Redis Cluster集群hash tag原理分析

工欲善其事必先利其器，在正式开始研究redis cluster hash tag之前，我们先以最小的成本搭建一套cluster集群。

docker-compose搭建redis cluster

这里使用dockerhub的bitnami/redis-cluster进行搭建，过程相比网上其他教程而言非常简单，2个shell命令搞定。

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curl -sSL https://raw.githubusercontent.com/bitnami/containers/main/bitnami/redis-cluster/docker-compose.yml > docker-compose.yml
docker-compose up -d

bitnami redis-cluster 对应的 docker-compose.yml (笔者做了细微的修改)

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version: '3'
services:
  redis-node-0:
    image: docker.io/bitnami/redis-cluster:7.0
    container_name: node-0
    volumes:
      - redis-cluster_data-0:/bitnami/redis/data
    environment:
      - 'REDIS_PASSWORD=123'
      - 'REDIS_NODES=redis-node-0 redis-node-1 redis-node-2 redis-node-3 redis-node-4 redis-node-5'

  redis-node-1:
    image: docker.io/bitnami/redis-cluster:7.0
    container_name: node-1
    volumes:
      - redis-cluster_data-1:/bitnami/redis/data
    environment:
      - 'REDIS_PASSWORD=123'
      - 'REDIS_NODES=redis-node-0 redis-node-1 redis-node-2 redis-node-3 redis-node-4 redis-node-5'

  redis-node-2:
    image: docker.io/bitnami/redis-cluster:7.0
    container_name: node-2
    volumes:
      - redis-cluster_data-2:/bitnami/redis/data
    environment:
      - 'REDIS_PASSWORD=123'
      - 'REDIS_NODES=redis-node-0 redis-node-1 redis-node-2 redis-node-3 redis-node-4 redis-node-5'

  redis-node-3:
    image: docker.io/bitnami/redis-cluster:7.0
    container_name: node-3
    volumes:
      - redis-cluster_data-3:/bitnami/redis/data
    environment:
      - 'REDIS_PASSWORD=123'
      - 'REDIS_NODES=redis-node-0 redis-node-1 redis-node-2 redis-node-3 redis-node-4 redis-node-5'

  redis-node-4:
    image: docker.io/bitnami/redis-cluster:7.0
    container_name: node-4
    volumes:
      - redis-cluster_data-4:/bitnami/redis/data
    environment:
      - 'REDIS_PASSWORD=123'
      - 'REDIS_NODES=redis-node-0 redis-node-1 redis-node-2 redis-node-3 redis-node-4 redis-node-5'

  redis-node-5:
    image: docker.io/bitnami/redis-cluster:7.0
    container_name: node-5
    volumes:
      - redis-cluster_data-5:/bitnami/redis/data
    depends_on:
      - redis-node-0
      - redis-node-1
      - redis-node-2
      - redis-node-3
      - redis-node-4
    environment:
      - 'REDIS_PASSWORD=123'
      - 'REDISCLI_AUTH=123'
      - 'REDIS_CLUSTER_REPLICAS=1'
      - 'REDIS_NODES=redis-node-0 redis-node-1 redis-node-2 redis-node-3 redis-node-4 redis-node-5'
      - 'REDIS_CLUSTER_CREATOR=yes'

volumes:
  redis-cluster_data-0:
    driver: local
  redis-cluster_data-1:
    driver: local
  redis-cluster_data-2:
    driver: local
  redis-cluster_data-3:
    driver: local
  redis-cluster_data-4:
    driver: local
  redis-cluster_data-5:
    driver: local

看到如下所示，即可认为redis cluster集群成功启动。

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➜  ivansli$ docker-compose up -d
[+] Running 6/6
⠿ Container node-2  Started                                                                                                                                        9.2s
⠿ Container node-3  Started                                                                                                                                       10.6s
⠿ Container node-1  Started                                                                                                                                        9.0s
⠿ Container node-4  Started                                                                                                                                       11.4s
⠿ Container node-0  Started                                                                                                                                        9.8s
⠿ Container node-5  Started                                                                                                                                       21.5s
➜  ivansli$ docker exec -it node-0 bash
ivansli@17affe689ed6:/$ redis-cli
127.0.0.1:6379> auth 123
OK
127.0.0.1:6379> cluster nodes
9ecc22a32815eb4f769069541279569c36b4b1d9 172.26.0.7:6379@16379 slave cc6e6b899e6f2b90f829aeff9ec36316433258a6 0 1685681651000 2 connected
f36960e21b778e1483237504fbffa2086ede7f4d 172.26.0.4:6379@16379 master - 0 1685681652000 3 connected 10923-16383
cc6e6b899e6f2b90f829aeff9ec36316433258a6 172.26.0.5:6379@16379 master - 0 1685681651976 2 connected 5461-10922
4523ca5ef7bfa6b7a22e39a418e2417204d5f34f 172.26.0.2:6379@16379 slave f36960e21b778e1483237504fbffa2086ede7f4d 0 1685681651000 3 connected
9cc6263d5ea15dcfb8795ce5e19f7844c5958781 172.26.0.3:6379@16379 slave 5bb46d5bb5df18a1977260da6183ec1cef9b8b00 0 1685681652984 1 connected
5bb46d5bb5df18a1977260da6183ec1cef9b8b00 172.26.0.6:6379@16379 myself,master - 0 1685681650000 1 connected 0-5460

可以看到redis cluster集群启动成功，其架构为：3主(master)3从(slave)。

cluster master节点 slot范围
master1 0-5460
master2 5461-10922
master3 10923-16383

集群共有16384(0~16383,2^14个)个slot(哈希槽)，每个master节点拥有连续的一段slot。

redis cluster集群key的存储方式

众所周知，对于单台服务器来说，在计算机硬件不变更的情况下其资源空间存在上限，例如：内存、硬盘、网卡带宽、CPU核心等。对于基于内存的redis服务来说，想要存储更多的、超过单机内存容量的数据，那么只能采用集群模式，最常用的就是redis cluster集群。
其数据存储原理简化为公式：CRC16(key) % 16384 = slot，即：取key进行CRC16计算之后对16384取模运算得到key所在的slot，由于redis cluster在启动时会对每一台master节点分配slot空间，那么当前slot的值在哪台master节点的slot空间范围内，key就存储在哪台节点。

通俗的讲：使用一种算法把整个数据空间化整为零分散存储在多个节点 (分布式系统设计中常用策略)。

什么是hash tag

Redis官方对Hash tags的定义如下：

There is an exception for the computation of the hash slot that is used in order to implement hash tags. Hash tags are a way to ensure that multiple keys are allocated in the same hash slot. This is used in order to implement multi-key operations in Redis Cluster.
To implement hash tags, the hash slot for a key is computed in a slightly different way in certain conditions. If the key contains a “{…}” pattern only the substring between { and } is hashed in order to obtain the hash slot. However since it is possible that there are multiple occurrences of { or } the algorithm is well specified by the following rules:

  • IF the key contains a { character.
  • AND IF there is a } character to the right of {.
  • AND IF there are one or more characters between the first occurrence of { and the first occurrence of }.
    Then instead of hashing the key, only what is between the first occurrence of { and the following first occurrence of } is hashed.

hash tags 是用于计算哈希槽时的一个例外，是一种确保多个键分配到同一个哈希槽中的方法。这是为了在Redis集群中实现多键操作而使用的。
为了实现hash tags，在某些情况下，会以稍微不同的方式计算key的哈希槽。如果key只包含”{…}”模式，则仅对{和}之间的子字符串进行散列以获取哈希槽。但由于可能存在多个{或}出现，因此该算法遵循以下规则：

  • 如果key包含字符 {
  • 并且如果 } 字符位于 { 的右侧
  • 并且在第一个 { 和第一个 } 之间存在一个或多个字符

对于符合上述规则的key，则不会对整个key进行散列处理，而只会对第一次出现 { 和随后第一次出现 } 之间的内容进行散列。否则，对整个key进行散列处理。

为什么使用hash tag

不使用hash tag批量获取不同名称的key

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127.0.0.1:6379> mget name name1 name2 name3
(error) CROSSSLOT Keys in request don't hash to the same slot

显示错误信息：CROSSSLOT 请求中的key没有哈希到同一个插槽。错误在指令执行之前的检查中触发，代码逻辑如下所示：

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// 代码文件：src/server.c

// 接收到client请求，解析并执行指令
int processCommand(client *c) {
    // ..... 省略

    // 如果是 cluster 集群，则进行一些检查操作
    if (server.cluster_enabled &&
        !mustObeyClient(c) &&
        !(!(c->cmd->flags&CMD_MOVABLE_KEYS) && c->cmd->key_specs_num == 0 &&
          c->cmd->proc != execCommand))
    {
        int error_code;

        // 检查当前指令的所有key对应的slot所在的node
        clusterNode *n = getNodeByQuery(c,c->cmd,c->argv,c->argc,
                                        &c->slot,&error_code);
        // key对应的slot所在的node不存在 或者 某些key对应的slot所在的node不是当前节点
        if (n == NULL || n != server.cluster->myself) {
            if (c->cmd->proc == execCommand) {
                discardTransaction(c);
            } else {
                flagTransaction(c);
            }

            // 不再执行指令操作，返回错误信息
            // 其中就包括错误：CROSSSLOT Keys in request don't hash to the same slot
            clusterRedirectClient(c,n,c->slot,error_code);
            c->cmd->rejected_calls++;
            return C_OK;
        }
    }

    // ..... 省略
    /* 执行指令 */
    call(c,CMD_CALL_FULL);
    // ..... 省略
}

使用hash tag批量获取不同名称的key

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172.26.0.5:6379> mget name {name} {name}1 {name}2 {name}3
1) (nil)
2) (nil)
3) (nil)
4) (nil)
5) (nil)

显示正常(请求中的key被哈希到同一个插槽)。

对上述操作的key计算得出对应slot，整理如下所示：

key 计算key的slot slot值 slot所在节点 是否使用hash tag
name cluster keyslot name 5798 master2 ❎
name1 cluster keyslot name1 12933 master3 ❎
name2 cluster keyslot name2 742 master1 ❎
name3 cluster keyslot name3 4807 master1 ❎
{name} cluster keyslot {name} 5798 master2 ✅
{name}1 cluster keyslot {name}1 5798 master2 ✅
{name}2 cluster keyslot {name}2 5798 master2 ✅
{name}3 cluster keyslot {name}3 5798 master2 ✅

redis中使用 cluster keyslot key的名称 可以得到key对应的slot值

结合上面例子以及官方对hash tag的描述，想必大家已经基本可以对为什么使用hash tag这个问题得出自己的结论。

假如在开发过程中，遇到Redis中既要存储大量数据，又要让某些相同特征的key(key包含相同字符串)存储在同一个节点的情况。那么，这个时候Redis cluster+hash tag绝对是你的首选。

redis源码中hash tag的计算方式

获取key的hash tag值，主要包含2部分逻辑：

  1. 查找 {} 包含的字符串
  2. 对找到的字符串进行使用crc16()计算

具体代码实现如在所示：

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// 代码文件：src/cluster.c

/* We have 16384 hash slots. The hash slot of a given key is obtained
 * as the least significant 14 bits of the crc16 of the key.
 *
 * However if the key contains the {...} pattern, only the part between
 * { and } is hashed. This may be useful in the future to force certain
 * keys to be in the same node (assuming no resharding is in progress). */
unsigned int keyHashSlot(char *key, int keylen) {
    int s, e; /* start-end indexes of { and } */

    // 找到第一个 { 出现的位置
    for (s = 0; s < keylen; s++)
        if (key[s] == '{') break;

    /* No '{' ? Hash the whole key. This is the base case. */
    /* 0x3FFF = 16383 = 11111111111111 (14个1)，使用 & 运算比取模运算 % 效率更高，并能实现相同效果*/
    // 没有找到 { ，则使用整个key计算hash值
    if (s == keylen) return crc16(key,keylen) & 0x3FFF;

    // 找到第一个 } 出现的位置
    /* '{' found? Check if we have the corresponding '}'. */
    for (e = s+1; e < keylen; e++)
        if (key[e] == '}') break;

    /* No '}' or nothing between {} ? Hash the whole key. */
    // 没找到 } 或者 {} 包含的字符串为空，则使用整个key计算hash值
    if (e == keylen || e == s+1) return crc16(key,keylen) & 0x3FFF;

    /* If we are here there is both a { and a } on its right. Hash
     * what is in the middle between { and }. */
    // 使用 {} 包含的字符串计算hash值
    return crc16(key+s+1,e-s-1) & 0x3FFF;
}


// 代码文件：src/crc16.c
// crc16() 的实现逻辑

/* CRC16 implementation according to CCITT standards.
 *
 * Note by @antirez: this is actually the XMODEM CRC 16 algorithm, using the
 * following parameters:
 *
 * Name                       : "XMODEM", also known as "ZMODEM", "CRC-16/ACORN"
 * Width                      : 16 bit
 * Poly                       : 1021 (That is actually x^16 + x^12 + x^5 + 1)
 * Initialization             : 0000
 * Reflect Input byte         : False
 * Reflect Output CRC         : False
 * Xor constant to output CRC : 0000
 * Output for "123456789"     : 31C3
 */

static const uint16_t crc16tab[256]= {
    0x0000,0x1021,0x2042,0x3063,0x4084,0x50a5,0x60c6,0x70e7,
    0x8108,0x9129,0xa14a,0xb16b,0xc18c,0xd1ad,0xe1ce,0xf1ef,
    0x1231,0x0210,0x3273,0x2252,0x52b5,0x4294,0x72f7,0x62d6,
    0x9339,0x8318,0xb37b,0xa35a,0xd3bd,0xc39c,0xf3ff,0xe3de,
    0x2462,0x3443,0x0420,0x1401,0x64e6,0x74c7,0x44a4,0x5485,
    0xa56a,0xb54b,0x8528,0x9509,0xe5ee,0xf5cf,0xc5ac,0xd58d,
    0x3653,0x2672,0x1611,0x0630,0x76d7,0x66f6,0x5695,0x46b4,
    0xb75b,0xa77a,0x9719,0x8738,0xf7df,0xe7fe,0xd79d,0xc7bc,
    0x48c4,0x58e5,0x6886,0x78a7,0x0840,0x1861,0x2802,0x3823,
    0xc9cc,0xd9ed,0xe98e,0xf9af,0x8948,0x9969,0xa90a,0xb92b,
    0x5af5,0x4ad4,0x7ab7,0x6a96,0x1a71,0x0a50,0x3a33,0x2a12,
    0xdbfd,0xcbdc,0xfbbf,0xeb9e,0x9b79,0x8b58,0xbb3b,0xab1a,
    0x6ca6,0x7c87,0x4ce4,0x5cc5,0x2c22,0x3c03,0x0c60,0x1c41,
    0xedae,0xfd8f,0xcdec,0xddcd,0xad2a,0xbd0b,0x8d68,0x9d49,
    0x7e97,0x6eb6,0x5ed5,0x4ef4,0x3e13,0x2e32,0x1e51,0x0e70,
    0xff9f,0xefbe,0xdfdd,0xcffc,0xbf1b,0xaf3a,0x9f59,0x8f78,
    0x9188,0x81a9,0xb1ca,0xa1eb,0xd10c,0xc12d,0xf14e,0xe16f,
    0x1080,0x00a1,0x30c2,0x20e3,0x5004,0x4025,0x7046,0x6067,
    0x83b9,0x9398,0xa3fb,0xb3da,0xc33d,0xd31c,0xe37f,0xf35e,
    0x02b1,0x1290,0x22f3,0x32d2,0x4235,0x5214,0x6277,0x7256,
    0xb5ea,0xa5cb,0x95a8,0x8589,0xf56e,0xe54f,0xd52c,0xc50d,
    0x34e2,0x24c3,0x14a0,0x0481,0x7466,0x6447,0x5424,0x4405,
    0xa7db,0xb7fa,0x8799,0x97b8,0xe75f,0xf77e,0xc71d,0xd73c,
    0x26d3,0x36f2,0x0691,0x16b0,0x6657,0x7676,0x4615,0x5634,
    0xd94c,0xc96d,0xf90e,0xe92f,0x99c8,0x89e9,0xb98a,0xa9ab,
    0x5844,0x4865,0x7806,0x6827,0x18c0,0x08e1,0x3882,0x28a3,
    0xcb7d,0xdb5c,0xeb3f,0xfb1e,0x8bf9,0x9bd8,0xabbb,0xbb9a,
    0x4a75,0x5a54,0x6a37,0x7a16,0x0af1,0x1ad0,0x2ab3,0x3a92,
    0xfd2e,0xed0f,0xdd6c,0xcd4d,0xbdaa,0xad8b,0x9de8,0x8dc9,
    0x7c26,0x6c07,0x5c64,0x4c45,0x3ca2,0x2c83,0x1ce0,0x0cc1,
    0xef1f,0xff3e,0xcf5d,0xdf7c,0xaf9b,0xbfba,0x8fd9,0x9ff8,
    0x6e17,0x7e36,0x4e55,0x5e74,0x2e93,0x3eb2,0x0ed1,0x1ef0
};

uint16_t crc16(const char *buf, int len) {
    int counter;
    uint16_t crc = 0;
    for (counter = 0; counter < len; counter++)
            crc = (crc<<8) ^ crc16tab[((crc>>8) ^ *buf++)&0x00FF];
    return crc;
}

hash tag 可能导致的问题

在Redis cluster集群中，使用hash tag可以确保多个键分配到同一个哈希槽中。但是，以下几种情况可能会导致一些负面影响：

  1. 存储时，大量key使用hash tag后落到同一slot，slot所在节点导致存储大量数据，甚至超过内存上限（数据倾斜）
  2. 查询/删除时，大量key使用hash tag后落到同一slot，slot所在节点处理大量请求，导致服务器忙碌、响应失败，甚至宕机（hot key）

hash tag是一把双刃剑，在使用时需要考虑具体业务逻辑与场景，应当尽量避免上述问题。假设无法避免时，可以对key按照业务线或者场景进行细化，进而对key进行拆分，以便更均匀的存储在不同的slot上。

延伸阅读

dockerhub bitnami/redis-cluster
Redis cluster specification
Redis hash tag 如何運作?
Redis Cluster mode and Key distribution