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Redis cluster集群Hash Tag原理分析
发布时间：2025-11-05 08:46:01 来源：技术快报 作者：IT科技
工欲善其事必先利其器，集群在正式开始研究redis cluster hash tag之前，理分我们先以最小的集群成本搭建一套cluster集群。
docker-compose搭建redis cluster
这里使用dockerhub的理分bitnami/redis-cluster进行搭建，过程相比网上其他教程而言非常简单，集群2个shell命令搞定。理分
复制curl -sSL https://raw.githubusercontent.com/bitnami/containers/main/bitnami/redis-cluster/docker-compose.yml > docker-compose.yml docker-compose up -d1.2.bitnami redis-cluster 对应的集群 docker-compose.yml (笔者做了细微的修改)
复制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:local1.2.3.4.5.6.7.8.9.10.11.12.13.14.15.16.17.18.19.20.21.22.23.24.25.26.27.28.29.30.31.32.33.34.35.36.37.38.39.40.41.42.43.44.45.46.47.48.49.50.51.52.53.54.55.56.57.58.59.60.61.62.63.64.65.66.67.68.69.70.71.72.73.74.75.76.77.78.看到如下所示，即可认为redis cluster集群成功启动。理分
复制➜ 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,集群master - 0 1685681650000 1 connected 0-54601.2.3.4.5.6.7.8.9.10.11.12.13.14.15.16.17.18.19.可以看到redis cluster集群启动成功，其架构为：3主(master)3从(slave)。理分
cluster master节点
slot范围
master1
0-5460
master2
5461-10922
master3
10923-16383
集群共有16384(0~16383,集群2^14个)个slot(哈希槽)，每个master节点拥有连续的理分一段slot。
redis cluster集群key的集群存储方式
众所周知，对于单台服务器来说，理分在计算机硬件不变更的集群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，最常用的免费信息发布网就是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b2b信息网右侧并且在第一个 { 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 复制127.0.0.1:6379> mget name name1 name2 name3 (error) CROSSSLOT Keys in request dont hash to the same slot1.2.显示错误信息：CROSSSLOT 请求中的key没有哈希到同一个插槽。
使用hash tag批量获取不同名称的key 复制172.26.0.5:6379> mget name {name} {name}1 {name}2 {name}3 1) (nil) 2) (nil) 3) (nil) 4) (nil) 5) (nil)1.2.3.4.5.6.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的服务器托管计算过程
获取key的hash tag值，主要包含2部分逻辑：
查找 {} 包含的字符串对找到的字符串进行使用crc16()计算具体代码实现如在所示：
复制// 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 */ staticconstuint16_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; }1.2.3.4.5.6.7.8.9.10.11.12.13.14.15.16.17.18.19.20.21.22.23.24.25.26.27.28.29.30.31.32.33.34.35.36.37.38.39.40.41.42.43.44.45.46.47.48.49.50.51.52.53.54.55.56.57.58.59.60.61.62.63.64.65.66.67.68.69.70.71.72.73.74.75.76.77.78.79.80.81.82.83.84.85.86.87.88.89.90.91.92.93.94.95.96.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：
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）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的粒度按照业务线或者场景进行细化，进而对key进行拆分，以便更均匀的分散到不同的slot上。
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