springdata jpa使用Example快速实现动态查询功能
目录
- Example官方介绍
- Example api的组成
- 限制
- 使用
- 测试查询
- 自定匹配器规则
- 补充
- 官方创建ExampleMatcher例子(1.8 lambda)
- StringMatcher 参数
- 总结
Example官方介绍
Query by Example (QBE) is a user-friendly querying technique with a simple interface. It allows dynamic query creation and does not require to write queries containing field names. In fact, Query by Example does not require to write queries using store-specific query languages at all.
谷歌翻译:
按例查询(QBE)是一种用户界面友好的查询技术。 它允许动态创建查询,并且不需要编写包含字段名称的查询。 实际上,按示例查询不需要使用特定的数据库的查询语言来编写查询语句。
Example api的组成
Probe
:含有对应字段的实例对象。ExampleMatcher
:ExampleMatcher携带有关如何匹配特定字段的详细信息,相当于匹配条件。Example
:由Probe和ExampleMatcher组成,用于查询。
限制
- 属性不支持嵌套或者分组约束,比如这样的查询 firstname = ?0 or (firstname = ?1 and lastname = ?2)
- 灵活匹配只支持字符串类型,其他类型只支持精确匹配
Limitations
1. No support for nested/grouped property constraints like firstname = ?0 or (firstname = ?1 and lastname = ?2)
2. Only supports starts/contains/ends/regex matching for strings and exact matching for other property types
使用
创建实体映射:
@Entity @Table(name="t_user") @Data @AllArgsConstructor @NoArgsConstructor @ToString public class User { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) private Integer id; @Column(name="username") private String username; @Column(name="password") private String password; @Column(name="email") private String email; @Column(name="phone") private String phone; @Column(name="address") private String address; }
测试查询
@Test public void contextLoads() { User user = new User(); user.setUsername("admin"); Example<User> example = Example.of(user); List<User> list = userRepository.findAll(example); System.out.println(list); }
打印的sql语句如下:
Hibernate: select user0_.id as id1_0_, user0_.address as address2_0_, user0_.email as email3_0_, user0_.password as password4_0_, user0_.phone as phone5_0_, user0_.username as username6_0_ from t_user user0_ where user0_.username=?
可以发现,试用Example查询,默认情况下会忽略空值,官方文档也有说明:
This is a simple domain object. You can use it to create an Example. By default, fields having null values are ignored, and strings are matched using the store specific defaults. Examples can be built by either using the of factory method or by using ExampleMatcher. Example is immutable.
在上面的测试之中,我们只是只是定义了Probe而没有ExampleMatcher,是因为默认会不传时会使用默认的匹配器。点进方法可以看到下面的代码:
static <T> Example<T> of(T probe) { return new TypedExample(probe, ExampleMatcher.matching()); } static ExampleMatcher matching() { return matchingAll(); } static ExampleMatcher matchingAll() { return (new TypedExampleMatcher()).withMode(ExampleMatcher.MatchMode.ALL); }
自定匹配器规则
@Test public void contextLoads() { User user = new User(); user.setUsername("y"); user.setAddress("sh"); user.setPassword("admin"); ExampleMatcher matcher = ExampleMatcher.matching() .withMatcher("username", ExampleMatcher.GenericPropertyMatchers.startsWith())//模糊查询匹配开头,即{username}% .withMatcher("address" ,ExampleMatcher.GenericPropertyMatchers.contains())//全部模糊查询,即%{address}% .withIgnorePaths("password");//忽略字段,即不管password是什么值都不加入查询条件 Example<User> example = Example.of(user ,matcher); List<User> list = userRepository.findAll(example); System.out.println(list); }
打印的sql语句如下:
select user0_.id as id1_0_, user0_.address as address2_0_, user0_.email as email3_0_, user0_.password as password4_0_, user0_.phone as phone5_0_, user0_.username as username6_0_ from t_user user0_ where ( user0_.username like ? ) and ( user0_.address like ? )
参数如下:
2018-03-24 13:26:57.425 TRACE 5880 --- [ main] o.h.type.descriptor.sql.BasicBinder : binding parameter [1] as [VARCHAR] - [y%]
2018-03-24 13:26:57.425 TRACE 5880 --- [ main] o.h.type.descriptor.sql.BasicBinder : binding parameter [2] as [VARCHAR] - [%sh%]
补充
官方创建ExampleMatcher例子(1.8 lambda)
ExampleMatcher matcher = ExampleMatcher.matching() .withMatcher("firstname", match -> match.endsWith()) .withMatcher("firstname", match -> match.startsWith()); }
StringMatcher 参数
Matching | 生成的语句 | 说明 |
---|---|---|
DEFAULT (case-sensitive) | firstname = ?0 | 默认(大小写敏感) |
DEFAULT (case-insensitive) | LOWER(firstname) = LOWER(?0) | 默认(忽略大小写) |
EXACT (case-sensitive) | firstname = ?0 | 精确匹配(大小写敏感) |
EXACT (case-insensitive) | LOWER(firstname) = LOWER(?0) | 精确匹配(忽略大小写) |
STARTING (case-sensitive) | firstname like ?0 + ‘%' | 前缀匹配(大小写敏感) |
STARTING (case-insensitive) | LOWER(firstname) like LOWER(?0) + ‘%' | 前缀匹配(忽略大小写) |
ENDING (case-sensitive) | firstname like ‘%' + ?0 | 后缀匹配(大小写敏感) |
ENDING (case-insensitive) | LOWER(firstname) like ‘%' + LOWER(?0) | 后缀匹配(忽略大小写) |
CONTAINING (case-sensitive) | firstname like ‘%' + ?0 + ‘%' | 模糊查询(大小写敏感) |
CONTAINING (case-insensitive) | LOWER(firstname) like ‘%' + LOWER(?0) + ‘%' | 模糊查询(忽略大小写) |
说明:
1. 在默认情况下(没有调用withIgnoreCase())都是大小写敏感的。
2. api之中还有个regex,但是我在mysql下测试报错,不了解具体作用。
总结
通过在使用springdata jpa时可以通过Example来快速的实现动态查询,同时配合Pageable可以实现快速的分页查询功能。
对于非字符串属性的只能精确匹配,比如想查询在某个时间段内注册的用户信息,就不能通过Example来查询
以上为个人经验,希望能给大家一个参考,也希望大家多多支持我们。