SpringBoot分布式项目订单管理实战：Mybatis最佳实践全解

一、架构设计与技术选型

典型分布式订单系统架构：

[网关层] → [订单服务] ←→ [分布式缓存]
    ↑           ↓
[用户服务]   [支付服务]
    ↓           ↓
[MySQL集群] ← [分库分表中间件]

技术栈组合：

• Spring Boot 3.x
• Mybatis-Plus 3.5.x
• ShardingSphere 5.3.x
• Redis 7.x
• Seata 1.7.x

二、核心实现步骤

1. 订单表设计（分库分表场景）

CREATE TABLE t_order_0 (
    order_id BIGINT PRIMARY KEY COMMENT '雪花算法ID',
    user_id INT NOT NULL,
    amount DECIMAL(10,2) UNSIGNED,
    order_status TINYINT DEFAULT 0,
    create_time DATETIME DEFAULT CURRENT_TIMESTAMP,
    update_time DATETIME ON UPDATE CURRENT_TIMESTAMP,
    INDEX idx_user_status(user_id, order_status)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

2. Mybatis-Plus增强配置

@Configuration
@MapperScan("com.orders.mapper")
public class MybatisConfig {

    @Bean
    public MybatisPlusInterceptor mybatisPlusInterceptor() {
        MybatisPlusInterceptor interceptor = new MybatisPlusInterceptor();
        // 分页插件
        interceptor.addInnerInterceptor(new PaginationInnerInterceptor(DbType.MYSQL));
        // 乐观锁插件
        interceptor.addInnerInterceptor(new OptimisticLockerInnerInterceptor());
        return interceptor;
    }
}

3. 分库分表策略实现

# application-sharding.yml
spring:
  shardingsphere:
    datasource:
      names: ds0,ds1
      ds0: # 数据源配置
      ds1: 
    rules:
      sharding:
        tables:
          t_order:
            actualDataNodes: ds${0..1}.t_order_${0..1}
            databaseStrategy:
              standard:
                shardingColumn: user_id
                shardingAlgorithmName: database-inline
            tableStrategy:
              standard:
                shardingColumn: order_id
                shardingAlgorithmName: table-inline
        shardingAlgorithms:
          database-inline:
            type: INLINE
            props:
              algorithm-expression: ds${user_id % 2}
          table-inline:
            type: INLINE
            props:
              algorithm-expression: t_order_${order_id % 2}

4. 订单服务核心实现

@Service
@Slf4j
public class OrderServiceImpl extends ServiceImpl<OrderMapper, Order> 
    implements OrderService {

    @Autowired
    private DistributedLockTemplate lockTemplate;

    @Transactional
    @GlobalTransactional // Seata分布式事务注解
    public Order createOrder(OrderDTO orderDTO) {
        // 幂等性检查
        String lockKey = "order_create:" + orderDTO.getRequestId();
        return lockTemplate.execute(lockKey, 3000, () -> {
            Order order = convertToEntity(orderDTO);
            baseMapper.insert(order);
            // 发送领域事件
            applicationContext.publishEvent(new OrderCreatedEvent(this, order));
            return order;
        });
    }

    @DS("slave") // 指定读从库
    public Page<OrderVO> queryOrders(OrderQuery query, Pageable pageable) {
        return baseMapper.selectPage(new Page<>(pageable.getPageNumber(), pageable.getPageSize()),
                Wrappers.<Order>lambdaQuery()
                        .eq(Order::getUserId, query.getUserId())
                        .between(Order::getCreateTime, query.getStartTime(), query.getEndTime())
                        .orderByDesc(Order::getCreateTime))
                .convert(this::convertToVO);
    }
}

5. Mybatis二级缓存优化

<!-- OrderMapper.xml -->
<cache type="org.mybatis.caches.redis.RedisCache" 
       eviction="LRU"
       flushInterval="600000"
       size="1024"
       readOnly="true"/>

三、性能优化实践

1. 热点订单缓存策略：

@Cached(name = "orderCache", expire = 30, timeUnit = TimeUnit.MINUTES)
public Order getOrderById(Long orderId) {
    return baseMapper.selectById(orderId);
}

@CacheRefresh(refresh = 10, stopRefreshAfterLastAccess = 30, timeUnit = TimeUnit.MINUTES)
public Order getHotOrder(Long orderId) {
    // 高频访问订单特殊处理
}

2. 批量操作优化：

public void batchInsertOrders(List<Order> orders) {
    String sql = "<script>INSERT INTO t_order (...) VALUES " +
            "<foreach collection='list' item='item' separator=','>" +
            "(#{item.userId}, ...)" +
            "</foreach></script>";
    sqlSessionTemplate.insert(sql, orders);
}

四、分布式事务解决方案对比

五、生产环境注意事项

1. 索引优化原则：

   • 遵循最左前缀原则
   • 避免在更新频繁的列建索引
   • 使用覆盖索引减少回表

2. 慢SQL监控配置：

mybatis-plus:
  configuration:
    log-impl: org.apache.ibatis.logging.slf4j.Slf4jImpl
    mapUnderscoreToCamelCase: true
    default-executor-type: REUSE
    aggressive-lazy-loading: false

# 开启SQL监控
spring:
  datasource:
    hikari:
      register-mbeans: true

3. 数据归档方案：

@Scheduled(cron = "0 0 3 * * ?")
public void archiveOrders() {
    LocalDateTime archiveTime = LocalDateTime.now().minusMonths(6);
    baseMapper.archiveOrders(archiveTime);
}

六、监控与排查工具链

1. 日志跟踪：SkyWalking + ELK
2. SQL分析：Arthas + Mybatis-Plus性能分析插件
3. 压测工具：JMeter + Gatling
4. 可视化监控：Grafana + Prometheus

典型监控指标：

• 订单创建TPS
• 平均响应时间（P99）
• 慢SQL占比
• 缓存命中率
• 分库分表均衡度

实战总结：在Spring Boot分布式项目中实施订单管理，需要重点把握分库分表策略、缓存与数据库的协同、分布式事务的选型这三个核心维度。通过Mybatis-Plus的增强功能可以显著提升开发效率，同时要注意避免过度依赖ORM特性导致的性能问题。建议定期进行全链路压测，持续优化数据访问模式。