Mybatis三种批量插入数据的方式

1. 循环插入

mapper.xml:




  
    INSERT INTO tb_student (name, age, phone, address, class_id) VALUES (#{name},#{age},#{phone},#{address},#{classId})
  

mapper接口:

public interface StudentMapper {
    int insert(Student student);
}

测试代码:

@SpringBootTest
class DemoApplicationTests {
	@Resource
	private StudentMapper studentMapper;

	@Test
	public void testInsert(){
		//数据生成
		List studentList = createData(100);

		//循环插入
		long start = System.currentTimeMillis();
		studentList.stream().forEach(student -> studentMapper.insert(student));
		System.out.println(System.currentTimeMillis() - start);
	}

	private List createData(int size){
		List studentList = new ArrayList<>();
		Student student;
		for(int i = 0; i < size; i++){
			student = new Student();
			student.setName("小王" + i);
			student.setAge(18);
			student.setClassId(1);
			student.setPhone("1585xxxx669");
			student.setAddress("未知");
			studentList.add(student);
		}

		return studentList;
	}
}

2. foreach标签

mapper.xml:




  
    INSERT INTO tb_student (name, age, phone, address, class_id) VALUES (#{name},#{age},#{phone},#{address},#{classId})
  

  
    INSERT INTO tb_student (name, age, phone, address, class_id) VALUES
    
        (#{item.name},#{item.age},#{item.phone},#{item.address},#{item.classId})
    
  

mapper接口:

public interface StudentMapper {
    int insert(Student student);

    int insertBatch(List studentList);
}

测试代码:

@SpringBootTest
class DemoApplicationTests {
	@Resource
	private StudentMapper studentMapper;

	@Test
	public void testInsertByForeachTag(){
		//数据生成
		List studentList = createData(100);

		//使用foreach标签,拼接SQL插入
		long start = System.currentTimeMillis();
		studentMapper.insertBatch(studentList);
		System.out.println(System.currentTimeMillis() - start);
	}


	private List createData(int size){
		List studentList = new ArrayList<>();
		Student student;
		for(int i = 0; i < size; i++){
			student = new Student();
			student.setName("小王" + i);
			student.setAge(18);
			student.setClassId(1);
			student.setPhone("1585xxxx669");
			student.setAddress("未知");
			studentList.add(student);
		}

		return studentList;
	}
}

3. 批处理

测试代码:

@SpringBootTest
class DemoApplicationTests {
	@Autowired
	private SqlSessionFactory sqlSessionFactory;

	@Test
	public void testInsertBatch(){
		//数据生成
		List studentList = createData(100);

                //使用批处理
		long start = System.currentTimeMillis();
		SqlSession sqlSession = sqlSessionFactory.openSession(ExecutorType.BATCH,false);
		StudentMapper studentMapperNew = sqlSession.getMapper(StudentMapper.class);
		studentList.stream().forEach(student -> studentMapperNew.insert(student));
		sqlSession.commit();
		sqlSession.clearCache();
		System.out.println(System.currentTimeMillis() - start);
	}

	private List createData(int size){
		List studentList = new ArrayList<>();
		Student student;
		for(int i = 0; i < size; i++){
			student = new Student();
			student.setName("小王" + i);
			student.setAge(18);
			student.setClassId(1);
			student.setPhone("1585xxxx669");
			student.setAddress("未知");
			studentList.add(student);
		}

		return studentList;
	}
}

三种方式的对比

MySQL服务器版本:5.6.4

其他依赖版本如下:



	4.0.0
	
		org.springframework.boot
		spring-boot-starter-parent
		2.4.4
		 
	
	com.buhe
	demo
	0.0.1-SNAPSHOT
	demo
	Demo project for Spring Boot
	
		1.8
	
	
		
			org.springframework.boot
			spring-boot-starter-web
		

		
			org.springframework.boot
			spring-boot-starter-test
			test
		

		
			mysql
			mysql-connector-java
			5.1.41
		
		
			org.mybatis.spring.boot
			mybatis-spring-boot-starter
			1.3.1
		
	

	
		
			
				org.springframework.boot
				spring-boot-maven-plugin
			
		

		
			
				src/main/java
				
					**/*.xml
				
			
		
	


三种插入方式在不同数据量下的表现,测试结果:

插入方式 10条 100条 500条 1000条
循环插入 496ms 3330ms 15584ms 33755ms
foreach标签 268ms 366ms 392ms 684ms
批处理 222ms 244ms 364ms 426ms

三种方式中,批处理的方式效率是最高的,尤其是在数据量大的情况下尤为明显。

其次是foreach标签,foreach标签是通过拼接SQL语句的方式完成批量操作的。但是当拼接的SQL过多,导致SQL大小超过了MySQL服务器中max_allowed_packet变量的值时,会导致操作失败,抛出PacketTooBigException异常。

最后是循环插入的方式,这种方式在数据量小的时候可以使用,在数据量大的情况下效率要低很多。

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