Redis系列之多线程下使用incr/decr命令

SmileNicky

修改于 2024-04-19 10:31:13

2350

修改于 2024-04-19 10:31:13

Redis是一个单线程的服务，所以正常来说redis的命令是会排队执行的。incr/decr命令是redis提供的可以实现递增递减的命令。但是如果使用不当也会有线程安全问题。动手实践一下吧，用一个例子来模拟实现高并发场景的秒杀减库存业务。

软件环境：

JDK 1.8
SpringBoot 2.2.1
Maven 3.2+
Mysql 8.0.26
spring-boot-starter-data-redis 2.2.1
redisson-spring-boot-starter 3.1.5.6
开发工具
IntelliJ IDEA
smartGit

项目搭建

使用Spring官网的https://start.spring.io快速创建Spring Initializr项目

选择maven、jdk版本

选择需要的依赖

redisson的没搜到，那就手动配置

 <dependency>
     <groupId>org.redisson</groupId>
     <artifactId>redisson-spring-boot-starter</artifactId>
     <version>3.15.6</version>
</dependency>

application.yml加上配置：

spring:
  redis:
    host: 127.0.0.1
    port: 6379
    password:
    database: 0
    redisson:
      config: |
        singleServerConfig:
          idleConnectionTimeout: 10000
          connectTimeout: 10000
          timeout: 3000
          retryAttempts: 3
          retryInterval: 1500
          password: null
          subscriptionsPerConnection: 5
          clientName: null
          address: "redis://127.0.0.1:6379"
          subscriptionConnectionMinimumIdleSize: 1
          subscriptionConnectionPoolSize: 50
          connectionMinimumIdleSize: 32
          connectionPoolSize: 64
          database: 0
          dnsMonitoringInterval: 5000
        threads: 0
        nettyThreads: 0
        codec: !<org.redisson.codec.JsonJacksonCodec> {}
        transportMode: "NIO"

动手实践

新建一个Redis配置类：

package com.example.redis.configuration;

import cn.hutool.core.util.StrUtil;
import org.redisson.Redisson;
import org.redisson.api.RedissonClient;
import org.redisson.config.Config;
import org.redisson.spring.data.connection.RedissonConnectionFactory;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.connection.RedisConnectionFactory;
import org.springframework.data.redis.connection.jedis.JedisConnectionFactory;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.serializer.GenericJackson2JsonRedisSerializer;
import org.springframework.data.redis.serializer.StringRedisSerializer;

@Configuration
public class RedisConfiguration {

  
    @Bean
    public RedisConnectionFactory redisConnectionFactory() {
        return new RedissonConnectionFactory();
    }

    @Bean
    public RedisTemplate<String, Object> redisTemplate() {
        RedisTemplate<String, Object> template = new RedisTemplate<String, Object>();
        template.setConnectionFactory(redisConnectionFactory());
        template.setKeySerializer(new StringRedisSerializer());
        template.setValueSerializer(new GenericJackson2JsonRedisSerializer());
        return template;
    }

    @Bean
    public RedissonClient redissonClient() {
        RedissonClient redissonClient = Redisson.create();
        return redissonClient;
    }


}

写一个测试类，初始化商品库存为1000，然后开启1024个线程去抢

package com.example.redis;

import cn.hutool.core.convert.Convert;
import cn.hutool.core.date.DatePattern;
import cn.hutool.core.date.DateUtil;
import com.example.redis.configuration.RedisConfiguration;
import lombok.SneakyThrows;
import lombok.extern.slf4j.Slf4j;
import org.junit.jupiter.api.BeforeEach;
import org.junit.jupiter.api.Test;
import org.redisson.api.RLock;
import org.redisson.api.RedissonClient;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.test.annotation.DirtiesContext;
import org.springframework.test.context.ContextConfiguration;

import javax.annotation.Resource;
import java.util.Date;
import java.util.concurrent.CountDownLatch;
import java.util.stream.IntStream;

@Slf4j
@SpringBootTest
@ContextConfiguration(classes = RedisConfiguration.class)
@DirtiesContext(classMode = DirtiesContext.ClassMode.BEFORE_CLASS)
public class SpringbootRedisIncrTests {

    private static final String REDIS_ID_KEY = "testKey:id:%s";
    private static final String REDIS_LOCK_KEY = "testKey:lock";

    @Resource
    private RedisTemplate redisTemplate;

    @Resource
    private RedissonClient redissonClient;

    @BeforeEach
    public void init(){
        log.info("init...");
        // 初始化库存为1000
        String idKey = String.format(REDIS_ID_KEY,  DateUtil.format(new Date() , DatePattern.PURE_DATE_PATTERN));
        redisTemplate.opsForValue().set(idKey, 1000);
    }

    @Test
    public void testIncr() throws InterruptedException {
        // 开启1024个线程去抢
        CountDownLatch countDownLatch = new CountDownLatch(1024);
        IntStream.range(0, 1024).forEach(e->{
            new Thread(new RunnableTest(countDownLatch)).start();
        });

        countDownLatch.await();
    }

    class RunnableTest implements Runnable {

        CountDownLatch countDownLatch;

        public RunnableTest(CountDownLatch countDownLatch) {
            this.countDownLatch = countDownLatch;
        }

        @SneakyThrows
        @Override
        public void run() {
            invoke();
            countDownLatch.countDown();
        }
    }


    private void invoke() throws InterruptedException {   
        String idKey = String.format(REDIS_ID_KEY, DateUtil.format(new Date(), DatePattern.PURE_DATE_PATTERN));
        long incr = Convert.toLong(redisTemplate.opsForValue().get(idKey));
        if (incr > 0) {
            redisTemplate.opsForValue().decrement(idKey);
        }
        log.info("increment:{}", incr);
        
    }




}

跑起来，测试，这个库存数量竟然为负数了，这个业务场景肯定是不合理的

所以，我们可以用分布式锁来简单改造一下代码

private void invoke() throws InterruptedException {
    RLock rLock = redissonClient.getLock(REDIS_LOCK_KEY);
    rLock.lock();
    try {
        String idKey = String.format(REDIS_ID_KEY, DateUtil.format(new Date(), DatePattern.PURE_DATE_PATTERN));
        long incr = Convert.toLong(redisTemplate.opsForValue().get(idKey));
        if (incr > 0) {
            redisTemplate.opsForValue().decrement(idKey);
        }
        log.info("increment:{}", incr);
    } finally {
        rLock.unlock();
    }
}

跑起来，可以看到执行效率会慢一点，但是业务是正确的，不会出现库存为负数的情况