使用sharding-jdbc實現(xiàn)水平分表的示例代碼

更新時間：2021年11月03日 10:19:05 作者：穿條秋褲到處跑

本文主要介紹了sharding-jdbc實現(xiàn)水平分表，文中通過示例代碼介紹的非常詳細(xì)，具有一定的參考價值，感興趣的小伙伴們可以參考一下

在mysql中新建數(shù)據(jù)庫sharding_db，新增兩張結(jié)構(gòu)一樣的表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`)
);

此處未指定主鍵自增，因為兩張表的id不能重復(fù)，所以只能從后端傳入id。

添加依賴

<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連接池 -->
<dependency>
    <groupId>com.alibaba</groupId>
    <artifactId>druid</artifactId>
    <version>1.1.20</version>
</dependency>

<!-- Mysql驅(qū)動依賴 -->
<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>

編寫配置文件

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

# 配置Sharding-JDBC的分片策略
# 配置數(shù)據(jù)源，給數(shù)據(jù)源起名g1,g2...此處可配置多數(shù)據(jù)源
spring.shardingsphere.datasource.names=g1

# 配置數(shù)據(jù)源具體內(nèi)容:連接池，驅(qū)動,地址，用戶名，密碼
# 由于上面配置數(shù)據(jù)源只有g(shù)1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 主鍵gid 生成策略為 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 約定id值是偶數(shù)添加到student_1表，如果id是奇數(shù)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}

# 打開sql輸出日志
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

編寫實體類

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

編寫mapper接口

@Repository
public interface StudentMapper extends BaseMapper<Student> {

}

編寫測試類

@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);
        }
    }
}

執(zhí)行測試

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執(zhí)行成功，主鍵通過雪花算法在后端生成，傳入到數(shù)據(jù)庫中，根據(jù)奇偶性進(jìn)行分表。

student_1表數(shù)據(jù)：

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student_2表數(shù)據(jù)：

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兩張表的數(shù)據(jù)分別有5條，但這只是因為雪花算法生成的id奇數(shù)偶數(shù)各5個，不是1:1的關(guān)系，需要注意。
主鍵生成后，根據(jù)策略插入到對應(yīng)的表中，從打印出來的sql可以證明這一點。
通過mapper接口的selectById方法進(jìn)行查詢時，會先根據(jù)主鍵策略判斷在哪個庫，再直接去那個庫根據(jù)主鍵查詢。而如果是通過其它條件查詢，或者是多個id的selectById方法查詢，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);
    }

取了兩張表的id進(jìn)行查詢。

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