MyBatis-plus的批量插入方式对比分析

  【摘要】Mybatis批量插入一直是开发者重点关注的问题，本文列举了Mybatis的五种插入方式进行对比分析，验证了五种批量插入的方式的优先级。

1 准备工作

1.1 新建spring项目

  略。

1.2 导入pom.xml依赖

<dependency>
    <groupId>mysql</groupId>
    <artifactId>mysql-connector-java</artifactId>
    <scope>runtime</scope>
</dependency>

<!--Mybatis依赖-->
<dependency>
    <groupId>org.mybatis.spring.boot</groupId>
    <artifactId>mybatis-spring-boot-starter</artifactId>
    <version>2.2.2</version>
</dependency>

<!--Mybatis-Plus依赖-->
<dependency>
    <groupId>com.baomidou</groupId>
    <artifactId>mybatis-plus-boot-starter</artifactId>
    <version>3.5.2</version>
</dependency>

<dependency>
    <groupId>org.projectlombok</groupId>
    <artifactId>lombok</artifactId>
    <optional>true</optional>
</dependency>

1.3 配置yml文件

server:
  port: 8080
 
spring:
  datasource:
    username: mysql用户名
    password: mysql密码
    url: jdbc:mysql://localhost:3306/数据库名字?useUnicode=true&characterEncoding=utf-8&useSSL=false&serverTimezone=UTC
    driver-class-name: com.mysql.cj.jdbc.Driver
 
mybatis:
  mapper-locations: classpath:mapping/*.xml

1.4 创建插入模型

@Data
public class User {
    private int id;
    private String username;
    private String password;
}

2 测试

2.1 Mybatis利用For循环批量插入

1、编写UserService服务类，测试一万条数据的耗时情况：

@Service
public class UserService {
 
    @Resource
    private UserMapper userMapper;
 
    public void InsertUsers(){
        long start = System.currentTimeMillis();
        for(int i = 0 ;i < 10000; i++) {
            User user = new User();
            user.setUsername("name" + i);
            user.setPassword("password" + i);
            userMapper.insertUsers(user);
        }
        long end = System.currentTimeMillis();
        System.out.println("一万条数据总耗时：" + (end-start) + "ms" );
    }
 
}

2、编写UserMapper接口

@Mapper
public interface UserMapper {
 
    Integer insertUsers(User user);
}

3、编写UserMapper.xml文件

<?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="com.ithuang.demo.mapper.UserMapper">
    <insert id="insertUsers">
        INSERT INTO user (username, password)
        VALUES(#{username}, #{password})
    </insert>
</mapper>

4、进行单元测试

@SpringBootTest
class DemoApplicationTests {
 
    @Resource
    private UserService userService;
 
    @Test
    public void insert(){
        userService.InsertUsers();
    }
}

5、输出结果
  一万条数据耗时26348ms

2.2 MyBatis的手动批量提交

1、其他保持不变，Service层作稍微的变化

@Service
public class UserService {
 
    @Resource
    private UserMapper userMapper;
 
    @Resource
    private SqlSessionTemplate sqlSessionTemplate;
 
    public void InsertUsers(){
        //关闭自动提交
        SqlSession sqlSession = sqlSessionTemplate.getSqlSessionFactory().openSession(ExecutorType.BATCH, false);
        UserMapper userMapper = sqlSession.getMapper(UserMapper.class);
        long start = System.currentTimeMillis();
        for(int i = 0 ;i < 10000; i++) {
            User user = new User();
            user.setUsername("name" + i);
            user.setPassword("password" + i);
            userMapper.insertUsers(user);
        }
        sqlSession.commit();
        long end = System.currentTimeMillis();
        System.out.println("一万条数据总耗时：" + (end-start) + "ms" );
    }
}

2、结果输出
  一万条数据总耗时：24516ms。

2.3 Mybatis以集合方式批量新增

1、编写UserService服务类

@Service
public class UserService {
    @Resource
    private UserMapper userMapper;
    public void InsertUsers(){
        long start = System.currentTimeMillis();
        List<User> userList = new ArrayList<>();
        User user;
        for(int i = 0 ;i < 10000; i++) {
            user = new User();
            user.setUsername("name" + i);
            user.setPassword("password" + i);
            userList.add(user);
        }
        userMapper.insertUsers(userList);
        long end = System.currentTimeMillis();
        System.out.println("一万条数据总耗时：" + (end-start) + "ms" );
    }
}

2、编写UserMapper接口

@Mapper
public interface UserMapper {
    Integer insertUsers(List<User> userList);
}

3、编写UserMapper.xml文件

<?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="com.ithuang.demo.mapper.UserMapper">
    <insert id="insertUsers">
        INSERT INTO user (username, password)
        VALUES
        <foreach collection ="userList" item="user" separator =",">
            (#{user.username}, #{user.password})
        </foreach>
    </insert>
</mapper>

4、输出结果
  一万条数据总耗时：521ms

2.4 MyBatis-Plus提供的SaveBatch方法

1、编写UserService服务

@Service
public class UserService extends ServiceImpl<UserMapper, User> implements IService<User> {
 
    public void InsertUsers(){
        long start = System.currentTimeMillis();
        List<User> userList = new ArrayList<>();
        User user;
        for(int i = 0 ;i < 10000; i++) {
            user = new User();
            user.setUsername("name" + i);
            user.setPassword("password" + i);
            userList.add(user);
        }
        saveBatch(userList);
        long end = System.currentTimeMillis();
        System.out.println("一万条数据总耗时：" + (end-start) + "ms" );
    }
}

2、编写UserMapper接口

@Mapper
public interface UserMapper extends BaseMapper<User> {
 
}

3、单元测试结果

  一万条数据总耗时：24674ms

2.5 MyBatis-Plus提供的InsertBatchSomeColumn方法

1、编写EasySqlInjector 自定义类

public class EasySqlInjector extends DefaultSqlInjector {
 
 
    @Override
    public List<AbstractMethod> getMethodList(Class<?> mapperClass, TableInfo tableInfo) {
        // 注意：此SQL注入器继承了DefaultSqlInjector(默认注入器)，调用了DefaultSqlInjector的getMethodList方法，保留了mybatis-plus的自带方法
        List<AbstractMethod> methodList = super.getMethodList(mapperClass, tableInfo);
        methodList.add(new InsertBatchSomeColumn(i -> i.getFieldFill() != FieldFill.UPDATE));
        return methodList;
    }
 
}

2、定义核心配置类注入此Bean

@Configuration
public class MybatisPlusConfig {

@Bean
public EasySqlInjector sqlInjector() {
    return new EasySqlInjector();
}

}
3、编写UserService服务类

public class UserService{
 
    @Resource
    private UserMapper userMapper;
    public void InsertUsers(){
        long start = System.currentTimeMillis();
        List<User> userList = new ArrayList<>();
        User user;
        for(int i = 0 ;i < 10000; i++) {
            user = new User();
            user.setUsername("name" + i);
            user.setPassword("password" + i);
            userList.add(user);
        }
        userMapper.insertBatchSomeColumn(userList);
        long end = System.currentTimeMillis();
        System.out.println("一万条数据总耗时：" + (end-start) + "ms" );
    }
}

4、编写EasyBaseMapper接口

public interface EasyBaseMapper<T> extends BaseMapper<T> {
    /**
     * 批量插入 仅适用于mysql
     *
     * @param entityList 实体列表
     * @return 影响行数
     */
    Integer insertBatchSomeColumn(Collection<T> entityList);
}

5、编写UserMapper接口

@Mapper
public interface UserMapper<T> extends EasyBaseMapper<User> {
    
}

6、单元测试结果

  一万条数据总耗时：575ms

2.6 JDBC原生的批量插入

1、编写JDBC池化工具类

public class JDBCDruidUtils {
    private static DataSource dataSource;

    private static Connection conn;

    /*
   创建数据Properties集合对象加载加载配置文件
    */
    static {
        Properties pro = new Properties();
        //加载数据库连接池对象
        try {
            //获取数据库连接池对象
            pro.load(JDBCDruidUtils.class.getClassLoader().getResourceAsStream("druid.properties"));
            dataSource = DruidDataSourceFactory.createDataSource(pro);
        } catch (Exception e) {
            e.printStackTrace();
        }
    }

    /*
    获取连接
     */
    public static Connection getConnection() throws SQLException {
        return dataSource.getConnection();
    }

    /**
     * 关闭conn,和 statement独对象资源
     *
     * @param connection
     * @param statement
     * @MethodName: close
     * @return: void
     */
    public static void close(Connection connection, Statement statement) {
        if (connection != null) {
            try {
                connection.close();
            } catch (SQLException e) {
                e.printStackTrace();
            }
        }
        if (statement != null) {
            try {
                statement.close();
            } catch (SQLException e) {
                e.printStackTrace();
            }
        }
    }

    /**
     * 关闭 conn , statement 和resultset三个对象资源
     *
     * @param connection
     * @param statement
     * @param resultSet
     * @MethodName: close
     * @return: void
     */
    public static void close(Connection connection, Statement statement, ResultSet resultSet) {
        close(connection, statement);
        if (resultSet != null) {
            try {
                resultSet.close();
            } catch (SQLException e) {             e.printStackTrace();
            }
        }
    }
    /*
    获取连接池对象
     */
    public static DataSource getDataSource() {
        return dataSource;
    }
}

# druid.properties配置
driverClassName=com.mysql.cj.jdbc.Driver
url=jdbc:mysql://localhost:3306/数据库?useUnicode=true&characterEncoding=utf-8&useSSL=false&serverTimezone=UTC
username=用户名
password=密码
initialSize=10
maxActive=50
maxWait=60000

2、编写UserService服务类

public void InsertUsersByJdbc() {
        long start = System.currentTimeMillis();
        Connection connection = null;
        PreparedStatement ps = null;
        try {
            connection = JDBCDruidUtils.getConnection();
            //控制事务:默认不提交
            connection.setAutoCommit(false);
            String sql = "INSERT INTO user (username, password) VALUES (?, ?)";
            ps = connection.prepareStatement(sql);
            User user;
            for (int i = 0; i < 1000000; i++) {
                user = new User();
                user.setUsername("name" + i);
                user.setPassword("password" + i);
                ps.setString(1, user.getUsername());
                ps.setString(2, user.getPassword());
                //将一组参数添加到此 PreparedStatement 对象的批处理命令中。
                ps.addBatch();
            }
            //执行批处理
            ps.executeBatch();
            //手动提交事务
            connection.commit();
        } catch (SQLException e) {
            throw new RuntimeException(e);
        } finally {
            JDBCDruidUtils.close(connection, ps);
        }
        long end = System.currentTimeMillis();
        System.out.println("一万条数据总耗时：" + (end - start) + "ms");
    }

3、输出结果
  1万数据总耗时19000ms。

3 总结

  大量数据的场景下性能对比：InsertBatchSomeColumn>自定义xml以集合的方式>Jdbc原生>SaveBatch>手动for循环批量>自动for循环批量。
  网上很多人都说JDBC原生性能很好，但是我发现其非常差，有可能是我使用的是mybatis-plus依赖，如果这是推论正确，那就可以证明mybatis-plus在mybatis的基础上不仅增强了功能也增强了性能。所以可以得出结论：开发中用mybatis-plus是没有错的，如果想提高性能，只能实施其他方案，比如分库分表，千万别想着JDBC原生性能更好。