Spring Cloud microservice practice for implementing distributed locks

With the popularity of microservice architecture, more and more enterprise development teams are beginning to use Spring Cloud to build their own microservice systems. In a distributed environment, implementing distributed locks is an important technical challenge. This article will introduce how to implement microservice practices of distributed locks under the Spring Cloud framework.

First of all, we need to understand what a distributed lock is. Distributed lock is a technology used to protect access to shared resources. It can ensure that multiple nodes will not modify or access the same resource at the same time in a distributed environment. In a microservice system, distributed locks can protect the reading and writing of shared resources and avoid resource competition and data inconsistency.

Next, we will introduce the solution of using Redis to implement distributed locks. Redis is a popular in-memory database that supports distributed locking and can be well integrated with the Spring Cloud framework.

First, we need to add the dependency of Redis in the Spring Boot application. Add the following dependencies in Gradle:

compile group: 'org.springframework.boot', name: 'spring-boot-starter-data-redis'

Add the following dependencies in Maven:

<dependency>
  <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>

Add the following code in our application to configure the Redis connection:

@Configuration
public class RedisConfig {

  @Bean
  JedisConnectionFactory jedisConnectionFactory() {
      RedisStandaloneConfiguration redisStandaloneConfiguration = new RedisStandaloneConfiguration();
      redisStandaloneConfiguration.setHostName("redis");
      redisStandaloneConfiguration.setPort(6379);
      return new JedisConnectionFactory(redisStandaloneConfiguration);
  }

  @Bean
  public RedisTemplate<String, String> redisTemplate(RedisConnectionFactory redisConnectionFactory) {
      RedisTemplate<String, String> redisTemplate = new RedisTemplate<>();
      redisTemplate.setConnectionFactory(redisConnectionFactory);
      redisTemplate.setDefaultSerializer(new StringRedisSerializer());
      redisTemplate.setEnableTransactionSupport(true);
      redisTemplate.afterPropertiesSet();
      return redisTemplate;
  }
}

Next, we need to implement a method to obtain distributed locks. This method needs to ensure that only one node can obtain the lock at the same time in a distributed environment. The following is a simple implementation:

@Service
public class DistributedLockService {

    @Autowired
    private RedisTemplate redisTemplate;

    public boolean acquireLock(String lockKey, String requestId, int expireTime) {

        String result = (String) redisTemplate.execute(new RedisCallback<String>() {
            @Override
            public String doInRedis(RedisConnection connection) throws DataAccessException {
                JedisCommands commands = (JedisCommands) connection.getNativeConnection();
                return commands.set(lockKey, requestId, "NX", "PX", expireTime);
            }
        });

        return result != null && result.equals("OK");
    }

    public boolean releaseLock(String lockKey, String requestId) {
        String script = "if redis.call('get', KEYS[1]) == ARGV[1] then return redis.call('del', KEYS[1]) else return 0 end";
        Boolean result = (Boolean) redisTemplate.execute(new RedisCallback<Boolean>() {
            @Override
            public Boolean doInRedis(RedisConnection connection) throws DataAccessException {
                Object nativeConnection = connection.getNativeConnection();
                Long execute = (Long) ((Jedis) nativeConnection).eval(script, Collections.singletonList(lockKey), Collections.singletonList(requestId));
                return execute.equals(1L);
            }
        });
        return result;
    }
}

In the above code, the Redis set command is executed through the execute method of redisTemplate to set the key-value pair. The NX parameter means that it is only set when the key does not exist to avoid two The situation when two threads acquire the lock at the same time. The PX parameter indicates the expiration time of the set key. The return result is OK, indicating that the lock is acquired successfully. When releasing the lock, use Redis's Lua script implementation to ensure that only the thread that owns the lock can release the lock.

Finally, we need to use distributed locks in microservices. For example, assuming we have a microservice endpoint that needs to protect resource access, we can use DistributedLockService in the Spring MVC controller to obtain a distributed lock to ensure that only one request can access the resource at the same time.

@RestController
public class ResourceController {

  private static final String LOCK_KEY = "lock";
  private static final String LOCK_REQUEST_ID = UUID.randomUUID().toString();
  private static final int EXPIRE_TIME = 5000;

  @Autowired
  private DistributedLockService distributedLockService;

  @Autowired
  private ResourceService resourceService;

  @RequestMapping("/resource")
  public ResponseEntity<String> accessResource() {

      boolean lockAcquired = distributedLockService.acquireLock(LOCK_KEY, LOCK_REQUEST_ID, EXPIRE_TIME);

      if (lockAcquired) {
          try {
              // 访问资源
              String result = resourceService.accessResource();
              return ResponseEntity.ok(result);
          } finally {
              distributedLockService.releaseLock(LOCK_KEY, LOCK_REQUEST_ID);
          }
      } else {
          return ResponseEntity.status(HttpStatus.SERVICE_UNAVAILABLE).body("Resource is busy, please try again later.");
      }
  }
}

The above code obtains the lock through DistributedLockService, accesses the resource after obtaining the lock, and releases the lock after the resource access is completed, avoiding the problem of multiple requests accessing the resource at the same time.

In the above example, we implemented the distributed lock scheme in Spring Cloud microservices. This solution can protect access to shared resources and ensure the correctness and consistency of system data. In actual use, we can adjust and optimize the implementation of distributed locks according to specific business scenarios and needs.

In short, distributed locks are a very important part of implementing a distributed system, which can ensure the correctness and consistency of system data. The combination of Spring Cloud and Redis can implement the distributed lock function well. Through the introduction of this article, I hope it can provide some help for everyone to understand and apply distributed lock technology.

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