey == NULL || thisval id);
        decrRefCount(keyobj);
        keys_freed++;

        /* When the memory to free starts to be big enough, we may */
        /* start spending so much time here that is impossible to */
        /* deliver data to the slaves fast enough, so we force the */
        /* transmission here inside the loop. */
        if (slaves) flushSlavesOutputBuffers();
      }
    }

    if (!keys_freed) return REDIS_ERR; /* nothing to free... */
  }

  return REDIS_OK;
}

8种淘汰策略

• Redis定义的策略常量(version < 4.0)

/* Redis maxmemory strategies */
 #define REDIS_MAXMEMORY_VOLATILE_LRU 0
 #define REDIS_MAXMEMORY_VOLATILE_TTL 1
 #define REDIS_MAXMEMORY_VOLATILE_RANDOM 2
 #define REDIS_MAXMEMORY_ALLKEYS_LRU 3
 #define REDIS_MAXMEMORY_ALLKEYS_RANDOM 4
 #define REDIS_MAXMEMORY_NO_EVICTION 5
 #define REDIS_DEFAULT_MAXMEMORY_POLICY REDIS_MAXMEMORY_NO_EVICTION

3.0版本提供6种策略：

4.0以上版本增加两种LFU策略：

volatile-lfu( REDIS_MAXMEMORY_VOLATILE_LFU): Evict using approximated LFU, only keys with an expire set -> 对配置了过期时间的key，淘汰最近使用频率最少的数据。

allkeys-lfu(REDIS_MAXMEMORY_ALLKEYS_LFU): Evict any key using approximated LFU -> 对所有key，淘汰最近使用频率最少的数据。

volatile-lru( REDIS_MAXMEMORY_VOLATILE_LRU): Evict using approximated LRU, only keys with an expire set -> 内存不足时，对所有配置了过期时间的key，淘汰最近最少使用的数据。

allkeys-lru(REDIS_MAXMEMORY_ALLKEYS_LRU): Evict any key using approximated LRU -> 内存不足时，对所有key，淘汰最近最少使用的数据。

volatile-random( REDIS_MAXMEMORY_VOLATILE_RANDOM): Remove a random key having an expire set -> 内存不足时，对所有配置了过期时间的key，淘汰随机数据。

allkeys-random(REDIS_MAXMEMORY_ALLKEYS_RANDOM): Remove a random key, any key -> 内存不足时，对所有key，淘汰随机数据。

volatile-ttl( REDIS_MAXMEMORY_VOLATILE_TTL): Remove the key with the nearest expire time (minor TTL) -> 内存不足时，对所有配置了过期时间的key，淘汰最近将要过期的数据。

noeviction( REDIS_MAXMEMORY_NO_EVICTION): Don't evict anything, just return an error on write operations -> 不开启淘汰策略，在不配置淘汰策略的情况下，maxmemory-policy默认等于该值。内存不足时，会抛出异常，写操作不可用。不同系统存在差异性-具体见⇑

淘汰策略的选择

• 存在冷热数据区别，即意味着访问频率存在较大差异，4.0及以上版本建议选择allkeys-lfu策略，但要设置lfu-decay-time 计数衰减值，一般默认1，这样可避免缓存污染现象；3.0及以下版本建议选择allkeys-lru策略。LFU访问计数衰减配置

# The counter decay time is the time, in minutes, that must elapse in order

# for the key counter to be divided by two (or decremented if it has a value

# less