Spring Boot(十三):整合Redis哨兵,集群模式實踐
- 2020 年 3 月 26 日
- 筆記
前面的兩篇文章(Redis的持久化方案, 一文掌握Redis的三種集群方案)分別介紹了Redis的持久化與集群方案 —— 包括主從複製模式、哨兵模式、Cluster模式,其中主從複製模式由於不能自動做故障轉移,當節點出現故障時需要人為干預,不滿足生產環境的高可用需求,所以在生產環境一般使用哨兵模式或Cluster模式。那麼在Spring Boot項目中,如何訪問這兩種模式的Redis集群,可能遇到哪些問題,是本文即將介紹的內容。
Spring Boot 2 整合Redis
spring boot中整合Redis非常簡單,在pom.xml中添加依賴
<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-data-redis</artifactId> </dependency>
spring boot 2的spring-boot-starter-data-redis
中,默認使用的是lettuce作為redis客戶端,它與jedis的主要區別如下:
- Jedis是同步的,不支援非同步,Jedis客戶端實例不是執行緒安全的,需要每個執行緒一個Jedis實例,所以一般通過連接池來使用Jedis
- Lettuce是基於Netty框架的事件驅動的Redis客戶端,其方法調用是非同步的,Lettuce的API也是執行緒安全的,所以多個執行緒可以操作單個Lettuce連接來完成各種操作,同時Lettuce也支援連接池
如果不使用默認的lettuce,使用jedis的話,可以排除lettuce的依賴,手動加入jedis依賴,配置如下
<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-data-redis</artifactId> <exclusions> <exclusion> <groupId>io.lettuce</groupId> <artifactId>lettuce-core</artifactId> </exclusion> </exclusions> </dependency> <dependency> <groupId>redis.clients</groupId> <artifactId>jedis</artifactId> <version>2.9.0</version> </dependency>
在配置文件application.yml中添加配置(針對單實例)
spring: redis: host: 192.168.40.201 port: 6379 password: passw0rd database: 0 # 資料庫索引,默認0 timeout: 5000 # 連接超時,單位ms jedis: # 或lettuce, 連接池配置,springboot2.0中使用jedis或者lettuce配置連接池,默認為lettuce連接池 pool: max-active: 8 # 連接池最大連接數(使用負值表示沒有限制) max-wait: -1 # 連接池分配連接最大阻塞等待時間(阻塞時間到,拋出異常。使用負值表示無限期阻塞) max-idle: 8 # 連接池中的最大空閑連接數 min-idle: 0 # 連接池中的最小空閑連接數
然後添加配置類。其中@EnableCaching註解是為了使@Cacheable、@CacheEvict、@CachePut、@Caching註解生效
@Configuration @EnableCaching public class RedisConfig { @Bean public RedisTemplate<String, Object> redisTemplate(RedisConnectionFactory factory) { RedisTemplate<String, Object> template = new RedisTemplate<>(); template.setConnectionFactory(factory); // 使用Jackson2JsonRedisSerialize 替換默認的jdkSerializeable序列化 Jackson2JsonRedisSerializer jackson2JsonRedisSerializer = new Jackson2JsonRedisSerializer(Object.class); ObjectMapper om = new ObjectMapper(); om.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY); om.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL); jackson2JsonRedisSerializer.setObjectMapper(om); StringRedisSerializer stringRedisSerializer = new StringRedisSerializer(); // key採用String的序列化方式 template.setKeySerializer(stringRedisSerializer); // hash的key也採用String的序列化方式 template.setHashKeySerializer(stringRedisSerializer); // value序列化方式採用jackson template.setValueSerializer(jackson2JsonRedisSerializer); // hash的value序列化方式採用jackson template.setHashValueSerializer(jackson2JsonRedisSerializer); template.afterPropertiesSet(); return template; } }
上述配置類注入了自定義的RedisTemplate<String, Object>, 替換RedisAutoConfiguration中自動配置的RedisTemplate<Object, Object>類(RedisAutoConfiguration另外還自動配置了StringRedisTemplate)。
此時,我們可以通過定義一個基於RedisTemplate的工具類,或通過在Service層添加@Cacheable、@CacheEvict、@CachePut、@Caching註解來使用快取。比如定義一個RedisService類,封裝常用的Redis操作方法,
@Component @Slf4j public class RedisService { @Autowired private RedisTemplate<String, Object> redisTemplate; /** * 指定快取失效時間 * * @param key 鍵 * @param time 時間(秒) * @return */ public boolean expire(String key, long time) { try { if (time > 0) { redisTemplate.expire(key, time, TimeUnit.SECONDS); } return true; } catch (Exception e) { log.error("exception when expire key {}. ", key, e); return false; } } /** * 根據key獲取過期時間 * * @param key 鍵 不能為null * @return 時間(秒) 返回0代表為永久有效 */ public long getExpire(String key) { return redisTemplate.getExpire(key, TimeUnit.SECONDS); } /** * 判斷key是否存在 * * @param key 鍵 * @return true 存在 false不存在 */ public boolean hasKey(String key) { try { return redisTemplate.hasKey(key); } catch (Exception e) { log.error("exception when check key {}. ", key, e); return false; } } ... }
出於篇幅,完整程式碼請查閱本文示例源碼: https://github.com/ronwxy/springboot-demos/tree/master/springboot-redis-sentinel
或在Service層使用註解,如
@Service @CacheConfig(cacheNames = "users") public class UserService { private static Map<String, User> userMap = new HashMap<>(); @CachePut(key = "#user.username") public User addUser(User user){ user.setUid(UUID.randomUUID().toString()); System.out.println("add user: " + user); userMap.put(user.getUsername(), user); return user; } @Caching(put = { @CachePut( key = "#user.username"), @CachePut( key = "#user.uid") }) public User addUser2(User user) { user.setUid(UUID.randomUUID().toString()); System.out.println("add user2: " + user); userMap.put(user.getUsername(), user); return user; } ... }
Spring Boot 2 整合Redis哨兵模式
Spring Boot 2 整合Redis哨兵模式除了配置稍有差異,其它與整合單實例模式類似,配置示例為
spring: redis: password: passw0rd timeout: 5000 sentinel: master: mymaster nodes: 192.168.40.201:26379,192.168.40.201:36379,192.168.40.201:46379 # 哨兵的IP:Port列表 jedis: # 或lettuce pool: max-active: 8 max-wait: -1 max-idle: 8 min-idle: 0
完整示例可查閱源碼: https://github.com/ronwxy/springboot-demos/tree/master/springboot-redis-sentinel
上述配置只指定了哨兵節點的地址與master的名稱,但Redis客戶端最終訪問操作的是master節點,那麼Redis客戶端是如何獲取master節點的地址,並在發生故障轉移時,如何自動切換master地址的呢?我們以Jedis連接池為例,通過源碼來揭開其內部實現的神秘面紗。
在 JedisSentinelPool 類的構造函數中,對連接池做了初始化,如下
public JedisSentinelPool(String masterName, Set<String> sentinels, final GenericObjectPoolConfig poolConfig, final int connectionTimeout, final int soTimeout, final String password, final int database, final String clientName) { this.poolConfig = poolConfig; this.connectionTimeout = connectionTimeout; this.soTimeout = soTimeout; this.password = password; this.database = database; this.clientName = clientName; HostAndPort master = initSentinels(sentinels, masterName); initPool(master); } private HostAndPort initSentinels(Set<String> sentinels, final String masterName) { for (String sentinel : sentinels) { final HostAndPort hap = HostAndPort.parseString(sentinel); log.fine("Connecting to Sentinel " + hap); Jedis jedis = null; try { jedis = new Jedis(hap.getHost(), hap.getPort()); List<String> masterAddr = jedis.sentinelGetMasterAddrByName(masterName); // connected to sentinel... sentinelAvailable = true; if (masterAddr == null || masterAddr.size() != 2) { log.warning("Can not get master addr, master name: " + masterName + ". Sentinel: " + hap + "."); continue; } master = toHostAndPort(masterAddr); log.fine("Found Redis master at " + master); break; } catch (JedisException e) { // resolves #1036, it should handle JedisException there's another chance // of raising JedisDataException log.warning("Cannot get master address from sentinel running @ " + hap + ". Reason: " + e + ". Trying next one."); } finally { if (jedis != null) { jedis.close(); } } } //省略了非關鍵程式碼 for (String sentinel : sentinels) { final HostAndPort hap = HostAndPort.parseString(sentinel); MasterListener masterListener = new MasterListener(masterName, hap.getHost(), hap.getPort()); // whether MasterListener threads are alive or not, process can be stopped masterListener.setDaemon(true); masterListeners.add(masterListener); masterListener.start(); } return master; }
initSentinels
方法中主要幹了兩件事:
- 遍歷哨兵節點,通過
get-master-addr-by-name
命令獲取master節點的地址資訊,找到了就退出循環。get-master-addr-by-name
命令執行結果如下所示
[root@dev-server-1 master-slave]# redis-cli -p 26379 127.0.0.1:26379> sentinel get-master-addr-by-name mymaster 1) "192.168.40.201" 2) "7001" 127.0.0.1:26379>
- 對每一個哨兵節點通過一個 MasterListener 進行監聽(Redis的發布訂閱功能),訂閱哨兵節點
+switch-master
頻道,當發生故障轉移時,客戶端能收到哨兵的通知,通過重新初始化連接池,完成主節點的切換。
MasterListener.run方法中監聽哨兵部分程式碼如下
j.subscribe(new JedisPubSub() { @Override public void onMessage(String channel, String message) { log.fine("Sentinel " + host + ":" + port + " published: " + message + "."); String[] switchMasterMsg = message.split(" "); if (switchMasterMsg.length > 3) { if (masterName.equals(switchMasterMsg[0])) { initPool(toHostAndPort(Arrays.asList(switchMasterMsg[3], switchMasterMsg[4]))); } else { log.fine("Ignoring message on +switch-master for master name " + switchMasterMsg[0] + ", our master name is " + masterName); } } else { log.severe("Invalid message received on Sentinel " + host + ":" + port + " on channel +switch-master: " + message); } } }, "+switch-master");
initPool 方法如下:如果發現新的master節點與當前的master不同,則重新初始化。
private void initPool(HostAndPort master) { if (!master.equals(currentHostMaster)) { currentHostMaster = master; if (factory == null) { factory = new JedisFactory(master.getHost(), master.getPort(), connectionTimeout, soTimeout, password, database, clientName, false, null, null, null); initPool(poolConfig, factory); } else { factory.setHostAndPort(currentHostMaster); // although we clear the pool, we still have to check the // returned object // in getResource, this call only clears idle instances, not // borrowed instances internalPool.clear(); } log.info("Created JedisPool to master at " + master); } }
通過以上兩步,Jedis客戶端在只知道哨兵地址的情況下便能獲得master節點的地址資訊,並且當發生故障轉移時能自動切換到新的master節點地址。
Spring Boot 2 整合Redis Cluster模式
Spring Boot 2 整合Redis Cluster模式除了配置稍有差異,其它與整合單實例模式也類似,配置示例為
spring: redis: password: passw0rd timeout: 5000 database: 0 cluster: nodes: 192.168.40.201:7100,192.168.40.201:7200,192.168.40.201:7300,192.168.40.201:7400,192.168.40.201:7500,192.168.40.201:7600 max-redirects: 3 # 重定向的最大次數 jedis: pool: max-active: 8 max-wait: -1 max-idle: 8 min-idle: 0
完整示例可查閱源碼: https://github.com/ronwxy/springboot-demos/tree/master/springboot-redis-cluster
在 一文掌握Redis的三種集群方案 中已經介紹了Cluster模式訪問的基本原理,可以通過任意節點跳轉到目標節點執行命令,上面配置中 max-redirects 控制在集群中跳轉的最大次數。
查看JedisClusterConnection的execute方法,
public Object execute(String command, byte[]... args) { Assert.notNull(command, "Command must not be null!"); Assert.notNull(args, "Args must not be null!"); return clusterCommandExecutor .executeCommandOnArbitraryNode((JedisClusterCommandCallback<Object>) client -> JedisClientUtils.execute(command, EMPTY_2D_BYTE_ARRAY, args, () -> client)) .getValue(); }
集群命令的執行是通過ClusterCommandExecutor.executeCommandOnArbitraryNode
來實現的,
public <T> NodeResult<T> executeCommandOnArbitraryNode(ClusterCommandCallback<?, T> cmd) { Assert.notNull(cmd, "ClusterCommandCallback must not be null!"); List<RedisClusterNode> nodes = new ArrayList<>(getClusterTopology().getActiveNodes()); return executeCommandOnSingleNode(cmd, nodes.get(new Random().nextInt(nodes.size()))); } private <S, T> NodeResult<T> executeCommandOnSingleNode(ClusterCommandCallback<S, T> cmd, RedisClusterNode node, int redirectCount) { Assert.notNull(cmd, "ClusterCommandCallback must not be null!"); Assert.notNull(node, "RedisClusterNode must not be null!"); if (redirectCount > maxRedirects) { throw new TooManyClusterRedirectionsException(String.format( "Cannot follow Cluster Redirects over more than %s legs. Please consider increasing the number of redirects to follow. Current value is: %s.", redirectCount, maxRedirects)); } RedisClusterNode nodeToUse = lookupNode(node); S client = this.resourceProvider.getResourceForSpecificNode(nodeToUse); Assert.notNull(client, "Could not acquire resource for node. Is your cluster info up to date?"); try { return new NodeResult<>(node, cmd.doInCluster(client)); } catch (RuntimeException ex) { RuntimeException translatedException = convertToDataAccessException(ex); if (translatedException instanceof ClusterRedirectException) { ClusterRedirectException cre = (ClusterRedirectException) translatedException; return executeCommandOnSingleNode(cmd, topologyProvider.getTopology().lookup(cre.getTargetHost(), cre.getTargetPort()), redirectCount + 1); } else { throw translatedException != null ? translatedException : ex; } } finally { this.resourceProvider.returnResourceForSpecificNode(nodeToUse, client); } }
上述程式碼邏輯如下
- 從集群節點列表中隨機選擇一個節點
- 從該節點獲取一個客戶端連接(如果配置了連接池,從連接池中獲取),執行命令
- 如果拋出ClusterRedirectException異常,則跳轉到返回的目標節點上執行
- 如果跳轉次數大於配置的值 max-redirects, 則拋出TooManyClusterRedirectionsException異常
可能遇到的問題
- Redis連接超時
檢查服務是否正常啟動(比如 ps -ef|grep redis
查看進程,netstat -ano|grep 6379
查看埠是否起來,以及日誌文件),如果正常啟動,則查看Redis伺服器是否開啟防火牆,關閉防火牆或配置通行埠。
- Cluster模式下,報連接到127.0.0.1被拒絕錯誤,如
Connection refused: no further information: /127.0.0.1:7600
這是因為在redis.conf中配置 bind 0.0.0.0
或 bind 127.0.0.1
導致,需要改為具體在外部可訪問的IP,如 bind 192.168.40.201
。如果之前已經起了集群,併產生了數據,則修改redis.conf文件後,還需要修改cluster-config-file文件,將127.0.0.1替換為bind 的具體IP,然後重啟。
- master掛了,slave升級成為master,重啟master,不能正常同步新的master數據
如果設置了密碼,需要在master, slave的配置文件中都配置masterauth password
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