Springboot基于shardingsphere实现分库分表及读写分离

Myth丶恋晨 2023-07-24 02:39 17阅读 0赞

### 导航 ###

*   *  环境-版本
     *  基础环境
     *  常规用法
     *  读写分离用法
     *  分库分表用法
     *  读写分离+分库分表用法

> [代码地址][Link 1]

## 环境-版本 ##

Springboot：2.2.5.RELEASE  
com.alibaba:druid-spring-boot-starter:1.1.21  
io.shardingsphere:sharding-jdbc-spring-boot-starter:3.1.0

## 基础环境 ##

***数据库权限：***

<table> 
 <thead> 
  <tr> 
   <th>用户</th> 
   <th>tp数据库（查）</th> 
   <th>tp数据库（增）</th> 
   <th>tp1数据库（查）</th> 
   <th>tp1数据库（增）</th> 
   <th>tp2数据库（查）</th> 
   <th>tp2数据库（增）</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>tp</td> 
   <td>√</td> 
   <td>√</td> 
   <td>×</td> 
   <td>×</td> 
   <td>×</td> 
   <td>×</td> 
  </tr> 
  <tr> 
   <td>tp1</td> 
   <td>×</td> 
   <td>×</td> 
   <td>×</td> 
   <td>×</td> 
   <td>×</td> 
   <td>√</td> 
  </tr> 
  <tr> 
   <td>tp2</td> 
   <td>×</td> 
   <td>×</td> 
   <td>×</td> 
   <td>×</td> 
   <td>×</td> 
   <td>√</td> 
  </tr> 
 </tbody> 
</table>

***数据库表结构：***  
tp、tp1、tp2数据下的test\_user、test\_user0、test\_user1结构均一样。  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hc3RlcjMzNg_size_16_color_FFFFFF_t_70]  
***项目结构预览***  
![项目结构预览][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hc3RlcjMzNg_size_16_color_FFFFFF_t_70 1]  
基于shardingsphere，无论是实现的分库分表还是读写分离，对业务代码均没有侵入，因此这里先把基础的代码列出  
***application.yml***

spring:
      profiles:
        #[单库单表]
        #active: single
        #[读写分离]
        active: masterslave
        #[分库分表]
        #active: strategy
        #[读写分离+分库分表]
        #active: masterslavestrategy
      main:
        allow-bean-definition-overriding: true
    server:
      servlet:
        context-path: /tp
      port: 8806
    
    mybatis:
      mapper-locations: classpath:mapping/*Mapper.xml
      type-aliases-package: cn.com.test.sharding.model
    
    
    log4j:
      rootLogger: debug,stdout
      config: classpath:log4j2.xml

***实体TestUser.java***

package cn.com.test.sharding.model;
    
    import com.alibaba.fastjson.JSON;
    
    import java.util.Date;
    
    public class TestUser { 
        public Integer id;
        public String db;
        public String userId;
        public Integer sex;
        public String remark;
        public Date modifyDate;
    
        public Integer getId() { 
            return id;
        }
    
        public void setId(Integer id) { 
            this.id = id;
        }
    
        public String getDb() { 
            return db;
        }
    
        public void setDb(String db) { 
            this.db = db;
        }
    
        public String getUserId() { 
            return userId;
        }
    
        public void setUserId(String userId) { 
            this.userId = userId;
        }
    
        public Integer getSex() { 
            return sex;
        }
    
        public void setSex(Integer sex) { 
            this.sex = sex;
        }
    
        public String getRemark() { 
            return remark;
        }
    
        public void setRemark(String remark) { 
            this.remark = remark;
        }
    
        public Date getModifyDate() { 
            return modifyDate;
        }
    
        public void setModifyDate(Date modifyDate) { 
            this.modifyDate = modifyDate;
        }
    
        @Override
        public String toString() { 
            return JSON.toJSONString(this);
        }
    }

***Dao操作接口TestUserMapper.java***

package cn.com.test.sharding.dao;
    
    import cn.com.test.sharding.model.TestUser;
    import org.springframework.stereotype.Repository;
    
    import java.util.List;
    
    @Repository
    public interface TestUserMapper { 
        void insert(TestUser user);
    
        List<TestUser> list();
    
        List<TestUser> listByremark(String remark);
    
        List<TestUser> listByremarkLimit2(String remark);
    }

***SQL操作 TestUserMapper.xml***

<?xml version="1.0" encoding="UTF-8"?>
    <!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN" "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
    <mapper namespace="cn.com.test.sharding.dao.TestUserMapper">
        <resultMap id="baseResultMap" type="cn.com.test.sharding.model.TestUser">
            <id column="id" jdbcType="INTEGER" property="id"/>
            <id column="db" jdbcType="VARCHAR" property="db"/>
            <result column="user_id" jdbcType="VARCHAR" property="userId"/>
            <result column="sex" jdbcType="INTEGER" property="sex"/>
            <result column="remark" jdbcType="VARCHAR" property="remark"/>
            <result column="modify_time" jdbcType="TIMESTAMP" property="modifyDate"/>
        </resultMap>
        <sql id="base_column_list">
            id,db,user_id,sex,remark,modify_time
        </sql>
        <insert id="insert" parameterType="cn.com.test.sharding.model.TestUser" useGeneratedKeys="true" keyColumn="id" keyProperty="id">
            insert into test_user (
                <include refid="base_column_list"/>
            )
            value (
             #{id,jdbcType=INTEGER},#{db,jdbcType=VARCHAR},#{userId,jdbcType=VARCHAR},#{sex,jdbcType=INTEGER},#{remark,jdbcType=VARCHAR},current_timestamp
            );
        </insert>
        <select id="list" resultMap="baseResultMap">
            select
            <include refid="base_column_list"/>
            from test_user
            where 1=1
    
        </select>
        <select id="listByremark" resultMap="baseResultMap" parameterType="string">
            select
            <include refid="base_column_list"/>
            from test_user
            where remark like #{remark,jdbcType=VARCHAR}
        </select>
        <select id="listByremarkLimit2" resultMap="baseResultMap" parameterType="string">
            select
            <include refid="base_column_list"/>
            from test_user
            where remark like #{remark,jdbcType=VARCHAR}
            limit 2
        </select>
    </mapper>

***操作层 TestController.xml***

package cn.com.test.sharding.controller;
    
    import cn.com.test.sharding.dao.TestUserMapper;
    import cn.com.test.sharding.model.TestUser;
    import com.alibaba.fastjson.JSON;
    import org.slf4j.Logger;
    import org.slf4j.LoggerFactory;
    import org.springframework.beans.factory.annotation.Autowired;
    import org.springframework.web.bind.annotation.GetMapping;
    import org.springframework.web.bind.annotation.RequestMapping;
    import org.springframework.web.bind.annotation.RestController;
    
    import java.util.List;
    import java.util.UUID;
    
    @RestController
    @RequestMapping("/test")
    public class TestController { 
        static Logger logger = LoggerFactory.getLogger(TestController.class);
        @Autowired
        TestUserMapper testUserMapper;
        @GetMapping("/user")
        public String user(TestUser user){ 
            logger.info("请求："+user);
            user.setUserId(UUID.randomUUID().toString());
            testUserMapper.insert(user);
            logger.info(user.toString());
            List<TestUser> userList = testUserMapper.list();
            logger.info("all查询结果："+userList.size()+"\t"+JSON.toJSONString(userList));
            List<TestUser> userList1 = testUserMapper.listByremark(user.getRemark()+"%");
            logger.info("remark查询结果："+userList1.size()+"\t"+JSON.toJSONString(userList1));
            List<TestUser> userList2 = testUserMapper.listByremarkLimit2(user.getRemark()+"%");
            logger.info("remark查询(限定查询2条)结果："+userList2.size()+"\t"+JSON.toJSONString(userList2));
            return JSON.toJSONString(userList);
        }
    
    }

## 常规用法 ##

> 常规用法，既不分库也不分表；读写在一个库上进行

***application-single.yml配置：***

# 不读写分离也不分表分库
    spring:
      servlet:
        multipart:
          max-file-size: 1MB
          max-request-size: 2MB
      datasource:
        username: tp
        password: tp@123
        url: jdbc:mysql://192.168.1.16:3308/tp?useUnicode=true&characterEncoding=utf8&serverTimezone=Asia/Shanghai
        driver-class-name: com.mysql.cj.jdbc.Driver
        type: com.alibaba.druid.pool.DruidDataSource
        initialSize: 2
        minIdle: 2
        maxActive: 20
        maxWait: 60000
        timeBetweenEvictionRunsMillis: 60000
        minEvictableIdleTimeMillis: 300000
        validationQuery: SELECT 1 FROM DUALco
        testWhileIdle: true
        testOnBorrow: false
        testOnReturn: false
        poolPreparedStatements: true
        druid.filters: stat,wall
        maxPoolPreparedStatementPerConnectionSize: 2

***pom.xml引入***

<?xml version="1.0" encoding="UTF-8"?>
    <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
        <modelVersion>4.0.0</modelVersion>
        <parent>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-parent</artifactId>
            <version>2.2.5.RELEASE</version>
            <relativePath/> 
        </parent>
        <groupId>com.test</groupId>
        <artifactId>sprintboot-sharding</artifactId>
        <version>0.0.1-SNAPSHOT</version>
        <packaging>war</packaging>
        <name>sharding-demon</name>
        <description>Spring-boot sharding</description>
    
        <properties>
            <java.version>1.8</java.version>
        </properties>
    
        <dependencies>
            <dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-starter-thymeleaf</artifactId>
                <exclusions>
                    <exclusion>
                        <artifactId>spring-boot-starter-logging</artifactId>
                        <groupId>org.springframework.boot</groupId>
                    </exclusion>
                </exclusions>
            </dependency>
            <dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-starter-web</artifactId>
            </dependency>
            <dependency>
                <groupId>org.mybatis.spring.boot</groupId>
                <artifactId>mybatis-spring-boot-starter</artifactId>
                <version>2.1.1</version>
            </dependency>
            <dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-starter-aop</artifactId>
            </dependency>
            <dependency>
                <groupId>com.alibaba</groupId>
                <artifactId>druid-spring-boot-starter</artifactId>
                <version>1.1.21</version>
            </dependency>
            <dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-starter-log4j2</artifactId>
                <version>2.2.2.RELEASE</version>
            </dependency>
            <dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-devtools</artifactId>
                <scope>runtime</scope>
                <optional>true</optional>
            </dependency>
            <dependency>
                <groupId>mysql</groupId>
                <artifactId>mysql-connector-java</artifactId>
            </dependency>
            <dependency>
                <groupId>com.alibaba</groupId>
                <artifactId>fastjson</artifactId>
                <version>1.2.62</version>
            </dependency>
            <dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-starter-test</artifactId>
                <scope>test</scope>
                <exclusions>
                    <exclusion>
                        <groupId>org.junit.vintage</groupId>
                        <artifactId>junit-vintage-engine</artifactId>
                    </exclusion>
                </exclusions>
            </dependency>
            <dependency>
                <groupId>commons-codec</groupId>
                <artifactId>commons-codec</artifactId>
                <version>1.9</version>
            </dependency>
        </dependencies>
    
        <build>
            <plugins>
                <plugin>
                    <groupId>org.springframework.boot</groupId>
                    <artifactId>spring-boot-maven-plugin</artifactId>
                    <configuration>
                        
                        <fork>true</fork>
                        <excludeDevtools>true</excludeDevtools>
                        <excludes>
                            <exclude>
                                <artifactId>spring-boot-starter-tomcat</artifactId>
                                <groupId>org.springframework.boot</groupId>
                            </exclude>
                        </excludes>
                    </configuration>
                </plugin>
            </plugins>
        </build>
    
    </project>

***常规情况***

> 测试url：localhost:8806/tp/test/user?sex=0&remark=DD&db=0  
> 分析：  
> 这种情况比较容易理解，数据库操作对象清晰可见，数据库：tp，表：test\_user

测试url：http://localhost:8806/tp/test/user?sex=0&remark=DD&db=0  
代码执行结果：  
![在这里插入图片描述][2020040821023269.png]  
数据库：  
![在这里插入图片描述][20200408210325117.png]

## 读写分离用法 ##

> 读写在不同的数据库上  
> 采用策略：在tp上写，在tp1上读 表：test\_user  
> 预期结果：tp上数据正常写入，tp1读取到测试数据

***application-masterslave.yml配置：***

sharding:
      jdbc:
        datasource:
          names: master,slave
          master:
            username: tp
            password: tp@123
            url: jdbc:mysql://192.168.1.16:3308/tp?useUnicode=true&characterEncoding=utf8&serverTimezone=Asia/Shanghai
            driver-class-name: com.mysql.cj.jdbc.Driver
            type: com.alibaba.druid.pool.DruidDataSource
          slave:
            username: tp1
            password: tp1@123
            url: jdbc:mysql://192.168.1.16:3308/tp1?useUnicode=true&characterEncoding=utf8&serverTimezone=Asia/Shanghai
            driver-class-name: com.mysql.cj.jdbc.Driver
            type: com.alibaba.druid.pool.DruidDataSource
        config:
          # 主从库配置 操作表名不会跟上数字（test_user）
          masterslave:
            # 负载均衡策略（load-balance-algorithm-class-name: 指定自定义策略，实现MasterSlaveLoadBalanceAlgorithm且提供无参构造）
            load-balance-algorithm-type: random
            master-data-source-name: master
            slave-data-source-names: slave
            name: demo1
          # 读写分离的实验结果：读库没有数据，所以数据可以正常写入，但是读出结果为空

执行测试前：  
tp:  
![在这里插入图片描述][20200408211357146.png]  
tp1:  
![在这里插入图片描述][20200408211446134.png]  
***执行结果：***  
![在这里插入图片描述][20200408211552251.png]  
tp：  
![在这里插入图片描述][20200408211626250.png]  
tp1

![在这里插入图片描述][20200408211700683.png]

## 分库分表用法 ##

> 相对与读写分离而言，pom无需变化  
> 无论读写，根据db决策使用的数据库，根据sex%2决策使用的表  
> 采用策略：数据库：tp d b 表 ： t e s t u s e r \{db\} 表：test\_user db表：testuser\{sex % 2\}  
> 预期结果：
> 
> > \{db=0,sex=1\}写入tp.test\_user1  
> > \{db=0,sex=2\}写入tp.test\_user0  
> > \{db=1,sex=3\}写入tp1.test\_user1  
> > \{db=1,sex=4\}写入tp1.test\_user0

***application-strategy.yml***

spring:
      main:
        allow-bean-definition-overriding: true
    sharding:
      jdbc:
        datasource:
          names: ds0,ds1
          ds0:
            username: tp
            password: tp@123
            url: jdbc:mysql://192.168.1.16:3308/tp?useUnicode=true&characterEncoding=utf8&serverTimezone=Asia/Shanghai
            driver-class-name: com.mysql.cj.jdbc.Driver
            type: com.alibaba.druid.pool.DruidDataSource
          ds1:
            username: tp1
            password: tp1@123
            url: jdbc:mysql://192.168.1.16:3308/tp1?useUnicode=true&characterEncoding=utf8&serverTimezone=Asia/Shanghai
            driver-class-name: com.mysql.cj.jdbc.Driver
            type: com.alibaba.druid.pool.DruidDataSource
        config:
          sharding:
            props:
              sql.show: true
            #分表分库策略 操作带数字的表和数据源ds[0,1].test_user[0,1]
            tables:
              test_user:
                # 自增主键，这里声明后mapper.xml中返回主键不再可用
                # key-generator-column-name: id
                # 数据节点,均匀分布 单一数据源去除数据库后的表达式即可 eg: ds$.test_user${0..1}
                actual-data-nodes: ds${ 0..1}.test_user${ 0..1}
                #分库策略
                database-strategy:
                  #行表达式
                  inline:
                    #列名称，多个列以逗号分隔
                    sharding-column: db
                    #直接参数里指定了数据源
                    algorithm-expression: ds${ db}
                #分表策略
                table-strategy:
                  #行表达式
                   inline:
                     #分片列
                     sharding-column: sex
                     #分片表达式 对sex列取模
                     algorithm-expression: test_user${ sex % 2}
                   #自定义复杂分片
    # complex:
    # sharding-columns: #分片列名称，多个列以逗号分隔
    # algorithm-class-name: #复合分片算法类名称。实现ComplexKeysShardingAlgorithm并提供无参数的构造器
            #分库分表，根据db决策写入的数据库，根据sex决策写入的表，读取时应为所有来源之和

> \{db=0,sex=1\}写入tp.test\_user1

测试url：localhost:8806/tp/test/user?sex=1&remark=DD&db=0  
清空tp、tp1下的test\_user0、test\_user1

执行结果  
![在这里插入图片描述][20200408213420263.png]tp.test\_user1  
![在这里插入图片描述][20200408213519647.png]

> \{db=0,sex=2\}写入tp.test\_user0

测试url：localhost:8806/tp/test/user?sex=2&remark=DD&db=0  
执行结果（汇总上一种的情况进行查询，所以查询结果应该为2条）：  
![在这里插入图片描述][2020040821370714.png]tp.test\_user0  
![在这里插入图片描述][20200408213734431.png]

> \{db=1,sex=3\}写入tp1.test\_user1

测试url：localhost:8806/tp/test/user?sex=3&remark=DD&db=1  
执行结果（汇总上一种的情况进行查询，所以查询结果应该为3条）：  
![在这里插入图片描述][20200408213958525.png]  
tp1.test\_user1  
![在这里插入图片描述][20200408213930741.png]

> \{db=1,sex=4\}写入tp1.test\_user0

测试url：localhost:8806/tp/test/user?sex=4&remark=DD&db=1  
执行结果（汇总上一种的情况进行查询，所以查询结果应该为4条）：  
![在这里插入图片描述][20200408214144586.png]![在这里插入图片描述][20200408214202723.png]简单整理下对应关系～

<table> 
 <thead> 
  <tr> 
   <th>条件db</th> 
   <th>条件sex</th> 
   <th>数据源</th> 
   <th>操作数据库</th> 
   <th>操作表</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>0</td> 
   <td>1</td> 
   <td>ds0</td> 
   <td>tp</td> 
   <td>test_user1</td> 
  </tr> 
  <tr> 
   <td>0</td> 
   <td>2</td> 
   <td>ds0</td> 
   <td>tp</td> 
   <td>test_user0</td> 
  </tr> 
  <tr> 
   <td>1</td> 
   <td>3</td> 
   <td>ds1</td> 
   <td>tp1</td> 
   <td>test_user1</td> 
  </tr> 
  <tr> 
   <td>1</td> 
   <td>4</td> 
   <td>ds1</td> 
   <td>tp1</td> 
   <td>test_user0</td> 
  </tr> 
 </tbody> 
</table>

## 读写分离+分库分表用法 ##

> 相对与读写分离、分库分表而言，pom无需变化  
> 读slave库，根据db决策查询的数据库，根据sex%2决策查询的表  
> 写master库，根据db决策写入的数据库，根据sex%2决策写入的表  
> 采用策略：数据库：tp d b 表 ： t e s t u s e r \{db\} 表：test\_user db表：testuser\{sex % 2\}  
> 增加tp2并仅对tp2赋予对tp2库所有表的查询权限  
> 预期结果：
> 
> > \{db=0,sex=5\}写入tp.test\_user1 读取tp2两次  
> > \{db=0,sex=6\}写入tp.test\_user0 读取tp2两次  
> > \{db=1,sex=7\}写入tp1.test\_user1 读取tp2两次  
> > \{db=1,sex=8\}写入tp1.test\_user0 读取tp2两次  
> > 注意：db被拆分为两个表，所以读取和写入均在两个表之间决策和聚集

***application-masterslavestrategy***

sharding:
      jdbc:
        datasource:
          names: master0,master1,master0-slave,master1-slave
          master0:
            username: tp
            password: tp@123
            url: jdbc:mysql://192.168.1.16:3308/tp?useUnicode=true&characterEncoding=utf8&serverTimezone=Asia/Shanghai
            driver-class-name: com.mysql.cj.jdbc.Driver
            type: com.alibaba.druid.pool.DruidDataSource
          master1:
            username: tp1
            password: tp1@123
            url: jdbc:mysql://192.168.1.16:3308/tp1?useUnicode=true&characterEncoding=utf8&serverTimezone=Asia/Shanghai
            driver-class-name: com.mysql.cj.jdbc.Driver
            type: com.alibaba.druid.pool.DruidDataSource
          master0-slave:
            username: tp2
            password: tp2@123
            url: jdbc:mysql://192.168.1.16:3308/tp2?useUnicode=true&characterEncoding=utf8&serverTimezone=Asia/Shanghai
            driver-class-name: com.mysql.cj.jdbc.Driver
            type: com.alibaba.druid.pool.DruidDataSource
          master1-slave:
            username: tp2
            password: tp2@123
            url: jdbc:mysql://192.168.1.16:3308/tp2?useUnicode=true&characterEncoding=utf8&serverTimezone=Asia/Shanghai
            driver-class-name: com.mysql.cj.jdbc.Driver
            type: com.alibaba.druid.pool.DruidDataSource
        config:
          sharding:
            tables:
              test_user:
                # 自增主键，这里声明后mapper.xml中返回主键不再可用
                # key-generator-column-name: id
                # 数据节点,均匀分布 单一数据源去除数据库后的表达式即可 eg: ds$.test_user${0..1}
                actual-data-nodes: ds${ 0..1}.test_user${ 0..1}
                #分库策略
                database-strategy:
                  #行表达式
                  inline:
                    #列名称，多个列以逗号分隔
                    sharding-column: db
                    #直接参数里指定了数据源
                    algorithm-expression: ds${ db}
                #分表策略
                table-strategy:
                  #行表达式
                  inline:
                    #分片列
                    sharding-column: sex
                    #分片表达式 对sex列取模
                    algorithm-expression: test_user${ sex % 2}
            master-slave-rules:
                ds0:
                    master-data-source-name: master0
                    slave-data-source-names: master0-slave
                ds1:
                  master-data-source-name: master1
                  slave-data-source-names: master1-slave

测试过程省略，执行结果如下：  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hc3RlcjMzNg_size_16_color_FFFFFF_t_70 2]  
tp.test\_user0  
![在这里插入图片描述][2020040821540317.png]  
tp.test\_user1  
![在这里插入图片描述][20200408215442519.png]  
tp1.test\_user0  
![在这里插入图片描述][20200408215509715.png]  
tp1.test\_user1  
![在这里插入图片描述][20200408215529790.png]tp2.test\_user0  
!\[在这里插入图片描述\](https://img-blog.csdnimg.cn/20200408215603959.png  
tp2.test\_user1  
![在这里插入图片描述][2020040821561921.png]

[Link 1]: https://gitee.com/master336/springboot-sharding.git
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hc3RlcjMzNg_size_16_color_FFFFFF_t_70]: /images/20230528/4aed94c19526446a8c12f0ec37912552.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hc3RlcjMzNg_size_16_color_FFFFFF_t_70 1]: /images/20230528/0579a03a2a784b4cbd564a7446d80f09.png
[2020040821023269.png]: /images/20230528/90265d3cb8104fb692e7f817dbcdb6b0.png
[20200408210325117.png]: /images/20230528/7b67f8f2cf0f4556b9d2bffce9243f94.png
[20200408211357146.png]: /images/20230528/afd7001fdcd2445f9e306f9bc3d5bd93.png
[20200408211446134.png]: /images/20230528/affefc8f76a84f8a970b25874e50bbc3.png
[20200408211552251.png]: /images/20230528/73327c1c6b764f7e9ae2b847c194c42a.png
[20200408211626250.png]: /images/20230528/3d14f531143841ddb720b1f8accb346b.png
[20200408211700683.png]: /images/20230528/c89c469a20a54736a681cc59766ab4c7.png
[20200408213420263.png]: /images/20230528/5fd1d80ecc93451d9b6f4edf66f7d347.png
[20200408213519647.png]: /images/20230528/c4c0bbf891d34deca0440cbd6b22f575.png
[2020040821370714.png]: /images/20230528/a012102770874097b47e888d16ff9d6a.png
[20200408213734431.png]: /images/20230528/30607e294eb04da789c7e3da46037e50.png
[20200408213958525.png]: /images/20230528/20e581fda71e483db3eb755d30686e4d.png
[20200408213930741.png]: /images/20230528/55bc42736f774b1ba7f03ef02123ceac.png
[20200408214144586.png]: https://img-blog.csdnimg.cn/20200408214144586.png
[20200408214202723.png]: /images/20230528/46e91241b9dc4128a8fe484703da4d86.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hc3RlcjMzNg_size_16_color_FFFFFF_t_70 2]: /images/20230528/835602d61c5244bc9c38dfadfde05d66.png
[2020040821540317.png]: /images/20230528/b949e0805dcd48b6b0612bfe21672c6a.png
[20200408215442519.png]: /images/20230528/7658acc0db1749378c2232fe1fb4334b.png
[20200408215509715.png]: /images/20230528/ff8f19658840454eaa5e90621b62fc6d.png
[20200408215529790.png]: /images/20230528/57e19eb077514b7098ed74dd2d38c726.png
[2020040821561921.png]: /images/20230528/f3c37feb76fb46d2993a6ac5e433799b.png