第二百二十五节 JPA教程 - JPA列长度示例、JPA列精度范围示例

JPA教程 - JPA列长度示例

使用JPA，我们可以设置字段的列长度。例如，当将字符串字段映射到VARCHAR时，我们可以在@Column 注释中设置VARCHAR长度。

@Column(length=40)
private String name;

例子

下面的代码来自Person.java。

package cn.w3cschool.common;
import static javax.persistence.FetchType.LAZY;
import javax.persistence.Basic;
import javax.persistence.Column;
import javax.persistence.Entity;
import javax.persistence.Id;
import javax.persistence.Lob;
import javax.persistence.Table;

@Entity
@Table(name="EMP")
public class Person {
  @Id
  @Column(name = "EMP_ID")
  private long id;
  
  @Column(length=40)
  private String name;
  private String surname;
  
  public Person() {}

  public Person(String name, String surname) {
    this.name = name;
    this.surname = surname;
  }
  
  public Long getId() {
    return id;
  }
  public void setId(Long id) {
    this.id = id;
  }
  public String getName() {
    return name;
  }
  public void setName(String name) {
    this.name = name;
  }
  public String getSurname() {
    return surname;
  }
  public void setSurname(String surname) {
    this.surname = surname;
  }

  @Override
  public String toString() {
    return "Person [id=" + id + ", name=" + name + ", surname=" + surname + "]";
  }
}

下面的代码来自PersonDaoImpl.java。

package cn.w3cschool.common;

import java.util.List;

import javax.persistence.EntityManager;
import javax.persistence.PersistenceContext;

import org.springframework.transaction.annotation.Transactional;

@Transactional
public class PersonDaoImpl {
  public void test(){
    Person p1 = new Person("Tom", "Smith");
    p1.setId(1L);

    Person p2 = new Person("Jack", "Kook");
    p2.setId(2L);
    
    save(p1);
    save(p2);

    listAll();
    
  }
  private void listAll(){
    List<Person> persons = getAll();
    for (Person person : persons) {
      System.out.println(person);
    }

  }
  @PersistenceContext
  private EntityManager em;
  
  
  public Long save(Person person) {
    em.persist(person);
    return person.getId();
  }
  
  public List<Person>getAll() {
    return em.createQuery("SELECT p FROM Person p", Person.class).getResultList();
  }
  
}

下面的代码是从App.java，主类。

package cn.w3cschool.common;

import org.springframework.context.support.ClassPathXmlApplicationContext;

public class App {

  public static void main(String[] args) {
    ClassPathXmlApplicationContext context = new ClassPathXmlApplicationContext(
        "applicationContext.xml");
    PersonDaoImpl dao = (PersonDaoImpl) context.getBean("personDao");

    dao.test();

    context.close();
    
    Helper.checkData();
  }
}

上面的代码生成以下结果。

以下是数据库转储。

Table Name: EMP
 Row:
    Column Name: EMP_ID,
    Column Type: BIGINT:
    Column Value: 1

    Column Name: NAME,
    Column Type: VARCHAR:
    Column Value: Tom

    Column Name: SURNAME,
    Column Type: VARCHAR:
    Column Value: Smith

 Row:
    Column Name: EMP_ID,
    Column Type: BIGINT:
    Column Value: 2

    Column Name: NAME,
    Column Type: VARCHAR:
    Column Value: Jack

    Column Name: SURNAME,
    Column Type: VARCHAR:
    Column Value: Kook

JPA教程 - JPA列精度范围示例

当将Java float或double值映射到数据库表列时，我们可以设置数字类型列的精度尺度。

以下代码将浮点值映射到具有精度8和尺度2的数据库表列。

@Column(precision=8, scale=2) 
private float hourlyRate;

例子

下面的代码来自Person.java。

package cn.w3cschool.common;
import javax.persistence.Column;
import javax.persistence.Entity;
import javax.persistence.Id;
import javax.persistence.Table;

@Entity
@Table(name="EMP")
public class Person {
  @Id
  private long id;
  
  @Column(unique=true, nullable=false) 
  private String name;
  private String surname;
  @Column(precision=8, scale=2) 
  private float hourlyRate;

  public Person() {}

  public Person(String name, String surname) {
    this.name = name;
    this.surname = surname;
  }

  public float getHourlyRate() {
    return hourlyRate;
  }

  public void setHourlyRate(float hourlyRate) {
    this.hourlyRate = hourlyRate;
  }

  public Long getId() {
    return id;
  }
  public void setId(Long id) {
    this.id = id;
  }
  public String getName() {
    return name;
  }
  public void setName(String name) {
    this.name = name;
  }
  public String getSurname() {
    return surname;
  }
  public void setSurname(String surname) {
    this.surname = surname;
  }

  @Override
  public String toString() {
    return "Person [id=" + id + ", name=" + name + ", surname=" + surname
        + ", hourlyRate=" + hourlyRate + "]";
  }


}

下面的代码来自PersonDaoImpl.java。它显示如何使用Person实体。

package cn.w3cschool.common;


import java.util.List;

import javax.persistence.EntityManager;
import javax.persistence.PersistenceContext;

import org.springframework.transaction.annotation.Transactional;

@Transactional
public class PersonDaoImpl {
  public void test(){
    Person p1 = new Person("Tom", "Smith");
    p1.setId(1L);
    p1.setHourlyRate(3.12222F);
    Person p2 = new Person("Jack", "Kook");
    p2.setId(2L);
    p1.setHourlyRate(2222222223.12222F);
    
    save(p1);
    save(p2);

    listAll();
    
  }
  private void listAll(){
    List<Person> persons = getAll();
    for (Person person : persons) {
      System.out.println(person);
    }

  }
  @PersistenceContext
  private EntityManager em;
  
  
  public Long save(Person person) {
    em.persist(person);
    return person.getId();
  }
  
  public List<Person>getAll() {
    return em.createQuery("SELECT p FROM Person p", Person.class).getResultList();
  }
  
}

以下代码来自App.java。它是主类应用程序。

package cn.w3cschool.common;

import org.springframework.context.support.ClassPathXmlApplicationContext;

public class App {

  public static void main(String[] args) {
    ClassPathXmlApplicationContext context = new ClassPathXmlApplicationContext(
        "applicationContext.xml");
    PersonDaoImpl dao = (PersonDaoImpl) context.getBean("personDao");

    dao.test();

    context.close();
    
    Helper.checkData();
  }
}

上面的代码生成以下结果。

以下是数据库转储。

Table Name: EMP
 Row:
    Column Name: ID,
    Column Type: BIGINT:
    Column Value: 1

    Column Name: HOURLYRATE,
    Column Type: DOUBLE:
    Column Value: 2.222222336E9

    Column Name: NAME,
    Column Type: VARCHAR:
    Column Value: Tom

    Column Name: SURNAME,
    Column Type: VARCHAR:
    Column Value: Smith

 Row:
    Column Name: ID,
    Column Type: BIGINT:
    Column Value: 2

    Column Name: HOURLYRATE,
    Column Type: DOUBLE:
    Column Value: 0.0

    Column Name: NAME,
    Column Type: VARCHAR:
    Column Value: Jack

    Column Name: SURNAME,
    Column Type: VARCHAR:
    Column Value: Kook