（一）前言
随着 Java 技术和微服务技术逐渐广泛应用，Spring Cloud、Spring Boot 逐渐成为 Java 开发的主流框架，ORM 框架也因此得到重视。
纵观目前主流的 ORM 框架，MyBatis 以灵活著称，但是需要维护复杂的配置，并且不是 Spring 官方的天然全家桶，还得做额外的配置工作；Hibernate 以 HQL 和关系映射著称，但使用起来并不灵活。
Spring Data JPA 是 Spring 基于 ORM 框架、JPA 规范的基础上封装的一套 JPA 应用框架，可使开发者用极简的代码即可实现对数据的访问和操作。它提供了包括增删改查等在内的常用功能，且易于扩展，学习并使用 Spring Data JPA 可以极大提高开发效率。开发者只需自定义仓储（Repository）接口并继承 JpaRepository 接口即可实现基本的 CRUD 功能。由此可以看出，Spring Data JPA 吸取了 MyBatis 和 Hibernate 的优点，其底层以 Hibernate 为封装，对外提供了灵活的使用接口，又非常符合面向对象和 REST 的风格，所以如今越来越多的公司对开发者的技术栈要求由传统的 SSH、SSM 框架逐步变为熟悉 Spring Boot、Spring Cloud、Spring Data 等 Spring 全家桶。
（二）案例实现
2.1 数据库表设计
本文数据库的表设计来自我之前的博客：趣味MySQL：查询NBA球员的冠军总数，一共有三张表：球员表 player，球队表 team，球员球队关系表 player_team。其中，player 和 team 表存在多对多关系，一名球员可能在不同年份为多支球队效力过，一支球队在历史上也拥有多名球员。如：詹姆斯在 2003 - 2010 / 2014 - 2018 年为骑士队效力，2010 - 2014年为迈阿密热火效力；湖人队在历史上拥有过科比、1997 - 2004年的奥尼尔等诸多巨星。表之间的关系架构图如下：
2.2 application 配置
这里可以在 application.yml 文件中开启 JPA SQL 语句的打印配置，以方便代码调试。
spring:
datasource:
url: jdbc:mysql://localhost:3306/nba?useUnicode=true&characterEncoding=utf8&serverTimezone=GMT%2B8
username: root
password: root
driver-class-name: com.mysql.cj.jdbc.Driver
jpa:
show-sql: true
logging:
level:
com.jake.demo.jpa.repository: debug
file: log/jpa-demo.log
2.3 实体类
首先根据数据库表之间的关系创建 JPA Entity，完成代码和数据库之间的 ORM。
@Data
@NoArgsConstructor
@AllArgsConstructor
@Entity
@Table(name = "player")
public class Player {
@Id
@JsonIgnore
private Integer pid;
private String name;
private String position;
}
@Data
@Entity
@Table(name = "team")
public class Team {
@Id
@JsonIgnore
private Integer tid;
private String name;
private String city;
}
本文中，由于 @OneToMany 的默认获取类型（FetchType）为懒加载（LAZY），而设置为 EAGER 后，又会导致递归查询数据库。比如 Player 对象中包含 PlayerTeam 集合，PlayerTeam 集合元素中又包含 Player 对象，Player 对象中又再次包含 PlayerTeam 集合，以此循环递归对数据库做查询，产生大量 SQL 语句。所以，本文不进行主表到中间表的一对多配置。
@Data
@Entity
@Table(name = "player_team",
uniqueConstraints = {@UniqueConstraint(columnNames = {"year", "pid", "tid"})})
public class PlayerTeam {
@Id
@JsonIgnore
private Integer ptid;
private Integer year;
@ManyToOne
@JoinColumn(name = "pid")
private Player player;
@ManyToOne
@JoinColumn(name = "tid")
private Team team;
}
根据 MySQL 中间关系表 player_team 的索引设置唯一约束 uniqueConstraints；当类中字段和表中列命名不同或不遵从下划线 - 小驼峰转换规则时，使用@JoinColumn为多对一关系所在字段设置好数据库表所在列。
2.4 Repository 接口
public interface PlayerRepository extends JpaRepository<Player, Integer> {
@Query("select max(p.pid) from Player p")
Integer findMaxId();
}
由于数据库主键没有设置为自增，所以此处自定义了一个找出数值最大主键的方法，以方便单元测试时设置新插入对象的主键为MAX(ID) + 1。
中间表 PlayerTeam 的 Repository 接口只需直接继承 JpaRepository 即可，无需自定义方法。
public interface PlayerTeamRepository extends JpaRepository<PlayerTeam, Integer> {
}
2.5 单元测试
@RunWith(SpringRunner.class)
@SpringBootTest
@Slf4j
public class PlayerRepositoryTest {
@Autowired
private PlayerRepository playerRepository;
@Test
public void findAll() {
List<Player> allPlayers = playerRepository.findAll();
log.info("all players list: {}", allPlayers);
assertNotNull(allPlayers);
}
@Test
public void findById() {
Player player = playerRepository.findById(1).orElse(null);
log.info("player with id 1: {}", player);
assertNotNull(player);
}
@Test
public void findByConditions() {
Player player = new Player();
player.setName("Kobe");
player.setPosition("Guard");
ExampleMatcher matcher = ExampleMatcher.matching()
.withMatcher("name", ExampleMatcher.GenericPropertyMatchers.startsWith())
.withMatcher("position", ExampleMatcher.GenericPropertyMatchers.contains())
.withIgnorePaths("pid");
Example<Player> example = Example.of(player, matcher);
List<Player> matchedPlayers = playerRepository.findAll(example);
log.info("player named Kobe: {}", matchedPlayers);
assertNotNull(matchedPlayers);
}
@Test
public void save() {
Integer maxId = playerRepository.findMaxId();
Player player = new Player(maxId + 1, "Yao Ming", "Center");
Player savedPlayer = playerRepository.save(player);
log.info("the saved player: {}", savedPlayer);
assertNotNull(savedPlayer);
}
@Test
public void update() {
Integer maxId = playerRepository.findMaxId();
Player player = playerRepository.findById(maxId).orElse(null);
assertNotNull(player);
player.setName("Yi Jianlian");
player.setPosition("Power Forward");
Player updatedPlayer = playerRepository.save(player);
log.info("the updated player: {}", updatedPlayer);
assertNotNull(updatedPlayer);
}
@Test
public void delete() {
Integer maxId = playerRepository.findMaxId();
assertNotNull(maxId);
playerRepository.deleteById(maxId);
}
}
针对 PlayerRepository 的 CRUD 方法，分别写了一个测试方法与之对应，最终打印结果与预期完全一致，相对简单。在做条件匹配时可以使用 ExampleMatcher，该类包含了字符串查询必备的精确、模糊、大小写匹配等。但这里仅仅是对单表 player 的 CRUD；为了验证多表的 JPA Persistence 注解 @ManyToOne 是否可用，对 PlayerTeamRepository 接口也进行单元测试：
@RunWith(SpringRunner.class)
@SpringBootTest
@Slf4j
public class PlayerTeamRepositoryTest {
@Autowired
private PlayerTeamRepository playerTeamRepository;
@Test
public void findAll() {
List<PlayerTeam> allPlayerTeams = playerTeamRepository.findAll();
log.info("allPlayerTeams list: {}", allPlayerTeams);
assertNotNull(allPlayerTeams);
}
}
最终 PlayerTeamRepository 接口 findAll 单元测试方法的打印结果如下：
Hibernate: select playerteam0_.ptid as ptid1_2_, playerteam0_.pid as pid3_2_, playerteam0_.tid as tid4_2_, playerteam0_.year as year2_2_ from player_team playerteam0_
Hibernate: select player0_.pid as pid1_1_0_, player0_.name as name2_1_0_, player0_.position as position3_1_0_ from player player0_ where player0_.pid=?
Hibernate: select team0_.tid as tid1_3_0_, team0_.city as city2_3_0_, team0_.name as name3_3_0_ from team team0_ where team0_.tid=?
Hibernate: select player0_.pid as pid1_1_0_, player0_.name as name2_1_0_, player0_.position as position3_1_0_ from player player0_ where player0_.pid=?
Hibernate: select team0_.tid as tid1_3_0_, team0_.city as city2_3_0_, team0_.name as name3_3_0_ from team team0_ where team0_.tid=?
Hibernate: select player0_.pid as pid1_1_0_, player0_.name as name2_1_0_, player0_.position as position3_1_0_ from player player0_ where player0_.pid=?
Hibernate: select player0_.pid as pid1_1_0_, player0_.name as name2_1_0_, player0_.position as position3_1_0_ from player player0_ where player0_.pid=?
Hibernate: select team0_.tid as tid1_3_0_, team0_.city as city2_3_0_, team0_.name as name3_3_0_ from team team0_ where team0_.tid=?
Hibernate: select player0_.pid as pid1_1_0_, player0_.name as name2_1_0_, player0_.position as position3_1_0_ from player player0_ where player0_.pid=?
Hibernate: select team0_.tid as tid1_3_0_, team0_.city as city2_3_0_, team0_.name as name3_3_0_ from team team0_ where team0_.tid=?
Hibernate: select team0_.tid as tid1_3_0_, team0_.city as city2_3_0_, team0_.name as name3_3_0_ from team team0_ where team0_.tid=?
2019-10-07 17:17:24.971 INFO 15156 --- [ main] c.j.d.j.r.PlayerTeamRepositoryTest : allPlayerTeams list: [PlayerTeam(ptid=15, year=1996, player=Player(pid=3, name=Michael Jordan, position=Shooting Guard), team=Team(tid=2, name=Bulls, city=Chicago)), PlayerTeam(ptid=4, year=1998, player=Player(pid=3, name=Michael Jordan, position=Shooting Guard), team=Team(tid=2, name=Bulls, city=Chicago)), PlayerTeam(ptid=1, year=2000, player=Player(pid=1, name=Kobe Bryant, position=Shooting Guard), team=Team(tid=1, name=Lakers, city=Los Angeles)), PlayerTeam(ptid=8, year=2000, player=Player(pid=4, name=Shaquille O'Neal, position=Center), team=Team(tid=1, name=Lakers, city=Los Angeles)), PlayerTeam(ptid=6, year=2001, player=Player(pid=1, name=Kobe Bryant, position=Shooting Guard), team=Team(tid=1, name=Lakers, city=Los Angeles)), PlayerTeam(ptid=9, year=2001, player=Player(pid=4, name=Shaquille O'Neal, position=Center), team=Team(tid=1, name=Lakers, city=Los Angeles)), PlayerTeam(ptid=16, year=2001, player=Player(pid=13, name=Allen Iverson, position=Shooting Guard), team=Team(tid=25, name=76ers, city=Philadelphia)), PlayerTeam(ptid=7, year=2002, player=Player(pid=1, name=Kobe Bryant, position=Shooting Guard), team=Team(tid=1, name=Lakers, city=Los Angeles)), PlayerTeam(ptid=5, year=2002, player=Player(pid=4, name=Shaquille O'Neal, position=Center), team=Team(tid=1, name=Lakers, city=Los Angeles)), PlayerTeam(ptid=11, year=2009, player=Player(pid=1, name=Kobe Bryant, position=Shooting Guard), team=Team(tid=1, name=Lakers, city=Los Angeles)), PlayerTeam(ptid=13, year=2009, player=Player(pid=2, name=Lebron James, position=Small Forward), team=Team(tid=4, name=Cavaliers, city=Cleveland)), PlayerTeam(ptid=12, year=2010, player=Player(pid=1, name=Kobe Bryant, position=Shooting Guard), team=Team(tid=1, name=Lakers, city=Los Angeles)), PlayerTeam(ptid=14, year=2010, player=Player(pid=2, name=Lebron James, position=Small Forward), team=Team(tid=4, name=Cavaliers, city=Cleveland)), PlayerTeam(ptid=10, year=2012, player=Player(pid=2, name=Lebron James, position=Small Forward), team=Team(tid=3, name=Heat, city=Miami)), PlayerTeam(ptid=3, year=2013, player=Player(pid=2, name=Lebron James, position=Small Forward), team=Team(tid=3, name=Heat, city=Miami)), PlayerTeam(ptid=2, year=2016, player=Player(pid=2, name=Lebron James, position=Small Forward), team=Team(tid=4, name=Cavaliers, city=Cleveland))]
一共执行了 11 条 SQL 语句，其中 1 条是对查出 player_team 表中所有数据，5 条是查出 player 表数据，另 5 条是查出 team 表数据。
这是因为 @ManyToOne 的默认 FetchType 为 EAGER，所以需要会对 player 和 team 表数据进行查询 player_team 对 pid 和 tid 进行去重后的计数都是 5 条：
select count(*) count_pid from (select distinct(pid) from player_team) dp;
select count(*) count_tid from (select distinct(tid) from player_team) dp;
需要根据这 5 条 pid 和 5 条 tid 分别去 player 和 team 表中分别查询并封装 Player 和 Team 对象。
（三）参考文章
