并发减库存 redis vs mysql

业务

商品有库存， 如10000 每买一个商品 库存就减一

减库存可以通过mysql来实现 如

update product_stock set stock = stock - 1 where product_id = 1 and stock > 0; 

也可以使用redis来实现 如

decr 1_stock
(integer) 99

面对这种场景都说要使用redis 因为redis并发性能更好 想实际验证一下是否这样
思路

设置较大的并发数去更新库存 执行10次 比较redis和mysql花费的时间

代码

@SpringBootApplication
public class CocurrentUpdateStockApplication implements CommandLineRunner {
    @Autowired
    private JdbcTemplate jdbcTemplate;
    
    @Bean
    JedisConnectionFactory jedisConnectionFactory() {
        return new JedisConnectionFactory();
    }

    @Bean
    RedisTemplate<String, Long> redisTemplate() {
        final RedisTemplate<String, Long> template = new RedisTemplate<String, Long>();
        template.setConnectionFactory(jedisConnectionFactory());
        template.setKeySerializer(new StringRedisSerializer());
        template.setHashValueSerializer(new GenericToStringSerializer<Long>(Long.class));
        template.setValueSerializer(new GenericToStringSerializer<Long>(Long.class));
        return template;
    }

    public static void main(String[] args) {
        SpringApplication.run(CocurrentUpdateStockApplication.class, args);
    }
    //mysql减库存任务
    private Callable<Void> updateStockInMysqlTask = () -> {
        final String sql = "update product_stock set stock = stock-1 where product_id=1 and stock>0";
        jdbcTemplate.update(sql);
        return null;
    };
    //redis减库存任务
    private Callable<Void> updateStockInRedisTask = () -> {
        redisTemplate().execute(new RedisCallback<Long>() {
            public Long doInRedis(RedisConnection connection) throws DataAccessException {
                Long decr = connection.decr("1_stock".getBytes());
                return decr;
            }
        });
        return null;
    };

    @Override
    public void run(String... args) throws Exception {
        final String name = "mysql"; // or "redis"
        System.out.printf("start concurrent update stock in %s...%n", name);
        List<Long> timeList = new ArrayList<>();
        for (int i = 0; i < 10; i++) {//分别统计10次
            long start = System.currentTimeMillis();
            concurrentUpdateStock(name); //
            long end = System.currentTimeMillis();
            System.out.printf("Done. Take time: %d ms%n", end - start);
            timeList.add(end - start);
            Thread.sleep(1000); //休眠1秒
        }
        System.out.println(timeList.stream().collect(Collectors.summarizingLong(t -> t))); //输出统计结果

    }

    private void concurrentUpdateStock(String name) throws InterruptedException {
        // 模拟并发更新库存
        int nThreads = 500; //设置一个较大线程数
        ExecutorService pool = Executors.newFixedThreadPool(nThreads);
        List<Callable<Void>> tasks = new ArrayList<>();
        for (int i = 0; i < nThreads * 2; i++) { //2倍于线程数的减库存任务
            if ("mysql".equalsIgnoreCase(name))
                tasks.add(updateStockInMysqlTask);
            else if ("redis".equalsIgnoreCase(name))
                tasks.add(updateStockInRedisTask);
        }
        List<Future<Void>> futureList = pool.invokeAll(tasks); //并发去执行这些任务

        while (futureList.stream().anyMatch(f -> !f.isDone())); //等待任务执行完
        pool.shutdown();

    }

}

输出结果

    mysql：
    LongSummaryStatistics{count=10, sum=11485, min=897, average=1148.500000, max=1458}
    
    redis：
    LongSummaryStatistics{count=10, sum=1706, min=95, average=170.600000, max=493}

结果
并发执行1000次减库存操作 mysql要比redis慢差不多7倍

完整代码见
https://github.com/zhugw/cocurrent_update_stock/blob/master/src/main/java/com/zhugw/CocurrentUpdateStockApplication.java