Hibernate part 13：批量检索策略-优快云博客

本文链接：https://blog.youkuaiyun.com/iteye_17225/article/details/82615376

本文介绍Hibernate框架中批量加载策略的应用，特别是如何通过设置batch-size属性来优化Customer与Order之间的关联查询，减少数据库交互次数，提高应用程序性能。

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

从Customer到Order，配置在<set>标签中，batch-size表示一次查询几个客户的订单，而不查询的订单数量，配置为2，表示一次查询两个客户的订单数量

<hibernate-mapping>
	<class name="rock.lee.bean.Customer" table="customer" catalog="test" >
		<id name="id" column="id" type="int">
			<generator class="native"></generator>
		</id>
		<set name="orders" cascade="save-update,delete,delete-orphan" inverse="true"  fetch="select" lazy="true"  batch-size="2">
			<!-- customer表order是中所生成的外键列 -->
			<key column="customer_id"></key>
			<one-to-many class="rock.lee.bean.Order" />
		</set>
		<property name="name" column="name" type="java.lang.String"></property>
		<property name="city" column="city" type="java.lang.String"></property>
	</class>
</hibernate-mapping>

查询所有的Customer并且获得Order集合的大小

	@Test
	public void test05() {
		Session session = HibernateUtils.openSession();
		Transaction transaction = session.beginTransaction();
		
		List<Customer> list = session.createQuery(" from Customer").list();
		for (Customer c : list) {
			System.out.println(c.getOrders().size());
		}
		
		transaction.commit();
		session.close();
	}

SQL：

Hibernate: 
    select
        customer0_.id as id0_,
        customer0_.name as name0_,
        customer0_.city as city0_ 
    from
        test.customer customer0_
Hibernate: 
    select
        orders0_.customer_id as customer4_0_1_,
        orders0_.id as id1_,
        orders0_.id as id1_0_,
        orders0_.address as address1_0_,
        orders0_.money as money1_0_,
        orders0_.customer_id as customer4_1_0_ 
    from
        test.orders orders0_ 
    where
        orders0_.customer_id in (
            ?, ?
        )

通过in条件查询order

从Orders到Customer配置在Customer.hbm.xml中的<class>标签中batch-size，一次查询几个客户

<hibernate-mapping>
      <class name="rock.lee.bean.Customer" table="customer" catalog="test" batch-size="2">
</hibernate-mapping>

检索策略的比较