MybatisPlus 集成 PostgreSQL 存储百度天气数据实战

天气警报信息表：

create table biz_weather_alerts (
 pk_id INT8 not null,
 weather_pk_id INT8 null,
 type VARCHAR(20) null,
 level VARCHAR(10) null,
 title VARCHAR(128) null,
 desc_info VARCHAR(512) null,
 constraint PK_BIZ_WEATHER_ALERTS primary key (pk_id)
);
comment on table biz_weather_alerts is '天气警报信息表';
comment on column biz_weather_alerts.pk_id is '主键';
comment on column biz_weather_alerts.weather_pk_id is '实时天气信息主键';
comment on column biz_weather_alerts.type is '预警事件类型';
comment on column biz_weather_alerts.level is '预警事件等级';
comment on column biz_weather_alerts.title is '预警标题';
comment on column biz_weather_alerts.desc_info is '预警详细提示信息';

*注：原始接口返回的 desc 是关键字，故在数据库中重命名为 desc_info。

天气指数信息表：

create table biz_weather_indexes (
 pk_id INT8 not null,
 weather_pk_id INT8 null,
 name VARCHAR(10) null,
 brief VARCHAR(10) null,
 detail VARCHAR(128) null,
 constraint PK_BIZ_WEATHER_INDEXES primary key (pk_id)
);
comment on column biz_weather_indexes.pk_id is '主键';
comment on column biz_weather_indexes.weather_pk_id is '实时天气信息主键';
comment on column biz_weather_indexes.name is '生活指数中文名称';
comment on column biz_weather_indexes.brief is '生活指数概要说明';
comment on column biz_weather_indexes.detail is '生活指数详细说明';

天气预报信息表：

create table biz_weather_forecasts (
 pk_id INT8 not null,
 weather_pk_id INT8 null,
 date TIMESTAMP null,
 week VARCHAR(3) null,
 high DECIMAL(8,2) null default 999999,
 low DECIMAL(8,2) null default 999999,
 wc_day VARCHAR(10) null,
 wc_night VARCHAR(10) null,
 wd_day VARCHAR(10) null,
 wd_night VARCHAR(10) null,
 text_day VARCHAR(20) null,
 text_night VARCHAR(20) null,
 constraint PK_BIZ_WEATHER_FORECASTS primary key (pk_id)
);
comment on column biz_weather_forecasts.pk_id is '主键';
comment on column biz_weather_forecasts.weather_pk_id is '实时天气信息主键';
comment on column biz_weather_forecasts.date is '日期，北京时区';
comment on column biz_weather_forecasts.week is '星期，北京时区';
comment on column biz_weather_forecasts.high is '最高温度 (℃)';
comment on column biz_weather_forecasts.low is '最低温度 (℃)';
comment on column biz_weather_forecasts.wc_day is '白天风力';
comment on column biz_weather_forecasts.wc_night is '晚上风力';
comment on column biz_weather_forecasts.wd_day is '白天风向';
comment on column biz_weather_forecasts.wd_night is '晚上风向';
comment on column biz_weather_forecasts.text_day is '白天天气现象';
comment on column biz_weather_forecasts.text_night is '晚上天气现象';

小时天气预报表：

create table biz_weather_forecast_hours (
 pk_id INT8 not null,
 weather_pk_id INT8 null,
 text VARCHAR(20) null,
 temp_fc DECIMAL(8,2) null,
 wind_class VARCHAR(10) null,
 wind_dir VARCHAR(10) null,
 rh DECIMAL(8,2) null,
 prec_1h NUMERIC(8,2) null,
 clouds DECIMAL(8,2) null,
 data_time TIMESTAMP null,
 constraint PK_BIZ_WEATHER_FORECAST_HOURS primary key (pk_id)
);
comment on column biz_weather_forecast_hours.pk_id is '主键';
comment on column biz_weather_forecast_hours.weather_pk_id is '实时天气信息主键';
comment on column biz_weather_forecast_hours.text is '天气现象';
comment on column biz_weather_forecast_hours.temp_fc is '温度 (℃)';
comment on column biz_weather_forecast_hours.wind_class is '风力等级';
comment on column biz_weather_forecast_hours.wind_dir is '风向描述';
comment on column biz_weather_forecast_hours.rh is '相对湿度';
comment on column biz_weather_forecast_hours.prec_1h is '1 小时累计降水量 (mm)';
comment on column biz_weather_forecast_hours.clouds is '云量 (%)';
comment on column biz_weather_forecast_hours.data_time is '数据时间';

二、MybatisPlus 实体实现

利用 MybatisPlus 的注解可以简化 ORM 映射。实体类需要对应上述表结构，并处理好 JSON 字段名与数据库列名的差异。

1. 实体关系梳理

实时天气与预警、指数、逐日/小时预报之间均为一对多关系。在 Java 对象中，我们通过 DTO 聚合这些集合，但在入库时需拆分写入。

2. 核心代码实现

以下展示几个关键实体的定义。注意 @SerializedName 用于处理 JSON 反序列化时的字段映射，@TableField 则指定了数据库列名。

预警信息 JavaBean：

package com.yelang.project.weather.domain;
import java.io.Serializable;
import com.baomidou.mybatisplus.annotation.TableField;
import com.baomidou.mybatisplus.annotation.TableId;
import com.baomidou.mybatisplus.annotation.TableName;
import com.google.gson.annotations.SerializedName;
import lombok.AllArgsConstructor;
import lombok.Getter;
import lombok.NoArgsConstructor;
import lombok.Setter;
import lombok.ToString;

@TableName(value = "biz_weather_alerts")
@NoArgsConstructor @AllArgsConstructor @Setter @Getter @ToString
public class WeatherAlerts implements Serializable {
    private static final long serialVersionUID = 9180445236146165608L;
    
    @TableId(value = "pk_id")
    private Long pkId; // 主键
    
    @TableField(value = "weather_pk_id")
    private Long weatherPkId; // 实时天气信息主键
    
    private String type; // 预警事件类型
    private String level; // 预警事件等级
    private String title; // 预警标题
    
    @TableField(value = "desc_info")
    @SerializedName("desc")
    private String descInfo; // 预警详细提示信息
}

逐日天气预报 JavaBean：

package com.yelang.project.weather.domain;
import java.io.Serializable;
import java.math.BigDecimal;
import java.util.Date;
import com.baomidou.mybatisplus.annotation.TableField;
import com.baomidou.mybatisplus.annotation.TableId;
import com.baomidou.mybatisplus.annotation.TableName;
import com.fasterxml.jackson.annotation.JsonFormat;
import com.google.gson.annotations.SerializedName;
import lombok.AllArgsConstructor;
import lombok.Getter;
import lombok.NoArgsConstructor;
import lombok.Setter;
import lombok.ToString;

@TableName(value = "biz_weather_forecasts")
@NoArgsConstructor @AllArgsConstructor @Setter @Getter @ToString
public class WeatherForecasts implements Serializable {
    private static final long serialVersionUID = 4929733391294381721L;
    
    @TableId(value = "pk_id")
    private Long pkId;
    
    @TableField(value = "weather_pk_id")
    private Long weatherPkId;
    
    @JsonFormat(pattern = "yyyy-MM-dd HH:mm:ss")
    private Date date; // 日期，北京时区
    private String week; // 星期，北京时区
    private BigDecimal high = new BigDecimal(999999); // 最高温度
    private BigDecimal low = new BigDecimal(999999); // 最低温度
    
    @TableField(value = "wc_day") @SerializedName("wc_day")
    private String wcDay; // 白天风力
    @TableField(value = "wc_night") @SerializedName("wc_night")
    private String wcNight; // 晚上风力
    @TableField(value = "wd_day") @SerializedName("wd_day")
    private String wdDay; // 白天风向
    @TableField(value = "wd_night") @SerializedName("wd_night")
    private String wdNight; // 晚上风向
    @TableField(value = "text_day") @SerializedName("text_day")
    private String textDay; // 白天天气现象
    @TableField(value = "text_night") @SerializedName("text_night")
    private String textNight; // 晚上天气现象
}

逐小时天气预报 JavaBean：

package com.yelang.project.weather.domain;
import java.io.Serializable;
import java.math.BigDecimal;
import java.util.Date;
import com.baomidou.mybatisplus.annotation.TableField;
import com.baomidou.mybatisplus.annotation.TableId;
import com.baomidou.mybatisplus.annotation.TableName;
import com.fasterxml.jackson.annotation.JsonFormat;
import com.google.gson.annotations.SerializedName;
import lombok.AllArgsConstructor;
import lombok.Getter;
import lombok.NoArgsConstructor;
import lombok.Setter;
import lombok.ToString;

@TableName(value = "biz_weather_forecast_hours")
@NoArgsConstructor @AllArgsConstructor @Setter @Getter @ToString
public class WeatherForecastHours implements Serializable {
    private static final long serialVersionUID = -18102820381727782L;
    
    @TableId(value = "pk_id")
    private Long pkId;
    
    @TableField(value = "weather_pk_id")
    private Long weatherPkId;
    
    private String text; // 天气现象
    
    @TableField(value = "temp_fc") @SerializedName("temp_fc")
    private BigDecimal tempFc; // 温度
    
    @TableField(value = "wind_class") @SerializedName("wind_class")
    private String windClass; // 风力等级
    
    @TableField(value = "wind_dir") @SerializedName("wind_dir")
    private String windDir; // 风向描述
    
    private BigDecimal rh; // 相对湿度
    
    @TableField(value = "prec_1h") @SerializedName("prec_1h")
    private BigDecimal prec1h; // 1 小时累计降水量
    
    private BigDecimal clouds; // 云量
    
    @JsonFormat(pattern = "yyyy-MM-dd HH:mm:ss")
    @TableField(value = "data_time") @SerializedName("data_time")
    private Date dataTime; // 数据时间
}

三、PostgreSQL 持久化实现

数据入库的核心在于 Service 层的逻辑编排。我们需要确保主表插入成功后，子表能正确关联主键 ID，并且整个流程在一个事务内完成。

1. 入库时序图

下图展示了从调用 API 到最终落库的完整交互流程。关键点在于先获取主表 ID，再将其赋值给所有子表记录。

2. 核心代码实现

这里省略通用的 Mapper 和基础 Service 代码，直接展示入口测试类和核心业务逻辑。

测试入口：

package com.yelang.project.unihttp;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.test.context.junit4.SpringRunner;
import com.baomidou.mybatisplus.core.toolkit.IdWorker;
import com.burukeyou.uniapi.http.core.response.HttpResponse;
import com.google.gson.Gson;
import com.yelang.project.thridinterface.BaiduWeatherApiServcie;
import com.yelang.project.weather.domain.BdWeatherDTO;
import com.yelang.project.weather.domain.WeatherInfoDTO;
import com.yelang.project.weather.service.IWeatherNowService;

@SpringBootTest
@RunWith(SpringRunner.class)
public class BaiduWeather2DBCase {
    private static final String DATA_TYPE = "all";
    
    @Autowired
    private BaiduWeatherApiServcie baiduWeatherApiService;
    
    @Autowired
    private IWeatherNowService weatherService;
    
    @Test
    public void bdWeather2PG() {
        String district_id = "430626"; // 行政区划代号
        HttpResponse<String> result = baiduWeatherApiService.getWeather(district_id, DATA_TYPE);
        System.out.println(result.getBodyResult());
        
        Gson gson = new Gson();
        BdWeatherDTO bdWeatherInfo = gson.fromJson(result.getBodyResult(), BdWeatherDTO.class);
        WeatherInfoDTO bdResult = bdWeatherInfo.getResult();
        
        if(null != bdResult) {
            Long weatherId = IdWorker.getId();
            bdResult.getWeatherNow().setPkId(weatherId);
            bdResult.getWeatherNow().setLocationCode(district_id);
            weatherService.insertWeatherInfo(bdResult);
        }
    }
}

持久化 Service 实现：

package com.yelang.project.weather.service.impl;
import java.util.List;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Propagation;
import org.springframework.transaction.annotation.Transactional;
import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
import com.yelang.common.utils.StringUtils;
import com.yelang.project.weather.domain.WeatherAlerts;
import com.yelang.project.weather.domain.WeatherForecastHours;
import com.yelang.project.weather.domain.WeatherForecasts;
import com.yelang.project.weather.domain.WeatherIndexes;
import com.yelang.project.weather.domain.WeatherInfoDTO;
import com.yelang.project.weather.domain.WeatherNow;
import com.yelang.project.weather.mapper.WeatherNowMapper;
import com.yelang.project.weather.service.IWeatherAlertsService;
import com.yelang.project.weather.service.IWeatherForecastHoursService;
import com.yelang.project.weather.service.IWeatherForecastsService;
import com.yelang.project.weather.service.IWeatherIndexesService;
import com.yelang.project.weather.service.IWeatherNowService;

@Service
public class WeatherNowServiceImpl extends ServiceImpl<WeatherNowMapper, WeatherNow> implements IWeatherNowService {
    
    @Autowired
    private IWeatherAlertsService alertsService;
    
    @Autowired
    private IWeatherForecastHoursService forecastHoursService;
    
    @Autowired
    private IWeatherForecastsService forecastsService;
    
    @Autowired
    private IWeatherIndexesService indexesService;
    
    @Transactional(propagation = Propagation.REQUIRED, rollbackFor = Exception.class)
    @Override
    public void insertWeatherInfo(WeatherInfoDTO infoDto) {
        WeatherNow now = infoDto.getWeatherNow();
        
        // Step 1: 保存实时天气信息
        this.baseMapper.insert(now);
        Long weatherId = now.getPkId();
        
        // Step 2: 保存生活指数信息
        List<WeatherAlerts> alerts = infoDto.getAlerts();
        if(StringUtils.isNotEmpty(alerts)) {
            for(WeatherAlerts alert : alerts) {
                alert.setWeatherPkId(weatherId);
            }
            alertsService.saveBatch(alerts);
        }
        
        // Step 3: 保存预警信息
        List<WeatherIndexes> indexes = infoDto.getIndexes();
        if(StringUtils.isNotEmpty(indexes)) {
            for(WeatherIndexes index : indexes) {
                index.setWeatherPkId(weatherId);
            }
            indexesService.saveBatch(indexes);
        }
        
        // Step 4: 保存天气预报
        List<WeatherForecasts> forecasts = infoDto.getForecasts();
        if(StringUtils.isNotEmpty(forecasts)) {
            for(WeatherForecasts forecast : forecasts) {
                forecast.setWeatherPkId(weatherId);
            }
            forecastsService.saveBatch(forecasts);
        }
        
        // Step 5: 保存逐小时天气预报
        List<WeatherForecastHours> forecastHours = infoDto.getForecastHours();
        if(StringUtils.isNotEmpty(forecastHours)) {
            for(WeatherForecastHours forecastHour : forecastHours) {
                forecastHour.setWeatherPkId(weatherId);
            }
            forecastHoursService.saveBatch(forecastHours);
        }
    }
}

3. 数据入库结果

执行上述程序后，控制台会输出日志，表明请求正常且数据已尝试写入。随后可以通过 SQL 验证数据库中的实际内容。

select * from biz_weather_now;
select * from biz_weather_alerts;
select * from biz_weather_forecasts where weather_pk_id = 1955642733221658626;

实时天气数据示例：

逐小时天气预报示例：

总结

本方案完整展示了从 API 采集到 PG 数据库落地的全流程。通过合理设计表结构解决了一对多数据的存储问题，利用 MybatisPlus 简化了实体映射，并在 Service 层通过事务保证了数据的一致性。这套模式同样适用于其他类似结构的第三方数据接入场景。