使用sharding-jdbc实现水平分表的示例代码_Java教程

在mysql中新建数据库sharding_db，新增两张结构一样的表student_1和student_2。

CREATE TABLE `student_1` (
`ID`  bigint(20) NOT NULL ,
`NAME`  varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_bin NOT NULL ,
`AGE`  int(11) NOT NULL ,
`GENDER`  varchar(1) CHARACTER SET utf8mb4 COLLATE utf8mb4_bin NOT NULL ,
PRIMARY KEY (`ID`)
);

此处未指定主键自增，因为两张表的id不能重复，所以只能从后端传入id。

添加依赖

<dependency>
  <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-starter-jdbc</artifactId>
</dependency>
<dependency>
  <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-starter-web</artifactId>
</dependency>
<!-- Druid连接池 -->
<dependency>
  <groupId>com.alibaba</groupId>
  <artifactId>druid</artifactId>
  <version>1.1.20</version>
</dependency>

<!-- Mysql驱动依赖 -->
<dependency>
  <groupId>mysql</groupId>
  <artifactId>mysql-connector-java</artifactId>
</dependency>

<!-- MybatisPlus -->
<dependency>
  <groupId>com.baomidou</groupId>
  <artifactId>mybatis-plus-boot-starter</artifactId>
  <version>3.0.5</version>
</dependency>

<!-- Sharding-JDBC -->
<dependency>
  <groupId>org.apache.shardingsphere</groupId>
  <artifactId>sharding-jdbc-spring-boot-starter</artifactId>
  <version>4.0.0-RC1</version>
</dependency>

<!-- lombok -->
<dependency>
  <groupId>org.projectlombok</groupId>
  <artifactId>lombok</artifactId>
</dependency>

<dependency>
  <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-test</artifactId>
  <scope>test</scope>
</dependency>

<dependency>
  <groupId>junit</groupId>
  <artifactId>junit</artifactId>
  <scope>test</scope>
</dependency>

<dependency>
  <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-starter-test</artifactId>
  <scope>test</scope>
  <exclusions>
      <exclusion>
          <groupId>org.junit.vintage</groupId>
          <artifactId>junit-vintage-engine</artifactId>
      </exclusion>
  </exclusions>
</dependency>

编写配置文件

spring.main.allow-bean-definition-overriding=true

# 配置Sharding-JDBC的分片策略
# 配置数据源，给数据源起名g1,g2...此处可配置多数据源
spring.shardingsphere.datasource.names=g1

# 配置数据源具体内容:连接池，驱动,地址，用户名，密码
# 由于上面配置数据源只有g1因此下面只配置g1.type,g1.driver-class-name,g1.url,g1.username,g1.password
spring.shardingsphere.datasource.g1.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.g1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.g1.url=jdbc:mysql://localhost:3306/sharding_db?characterEncoding=utf-8&useUnicode=true&useSSL=false&serverTimezone=UTC
spring.shardingsphere.datasource.g1.username=root
spring.shardingsphere.datasource.g1.password=123456

# 配置表的分布，表的策略
spring.shardingsphere.sharding.tables.student.actual-data-nodes=g1.student_$->{1..2}

# 指定student表 主键gid 生成策略为 SNOWFLAKE
spring.shardingsphere.sharding.tables.student.key-generator.column=id
spring.shardingsphere.sharding.tables.student.key-generator.type=SNOWFLAKE

# 指定分片策略 约定id值是偶数添加到student_1表，如果id是奇数添加到student_2表
spring.shardingsphere.sharding.tables.student.table-strategy.inline.sharding-column=id
spring.shardingsphere.sharding.tables.student.table-strategy.inline.algorithm-expression=student_$->{id % 2 + 1}

# 打开sql输出日志
spring.shardingsphere.props.sql.show=true

或者是yml格式

spring:
main:
  allow-bean-definition-overriding: true
shardingsphere:
  datasource:
    g1:
      driver-class-name: com.mysql.cj.jdbc.Driver
      password: 123456
      type: com.alibaba.druid.pool.DruidDataSource
      url: jdbc:mysql://localhost:3306/sharding_db?characterEncoding=utf-8&useUnicode=true&useSSL=false&serverTimezone=UTC
      username: root
    names: g1
  props:
    sql:
      show: true
  sharding:
    tables:
      student:
        actual-data-nodes: g1.student_$->{1..2}
        key-generator:
          column: id
          type: SNOWFLAKE
        table-strategy:
          inline:
            algorithm-expression: student_$->{id % 2 + 1}
            sharding-column: id

编写实体类

@Data
public class Student {
  private Long id;
  private String name;
  private int age;
  private String gender;
}

编写mapper接口

@Repository
public interface StudentMapper extends BaseMapper<Student> {

}

编写测试类

@SpringBootTest
class ShardingJdbcDemoApplicationTests {

  @Autowired
  private StudentMapper studentMapper;

  @Test
  public void test01() {
      for (int i = 0; i < 10; i++) {
          Student student = new Student();
          student.setName("wuwl");
          student.setAge(27);
          student.setGender("男");
          studentMapper.insert(student);
      }
  }
}

执行测试

使用sharding-jdbc实现水平分表的示例代码

执行成功，主键通过雪花算法在后端生成，传入到数据库中，根据奇偶性进行分表。

student_1表数据：

使用sharding-jdbc实现水平分表的示例代码

student_2表数据：

使用sharding-jdbc实现水平分表的示例代码

两张表的数据分别有5条，但这只是因为雪花算法生成的id奇数偶数各5个，不是1:1的关系，需要注意。
主键生成后，根据策略插入到对应的表中，从打印出来的sql可以证明这一点。
通过mapper接口的selectById方法进行查询时，会先根据主键策略判断在哪个库，再直接去那个库根据主键查询。而如果是通过其它条件查询，或者是多个id的selectById方法查询，又是如何的呢？

  @Test
  public void test03() {
      List<Long> list = new ArrayList<>();
      list.add(1362282042768609282l);
      list.add(1362282040277192705l);
      List<Student> studentList = studentMapper.selectBatchIds(list);
      System.out.println(studentList);
  }

取了两张表的id进行查询。

使用sharding-jdbc实现水平分表的示例代码