Sharding-JDBC分库分表实战指南(一)

shardingSphere-JDBC是Apache ShardingSphere的第一个产品，也是ShardingSphere的前身。它定位为轻量级Java框架，在Java的JDBC层提供的额外服务。它使用客户端直连数据库，以jar包形式提供服务，无需额外部署和依赖，可理解为增强版的JDBC驱动，完全兼容JDBC和各种ORM框架。

shardingSphere-JDBC的核心功能是数据分片和读写分离。数据分片包括水平分库、水平分表、垂直分库、垂直分表等多种分片方式。读写分离功能可以将写操作指向主库，读操作分散到多个从库，提高系统吞吐量。

ShardingSphere 官网：概览 :: ShardingSphere

ShardingSphere github：https://github.com/apache/shardingsphere

ShardingSphere-5.2.1 Demo：https://gitee.com/original-intention/sharding-jdbc-gorgor

⼆、理解分库分表的核⼼概念

1、ShardingSphere分库分表的核⼼概念

ShardingSphere 分库分表的核⼼概念围绕 数据分⽚（Sharding） 展开，旨在通过透明化路由将单库单表的数据分散到多个数据库/表中，解决海量数据存储与高并发访问的性能瓶颈。以下是其核心概念解析：

虚拟库： ShardingSphere的核⼼就是提供⼀个具备分库分表功能的虚拟库，他是⼀个ShardingSphereDatasource实例。应⽤程序只需要像操作单数据源⼀样访问这个ShardingSphereDatasource即可。示例中，MyBatis框架并没有特殊指定DataSource，就是使⽤的ShardingSphere的DataSource数据源。
真实库：实际保存数据的数据库。这些数据库都被包含在ShardingSphereDatasource实例当中，由ShardingSphere 决定未来需要使⽤哪个真实库。示例中，m0和m1就是两个真实库。
逻辑表：应⽤程序直接操作的逻辑表。示例中操作的course表就是⼀个逻辑表，并不需要在数据库中真实存在。
真实表：实际保存数据的表。这些真实表与逻辑表表名不需要⼀致，但是需要有相同的表结构，可以分布在不同的真实库中。应⽤可以维护⼀个逻辑表与真实表的对应关系，所有的真实表默认也会映射成为ShardingSphere的虚拟表。示例中course_1和course_2就是真实表。
分布式主键⽣成算法：给逻辑表⽣成唯⼀主键。由于逻辑表的数据是分布在多个真实表当中的，所有，单表的索引就⽆法保证逻辑表的ID唯⼀性。因此，在做分库分表时，通常都会独⽴出⼀个⽣成分布式ID的主键⽣成算法。示例中使⽤的SNOWFLAKE雪花算法就是⼀种很常⻅的主键⽣成算法。
分⽚策略：表示逻辑表要如何分配到真实库和真实表当中，分为分库策略和分表策略两个部分。分⽚策略由分⽚键和分⽚算法组成。分⽚键是进⾏数据⽔平拆分的关键字段。分⽚算法则表示根据分⽚键如何寻找对应的真实库和真实表。示例当中对cid字段取模，就是⼀种简单的分⽚算法。如果ShardingSphere匹配不到合适的分⽚策略，那就只能进⾏全分⽚路由，这是效率最差的⼀种实现⽅式。

核心分层架构

层级	职责	关键实现
逻辑层	开发者视角的虚拟表/库（如 `order_db`, `order_table`）	`LogicSchema`, `LogicTable`
物理层	真实存储节点（如 `ds_0.order_table_0`, `ds_1.order_table_1`）	`ActualDataSource`, `ActualTable`
路由层	根据分片规则将 SQL 路由到物理节点	`ShardingRouter`
执行层	多线程并行操作物理库表	`ShardingExecutor`
归并层	合并多个物理节点的查询结果（如排序、聚合）	`MergeEngine`

2、垂直分⽚和⽔平分⽚

当我们设计分库分表⽅案时，通常有两种拆分数据的维度。

⼀是按照业务划分的维度，将不同的表拆分到不同的库当中。这样可以减少每个数据库的数据量以及客户端的连接数，提⾼查询效率。这种⽅案称为垂直分库。
⼆是按照数据分布的维度，将原本存在同⼀张表当中的数据，拆分到多张⼦表当中。每个⼦表只存储⼀部分数据。这样可以介绍每⼀张表的数据量，提升查询效率。这种⽅案称为⽔平分表

常我们讲的分库分表，主要是指⽔平分⽚，因为这样才能减少数据量，从根本上解决数据量过⼤带来的存储和查询的问题。但是，这也并不意味着垂直分⽚⽅案就不重要。

三、分库分表的案例

案例是基于ShardingSphere-Jdbc 5.2.1 版本进行讲解。

此次案例准备把一张课程表，拆分到两个库和四个表中，具体如下图：

Course表的建表语句如下：

CREATE TABLE `course` (
  `cid` bigint(20) NOT NULL,
  `cname` varchar(50) NOT NULL,
  `user_id` bigint(20) NOT NULL,
  `cstatus` varchar(10) NOT NULL,
  PRIMARY KEY (`cid`) USING BTREE
) ENGINE=InnoDB DEFAULT CHARSET=utf8 ROW_FORMAT=DYNAMIC;

shardingsphere-jdbc 整合 spring boot 核心 jar 包

 <dependency>
    <groupId>org.apache.shardingsphere</groupId>
    <artifactId>shardingsphere-jdbc-core-spring-boot-starter</artifactId>
    <version>5.2.1</version>
</dependency>

1. 快速搭建案例项目

1.1 引入 Maven依赖

<dependencyManagement>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-dependencies</artifactId>
            <version>2.2.1.RELEASE</version>
            <type>pom</type>
            <scope>import</scope>
        </dependency>
        <!-- mybatisplus依赖 -->
        <dependency>
            <groupId>com.baomidou</groupId>
            <artifactId>mybatis-plus-boot-starter</artifactId>
            <version>3.0.5</version>
        </dependency>
        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>druid-spring-boot-starter</artifactId>
            <version>1.1.20</version>
        </dependency>
    </dependencies>
</dependencyManagement>
<dependencies>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter</artifactId>
    </dependency>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-test</artifactId>
    </dependency>
    <!-- 数据源连接池 -->
    <dependency>
        <groupId>com.alibaba</groupId>
        <artifactId>druid-spring-boot-starter</artifactId>
        <version>1.1.20</version>
    </dependency>
    <!-- mysql连接驱动 -->
    <dependency>
        <groupId>mysql</groupId>
        <artifactId>mysql-connector-java</artifactId>
    </dependency>
    <!-- mybatisplus依赖 -->
    <dependency>
        <groupId>com.baomidou</groupId>
        <artifactId>mybatis-plus-boot-starter</artifactId>
        <version>3.4.3.3</version>
    </dependency>
</dependencies>

1.2 在springboot的配置⽂件application.properties中增加数据库配置

pring.datasource.druid.db-type=mysql
spring.datasource.druid.driver-class-name=com.mysql.cj.jdbc.Driver
spring.datasource.druid.url=jdbc:mysql://192.168.65.212:3306/test?serverTimezone=UTC
spring.datasource.druid.username=root
spring.datasource.druid.password=root

1.3 使⽤MyBatis-plus的⽅式，直接声明Entity和Mapper，映射数据库中的course表。

public class Course {
    private Long cid;
    private String cname;
    private Long userId;
    private String cstatus;
    //省略。getter ... setter ....
}
public interface CourseMapper extends BaseMapper<Course> {
}

1.4 增加SpringBoot启动类，扫描mapper接⼝

@SpringBootApplication
@MapperScan("com.roy.jdbcdemo.mapper")
public class App {
    public static void main(String[] args) {
    SpringApplication.run(App.class,args);
    }
}

1.5 做⼀个单元测试，简单的把course课程信息插⼊到数据库，以及从数据库中进⾏查询

@SpringBootTest
@RunWith(SpringRunner.class)
public class JDBCTest {
    @Resource
    private CourseMapper courseMapper;

    @Test
    public void addcourse() {
        for (int i = 0; i < 10; i++) {
            Course c = new Course();
            c.setCname("java");
            c.setUserId(1001L);
            c.setCstatus("1");
            courseMapper.insert(c);
//insert into course values ....
            System.out.println(c);
        }
    }

    @Test
    public void queryCourse() {
        QueryWrapper<Course> wrapper = new QueryWrapper<Course>();
        wrapper.eq("cid", 1L);
        List<Course> courses = courseMapper.selectList(wrapper);
        courses.forEach(course -> System.out.println(course));
    }
}

2.引入ShardingJdbc实现分库分片

1.1 在pom.xml中引入ShardingSphere

<dependencies>
        <!-- shardingJDBC核心依赖 -->
        <dependency>
            <groupId>org.apache.shardingsphere</groupId>
            <artifactId>shardingsphere-jdbc-core-spring-boot-starter</artifactId>
            <version>5.2.1</version>
            <exclusions>
                <exclusion>
                    <artifactId>snakeyaml</artifactId>
                    <groupId>org.yaml</groupId>
                </exclusion>
            </exclusions>
        </dependency>
        <!-- 版本冲突 -->
        <dependency>
            <groupId>org.yaml</groupId>
            <artifactId>snakeyaml</artifactId>
            <version>1.33</version>
        </dependency>
        <!-- SpringBoot依赖 -->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter</artifactId>
            <exclusions>
                <exclusion>
                    <artifactId>snakeyaml</artifactId>
                    <groupId>org.yaml</groupId>
                </exclusion>
            </exclusions>
        </dependency>
        <!-- 数据源连接池 -->
        <!--注意不要用这个依赖，他会创建数据源，跟上面ShardingJDBC的SpringBoot集成依赖有冲突 -->
        <!--        <dependency>-->
        <!--            <groupId>com.alibaba</groupId>-->
        <!--            <artifactId>druid-spring-boot-starter</artifactId>-->
        <!--            <version>1.1.20</version>-->
        <!--        </dependency>-->
        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>druid</artifactId>
            <version>1.1.20</version>
        </dependency>
        <!-- mysql连接驱动 -->
        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
        </dependency>
        <!-- mybatisplus依赖 -->
        <dependency>
            <groupId>com.baomidou</groupId>
            <artifactId>mybatis-plus-boot-starter</artifactId>
            <version>3.4.3.3</version>
        </dependency>
  <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
        </dependency>
    </dependencies>

1.2 在对应数据库里创建分片表

按照我们之前的设计，去对应的数据库中自行创建course_1和course_2表。表结构与course表是一致的。

初始化SQL在项目：resources/sql

1.3 增加ShardingJDBC的分库分表配置

### -------------------------------数据源配置-------------------------------------------------
# 指定对应的库
spring.shardingsphere.datasource.names=m0,m1

spring.shardingsphere.datasource.m0.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m0.url=jdbc:mysql://localhost:3306/shardingdb1?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m0.username=root
spring.shardingsphere.datasource.m0.password=root

spring.shardingsphere.datasource.m1.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m1.url=jdbc:mysql://localhost:3306/shardingdb2?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m1.username=root
spring.shardingsphere.datasource.m1.password=root
### -------------------------------数据源配置-------------------------------------------------

### --------------------------------分布式序列算法配置---------------------------------------------------------
# 指定分布式主键生成策略
spring.shardingsphere.rules.sharding.tables.course.key-generate-strategy.column=cid
spring.shardingsphere.rules.sharding.tables.course.key-generate-strategy.key-generator-name=alg_snowflake
# 雪花算法，生成Long类型主键。
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.type=SNOWFLAKE
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.worker-id=1
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.max-vibration-offset=8
### --------------------------------分布式序列算法配置---------------------------------------------------------


### --------------------------------------配置实际分片节点------------------------------------------------
spring.shardingsphere.rules.sharding.tables.course.actual-data-nodes=m$->{0..1}.course_$->{1..2}
### --------------------------------------配置实际分片节点------------------------------------------------

### ---------------------------inline 分库配置--------------------------------------------------------------
# 分库字段
spring.shardingsphere.rules.sharding.tables.course.database-strategy.standard.sharding-column=user_id
# 分库算法名称
spring.shardingsphere.rules.sharding.tables.course.database-strategy.standard.sharding-algorithm-name=db_inline_algorithm
# 分库算法
spring.shardingsphere.rules.sharding.sharding-algorithms.db_inline_algorithm.type=MOD
spring.shardingsphere.rules.sharding.sharding-algorithms.db_inline_algorithm.props.sharding-count=2
### ---------------------------inline 分库配置--------------------------------------------------------------


### ---------------------------inline 分表配置--------------------------------------------------------------
# 分表字段
spring.shardingsphere.rules.sharding.tables.course.table-strategy.standard.sharding-column=user_id
# 分表算法名称
spring.shardingsphere.rules.sharding.tables.course.table-strategy.standard.sharding-algorithm-name=table_inline_algorithm
# 分表算法 --> 四种数据分片方式 INLINE|STANDARD|COMPLEX|HINT
spring.shardingsphere.rules.sharding.sharding-algorithms.table_inline_algorithm.type=INLINE
spring.shardingsphere.rules.sharding.sharding-algorithms.table_inline_algorithm.props.algorithm-expression=course_$->{user_id.intdiv(2) % 2 + 1}
### ---------------------------inline 分表配置--------------------------------------------------------------

# inline允许进行范围查询
spring.shardingsphere.rules.sharding.sharding-algorithms.table_inline_algorithm.props.allow-range-query-with-inline-sharding=true

1.4 单元测试

@SpringBootTest
@RunWith(SpringRunner.class)
public class InlineTest {

    @Autowired
    private CourseMapper courseMapper;

    @BeforeClass
    public static void setUp() {
        //设置系统属性
        System.setProperty("spring.profiles.active", "inline");
    }


    @Test
    public void testInlineDemo() {
        for (Long i = 1L; i < 10L; i++) {
            Course c = new Course();
            c.setCname("java");
            c.setUserId(i);
            c.setCstatus("1");
            courseMapper.insert(c);
        }

    }

    /**
     * 精确查询
     * @return
     */
    @Test
    public void testInlineDemo1() {
        Course course = courseMapper.selectByUseId(7L);
        System.out.println(course);
    }

    /**
     * inline 分片算法默认不支持范围查询，除非配置下面配置
     * # inline允许进行范围查询
     * spring.shardingsphere.rules.sharding.sharding-algorithms.table_standard_algorithm.props.allow-range-query-with-inline-sharding=true
     */
    @Test
    public void testBetweenDemo() {
        List<Course> courses = courseMapper.selectByBetweenUserId(1L, 6L);
        System.out.println(courses);
    }
    
}

四、ShardingJDBC常⻅数据分⽚策略实战

分片策略全景图

策略类型	适用场景	支持操作符	分片键数量	实现复杂度
行表达式(Inline)	简单取模/哈希路由	`=`, `IN`	单分片键	⭐
标准(Standard)	精确查询+范围查询	`=`, `IN`, `>`, `<`, `BETWEEN`	单分片键	⭐⭐
复合(Complex)	多字段组合路由	`=`, `IN`, `范围查询`	多分片键	⭐⭐⭐
Hint(强制路由)	外部逻辑指定路由	任意SQL	无需分片键	⭐⭐

分片策略实战详解

1. 行表达式分片策略（Inline）

场景：单分片键的简单路由（如用户ID取模）
优势：零代码开发，Groovy表达式配置
单元测试：com.gorgor.shardingjdbc.InlineTest
示例配置：

### -------------------------------数据源配置-------------------------------------------------
# 指定对应的库
spring.shardingsphere.datasource.names=m0,m1

spring.shardingsphere.datasource.m0.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m0.url=jdbc:mysql://localhost:3306/shardingdb1?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m0.username=root
spring.shardingsphere.datasource.m0.password=root

spring.shardingsphere.datasource.m1.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m1.url=jdbc:mysql://localhost:3306/shardingdb2?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m1.username=root
spring.shardingsphere.datasource.m1.password=root
### -------------------------------数据源配置-------------------------------------------------

### --------------------------------分布式序列算法配置---------------------------------------------------------
# 指定分布式主键生成策略
spring.shardingsphere.rules.sharding.tables.course.key-generate-strategy.column=cid
spring.shardingsphere.rules.sharding.tables.course.key-generate-strategy.key-generator-name=alg_snowflake
# 雪花算法，生成Long类型主键。
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.type=SNOWFLAKE
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.worker-id=1
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.max-vibration-offset=8
### --------------------------------分布式序列算法配置---------------------------------------------------------


### --------------------------------------配置实际分片节点------------------------------------------------
spring.shardingsphere.rules.sharding.tables.course.actual-data-nodes=m$->{0..1}.course_$->{1..2}
### --------------------------------------配置实际分片节点------------------------------------------------

### ---------------------------inline 分库配置--------------------------------------------------------------
# 分库字段
spring.shardingsphere.rules.sharding.tables.course.database-strategy.standard.sharding-column=user_id
# 分库算法名称
spring.shardingsphere.rules.sharding.tables.course.database-strategy.standard.sharding-algorithm-name=db_inline_algorithm
# 分库算法
spring.shardingsphere.rules.sharding.sharding-algorithms.db_inline_algorithm.type=MOD
spring.shardingsphere.rules.sharding.sharding-algorithms.db_inline_algorithm.props.sharding-count=2
### ---------------------------inline 分库配置--------------------------------------------------------------


### ---------------------------inline 分表配置--------------------------------------------------------------
# 分表字段
spring.shardingsphere.rules.sharding.tables.course.table-strategy.standard.sharding-column=user_id
# 分表算法名称
spring.shardingsphere.rules.sharding.tables.course.table-strategy.standard.sharding-algorithm-name=table_inline_algorithm
# 分表算法 --> 四种数据分片方式 INLINE|STANDARD|COMPLEX|HINT
spring.shardingsphere.rules.sharding.sharding-algorithms.table_inline_algorithm.type=INLINE
spring.shardingsphere.rules.sharding.sharding-algorithms.table_inline_algorithm.props.algorithm-expression=course_$->{user_id.intdiv(2) % 2 + 1}
### ---------------------------inline 分表配置--------------------------------------------------------------

# inline允许进行范围查询
spring.shardingsphere.rules.sharding.sharding-algorithms.table_inline_algorithm.props.allow-range-query-with-inline-sharding=true

2. 标准分片策略（Standard）

场景：需同时处理精确查询（=）和范围查询（BETWEEN）
开发要点：
1. 实现PreciseShardingAlgorithm处理=和IN
2. 实现RangeShardingAlgorithm处理范围查询（可选但强烈建议）
分表算法类：com.gorgor.shardingjdbc.algorithm.CustomizeStandardShardingAlgorithm
单元测试：com.gorgor.shardingjdbc.StandardTest
分库算法示例：

### -------------------------------数据源配置-------------------------------------------------
# 指定对应的库
spring.shardingsphere.datasource.names=m0,m1

spring.shardingsphere.datasource.m0.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m0.url=jdbc:mysql://localhost:3306/shardingdb1?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m0.username=root
spring.shardingsphere.datasource.m0.password=root

spring.shardingsphere.datasource.m1.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m1.url=jdbc:mysql://localhost:3306/shardingdb2?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m1.username=root
spring.shardingsphere.datasource.m1.password=root
### -------------------------------数据源配置-------------------------------------------------

### --------------------------------分布式序列算法配置---------------------------------------------------------
# 指定分布式主键生成策略
spring.shardingsphere.rules.sharding.tables.course.key-generate-strategy.column=cid
spring.shardingsphere.rules.sharding.tables.course.key-generate-strategy.key-generator-name=alg_snowflake
# 雪花算法，生成Long类型主键。
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.type=SNOWFLAKE
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.worker-id=1
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.max-vibration-offset=8
### --------------------------------分布式序列算法配置---------------------------------------------------------


### --------------------------------------配置实际分片节点------------------------------------------------
spring.shardingsphere.rules.sharding.tables.course.actual-data-nodes=m$->{0..1}.course_$->{1..2}
### --------------------------------------配置实际分片节点------------------------------------------------

### ---------------------------standard 分库配置--------------------------------------------------------------
# 分库字段
spring.shardingsphere.rules.sharding.tables.course.database-strategy.standard.sharding-column=user_id
# 分库算法名称
spring.shardingsphere.rules.sharding.tables.course.database-strategy.standard.sharding-algorithm-name=db_standard_algorithm
# 分库算法
spring.shardingsphere.rules.sharding.sharding-algorithms.db_standard_algorithm.type=MOD
spring.shardingsphere.rules.sharding.sharding-algorithms.db_standard_algorithm.props.sharding-count=2
### ---------------------------standard 分库配置--------------------------------------------------------------


### ---------------------------standard 分表配置--------------------------------------------------------------
# 分表字段
spring.shardingsphere.rules.sharding.tables.course.table-strategy.standard.sharding-column=user_id
# 分表算法名称
spring.shardingsphere.rules.sharding.tables.course.table-strategy.standard.sharding-algorithm-name=table_standard_algorithm

# 算法类型配置
spring.shardingsphere.rules.sharding.sharding-algorithms.table_standard_algorithm.type=CLASS_BASED
# 策略类型参数
# 分表算法 --> 四种数据分片方式 INLINE|STANDARD|COMPLEX|HINT
# 自定义算法需要实现对应的接口
# STANDARD-> StandardShardingAlgorithm
# COMPLEX->ComplexKeysShardingAlgorithm
# HINT -> HintShardingAlgorithm
spring.shardingsphere.rules.sharding.sharding-algorithms.table_standard_algorithm.props.strategy = STANDARD
# 自定义算法类
spring.shardingsphere.rules.sharding.sharding-algorithms.table_standard_algorithm.props.algorithmClassName=com.gorgor.shardingjdbc.algorithm.CustomizeStandardShardingAlgorithm
### ---------------------------standard 分表配置--------------------------------------------------------------


spring.shardingsphere.rules.sharding.sharding-algorithms.table_standard_algorithm.props.sharding-count=2

3. 复合分片策略（Complex）

场景：多字段联合路由（如user_id+id）
分库算法类：com.gorgor.shardingjdbc.algorithm.CustomizeDbComplexKeysShardingAlgorithm

分表算法类：

com.gorgor.shardingjdbc.algorithm.CustomizeComplexKeysShardingAlgorithm

单元测试：com.gorgor.shardingjdbc.ComplexTest
算法实现：

### -------------------------------数据源配置-------------------------------------------------
# 指定对应的库
spring.shardingsphere.datasource.names=m0,m1

spring.shardingsphere.datasource.m0.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m0.url=jdbc:mysql://localhost:3306/shardingdb1?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m0.username=root
spring.shardingsphere.datasource.m0.password=root

spring.shardingsphere.datasource.m1.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m1.url=jdbc:mysql://localhost:3306/shardingdb2?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m1.username=root
spring.shardingsphere.datasource.m1.password=root
### -------------------------------数据源配置-------------------------------------------------

### --------------------------------分布式序列算法配置---------------------------------------------------------
# 指定分布式主键生成策
spring.shardingsphere.rules.sharding.tables.course.key-generate-strategy.column=cid
spring.shardingsphere.rules.sharding.tables.course.key-generate-strategy.key-generator-name=customize_snowflake

# 自定义分布式主键生成策略
spring.shardingsphere.rules.sharding.key-generators.customize_snowflake.type=MY_SNOWFLAKE
spring.shardingsphere.rules.sharding.key-generators.customize_snowflake.props.worker-id=1
spring.shardingsphere.rules.sharding.key-generators.customize_snowflake.props.max-vibration-offset=8
### --------------------------------分布式序列算法配置---------------------------------------------------------


### --------------------------------------配置实际分片节点------------------------------------------------
spring.shardingsphere.rules.sharding.tables.course.actual-data-nodes=m$->{0..1}.course_$->{1..2}
### --------------------------------------配置实际分片节点------------------------------------------------

### ---------------------------complex 分库配置--------------------------------------------------------------
# 分库字段
spring.shardingsphere.rules.sharding.tables.course.database-strategy.complex.sharding-columns=cid,user_id
# 分库算法名称
spring.shardingsphere.rules.sharding.tables.course.database-strategy.complex.sharding-algorithm-name=db_complex_algorithm
# 分库算法
#spring.shardingsphere.rules.sharding.sharding-algorithms.db_complex_algorithm.type=COMPLEX_INLINE
spring.shardingsphere.rules.sharding.sharding-algorithms.db_complex_algorithm.props.strategy = COMPLEX
#spring.shardingsphere.rules.sharding.sharding-algorithms.db_complex_algorithm.props.algorithm-expression=m$->{((cid ?: 0L).toLong() + (user_id ?: 0L).toLong()) % 2}

spring.shardingsphere.rules.sharding.sharding-algorithms.db_complex_algorithm.type=CLASS_BASED
spring.shardingsphere.rules.sharding.sharding-algorithms.db_complex_algorithm.props.algorithmClassName = com.gorgor.shardingjdbc.algorithm.CustomizeDbComplexKeysShardingAlgorithm

### ---------------------------complex 分库配置--------------------------------------------------------------


### ---------------------------complex 分表配置--------------------------------------------------------------
# 分表字段
spring.shardingsphere.rules.sharding.tables.course.table-strategy.complex.sharding-columns=cid,user_id
# 分表算法名称
spring.shardingsphere.rules.sharding.tables.course.table-strategy.complex.sharding-algorithm-name=table_complex_algorithm

# 算法类型配置
# 五种分片算法类型
#   1.MOD (取模分片)
#   2.HASH_MOD (哈希取模分片)
#   3.VOLUME_RANGE (基于数据容量的范围分片)
#   4.BOUNDARY_RANGE (基于边界值的范围分片)
#   5.AUTO_INTERVAL (自动时间间隔分片)
#   6.CLASS_BASED (自定义算法)
spring.shardingsphere.rules.sharding.sharding-algorithms.table_complex_algorithm.type=CLASS_BASED
# 策略类型参数
# 分表算法 --> 四种数据分片方式 INLINE|STANDARD|COMPLEX|HINT
# 自定义算法需要实现对应的接口
#   STANDARD-> StandardShardingAlgorithm
#   COMPLEX->ComplexKeysShardingAlgorithm
#   HINT -> HintShardingAlgorithm
spring.shardingsphere.rules.sharding.sharding-algorithms.table_complex_algorithm.props.strategy = COMPLEX
# 自定义算法类
spring.shardingsphere.rules.sharding.sharding-algorithms.table_complex_algorithm.props.algorithmClassName=com.gorgor.shardingjdbc.algorithm.CustomizeComplexKeysShardingAlgorithm
### ---------------------------complex 分表配置--------------------------------------------------------------


spring.shardingsphere.rules.sharding.sharding-algorithms.table_complex_algorithm.props.sharding-count=2

4. Hint强制分片策略

场景：
- 分片字段不在SQL中（如按外部业务ID路由）
- 跨分片数据迁移时手动指定目标库表
单元测试：com.gorgor.shardingjdbc.HintTest
示例配置：

### -------------------------------数据源配置-------------------------------------------------
spring.shardingsphere.datasource.names=m0,m1
spring.shardingsphere.datasource.m0.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m0.url=jdbc:mysql://localhost:3306/shardingdb1?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m0.username=root
spring.shardingsphere.datasource.m0.password=root
spring.shardingsphere.datasource.m1.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m1.url=jdbc:mysql://localhost:3306/shardingdb2?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m1.username=root
spring.shardingsphere.datasource.m1.password=root

### --------------------------------分布式序列算法配置-----------------------------------------
spring.shardingsphere.rules.sharding.tables.course.key-generate-strategy.column=cid
spring.shardingsphere.rules.sharding.tables.course.key-generate-strategy.key-generator-name=alg_snowflake
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.type=SNOWFLAKE
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.worker-id=1
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.max-vibration-offset=8

### --------------------------------------配置实际分片节点------------------------------------
# 修正：明确指定分片范围
spring.shardingsphere.rules.sharding.tables.course.actual-data-nodes=m$->{0..1}.course_$->{1..2}

### ---------------------------hint 分库配置------------------------------------------------
spring.shardingsphere.rules.sharding.tables.course.database-strategy.hint.sharding-algorithm-name=db_hint_algorithm
spring.shardingsphere.rules.sharding.sharding-algorithms.db_hint_algorithm.type=HINT_INLINE
# 修正：确保value是整数类型
spring.shardingsphere.rules.sharding.sharding-algorithms.db_hint_algorithm.props.algorithm-expression=m$->{value}

### ---------------------------hint 分表配置------------------------------------------------
spring.shardingsphere.rules.sharding.tables.course.table-strategy.hint.sharding-algorithm-name=table_hint_algorithm
spring.shardingsphere.rules.sharding.sharding-algorithms.table_hint_algorithm.type=HINT_INLINE
# 修正：添加后缀处理
spring.shardingsphere.rules.sharding.sharding-algorithms.table_hint_algorithm.props.algorithm-expression=course_$->{value}

五、基于ShardingJDBC实现读写分离

ShardingJDBC的读写分离功能通过透明化路由将写操作指向主库、读操作分散到从库，有效提升数据库吞吐量。以下是完整实现方案：

1. 核心架构原理

2. 配置数据源

### -------------------------------数据源配置-------------------------------------------------
spring.shardingsphere.datasource.names=m0,m1
spring.shardingsphere.datasource.m0.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m0.url=jdbc:mysql://localhost:3306/shardingdb1?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m0.username=root
spring.shardingsphere.datasource.m0.password=root
spring.shardingsphere.datasource.m1.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m1.url=jdbc:mysql://localhost:3306/shardingdb2?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m1.username=root
spring.shardingsphere.datasource.m1.password=root

### --------------------------------分布式序列算法配置-----------------------------------------
spring.shardingsphere.rules.sharding.tables.user.key-generate-strategy.column=userid
spring.shardingsphere.rules.sharding.tables.user.key-generate-strategy.key-generator-name=alg_snowflake
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.type=SNOWFLAKE
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.worker-id=1
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.max-vibration-offset=8
### --------------------------------分布式序列算法配置-----------------------------------------


###-----------------------配置读写分离--------------------------------------------------------------------
# 要配置成读写分离的虚拟库
spring.shardingsphere.rules.sharding.tables.user.actual-data-nodes=userdb.user
# 配置读写分离虚拟库 主库一个，从库多个
spring.shardingsphere.rules.readwrite-splitting.data-sources.userdb.static-strategy.write-data-source-name=m0
spring.shardingsphere.rules.readwrite-splitting.data-sources.userdb.static-strategy.read-data-source-names[0]=m1
# 指定负载均衡器
spring.shardingsphere.rules.readwrite-splitting.data-sources.userdb.load-balancer-name=user_lb
# 配置负载均衡器
# 按操作轮训
spring.shardingsphere.rules.readwrite-splitting.load-balancers.user_lb.type=ROUND_ROBIN
# 按事务轮训
#spring.shardingsphere.rules.readwrite-splitting.load-balancers.user_lb.type=TRANSACTION_ROUND_ROBIN
# 按操作随机
#spring.shardingsphere.rules.readwrite-splitting.load-balancers.user_lb.type=RANDOM
# 按事务随机
#spring.shardingsphere.rules.readwrite-splitting.load-balancers.user_lb.type=TRANSACTION_RANDOM
# 读请求全部强制路由到主库
#spring.shardingsphere.rules.readwrite-splitting.load-balancers.user_lb.type=FIXED_PRIMARY

3. 单元测试

单元测试类：com.gorgor.shardingjdbc.ReadwriteSplittingTest

六、广播表

广播表是 ShardingSphere 分库分表架构中的全局数据同步方案，用于解决分布式环境下跨分片数据一致性与高效关联查询的问题。以下是其核心原理、应用场景及实战配置详解：

1. 广播表核心特性

特性	说明
数据全冗余	广播表数据在所有物理分片库中均存储完整副本
写操作同步	执行`INSERT/UPDATE/DELETE`时，操作自动广播到所有分片库
读操作本地化	查询广播表时，直接读取当前分片副本，避免跨库网络开销
强一致性	通过分布式事务（如 XA）保证所有分片数据一致（需事务支持）

2. yml 配置

### -------------------------------数据源配置-------------------------------------------------
spring.shardingsphere.datasource.names=m0,m1
spring.shardingsphere.datasource.m0.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m0.url=jdbc:mysql://localhost:3306/shardingdb1?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m0.username=root
spring.shardingsphere.datasource.m0.password=root
spring.shardingsphere.datasource.m1.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m1.url=jdbc:mysql://localhost:3306/shardingdb2?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m1.username=root
spring.shardingsphere.datasource.m1.password=root

### --------------------------------分布式序列算法配置-----------------------------------------
spring.shardingsphere.rules.sharding.tables.dict.key-generate-strategy.column=dictId
spring.shardingsphere.rules.sharding.tables.dict.key-generate-strategy.key-generator-name=alg_snowflake
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.type=SNOWFLAKE
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.worker-id=1
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.max-vibration-offset=8


### 广播表
spring.shardingsphere.rules.sharding.broadcast-tables=dict

3. 应用场景

字典表
配置表

4. 单元测试

单元测试类：com.gorgor.shardingjdbc.BroadcastTablesTest

七、绑定表

绑定表是 ShardingSphere 解决跨分片表关联查询性能问题的核心机制，通过相同分片规则将逻辑关联的表物理存储在相同分片，避免跨库笛卡尔积查询。以下是深度解析与实战指南：

1. 绑定表核心价值

场景	未绑定	绑定后
2表JOIN查询	产生 `M×N` 次查询（M=订单表分片数, N=明细表分片数）	仅产生 `1` 次查询（同组分片内执行）
SQL执行效率	全分片广播 + 内存归并（性能灾难）	单分片本地JOIN（毫秒级响应）
网络开销	高（跨节点传输大量中间数据）	零（节点内完成）

📌 典型场景：订单表（order）与订单明细表（order_item）按相同分片键（order_id）分片

2. 工作原理图解

3. yml 配置

### -------------------------------数据源配置-------------------------------------------------
spring.shardingsphere.datasource.names=m0,m1
spring.shardingsphere.datasource.m0.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m0.url=jdbc:mysql://localhost:3306/shardingdb1?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m0.username=root
spring.shardingsphere.datasource.m0.password=root
spring.shardingsphere.datasource.m1.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m1.url=jdbc:mysql://localhost:3306/shardingdb2?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m1.username=root
spring.shardingsphere.datasource.m1.password=root

### --------------------------------分布式序列算法配置-----------------------------------------
spring.shardingsphere.rules.sharding.tables.user_course_info.key-generate-strategy.column=infoid
spring.shardingsphere.rules.sharding.tables.user_course_info.key-generate-strategy.key-generator-name=alg_snowflake
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.type=SNOWFLAKE
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.worker-id=1
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.max-vibration-offset=8


### --------------------------------------配置实际分片节点------------------------------------------------
spring.shardingsphere.rules.sharding.tables.user.actual-data-nodes=m$->{0..1}.user_$->{1..2}
spring.shardingsphere.rules.sharding.tables.user_course_info.actual-data-nodes=m$->{0..1}.user_course_info_$->{1..2}
### --------------------------------------配置实际分片节点------------------------------------------------

### ---------------------------inline 分库配置--------------------------------------------------------------
# 分库字段
spring.shardingsphere.rules.sharding.tables.user.database-strategy.standard.sharding-column=userid
# 分库算法名称
spring.shardingsphere.rules.sharding.tables.user.database-strategy.standard.sharding-algorithm-name=db_user_inline_algorithm
# 分库算法
spring.shardingsphere.rules.sharding.sharding-algorithms.db_user_inline_algorithm.type=HASH_MOD
spring.shardingsphere.rules.sharding.sharding-algorithms.db_user_inline_algorithm.props.sharding-count=2


# 分库字段
spring.shardingsphere.rules.sharding.tables.user_course_info.database-strategy.standard.sharding-column=userid
# 分库算法名称
spring.shardingsphere.rules.sharding.tables.user_course_info.database-strategy.standard.sharding-algorithm-name=db_user_course_info_inline_algorithm
# 分库算法
spring.shardingsphere.rules.sharding.sharding-algorithms.db_user_course_info_inline_algorithm.type=HASH_MOD
spring.shardingsphere.rules.sharding.sharding-algorithms.db_user_course_info_inline_algorithm.props.sharding-count=2

### ---------------------------inline 分库配置--------------------------------------------------------------



### ---------------------------inline 分表配置--------------------------------------------------------------
spring.shardingsphere.rules.sharding.tables.user.table-strategy.standard.sharding-column=userid
spring.shardingsphere.rules.sharding.tables.user.table-strategy.standard.sharding-algorithm-name=user_tbl_alg

spring.shardingsphere.rules.sharding.tables.user_course_info.table-strategy.standard.sharding-column=userid
spring.shardingsphere.rules.sharding.tables.user_course_info.table-strategy.standard.sharding-algorithm-name=usercourse_tbl_alg
# ----------------------配置分表策略
spring.shardingsphere.rules.sharding.sharding-algorithms.user_tbl_alg.type=INLINE
spring.shardingsphere.rules.sharding.sharding-algorithms.user_tbl_alg.props.algorithm-expression=user_$->{Math.abs(userid.hashCode()%4).intdiv(2) +1}

spring.shardingsphere.rules.sharding.sharding-algorithms.usercourse_tbl_alg.type=INLINE
spring.shardingsphere.rules.sharding.sharding-algorithms.usercourse_tbl_alg.props.algorithm-expression=user_course_info_$->{Math.abs(userid.hashCode()%4).intdiv(2) +1}

### ---------------------------inline 分表配置--------------------------------------------------------------


### 指定绑定表
spring.shardingsphere.rules.sharding.binding-tables[0]=user,user_course_info

4. 单元测试

单元测试类：com.gorgor.shardingjdbc.BindingTablesTest

5. 绑定表 vs 广播表

维度	绑定表	广播表
数据分布	分片存储（不同分片存不同数据）	全量冗余（所有分片存相同数据）
适用表	大表（订单/交易记录）	小表（地区/配置）
存储成本	低（数据水平拆分）	高（全量复制 * 分片数）
JOIN效率	高（同分片本地JOIN）	极高（任意节点本地JOIN）
写入性能	高（仅写目标分片）	差（需写所有分片）

八、分⽚审计

分⽚审计功能是针对数据库分⽚场景下对执⾏的 SQL 语句进⾏审计操作。分⽚审计既可以进⾏拦截操作，拦截系统配置的⾮法 SQL 语句，也可以是对 SQL 语句进⾏统计操作。

⽬前ShardingSphere内置的分⽚审计算法只有⼀个，DML_SHARDING_CONDITIONS。他的功能是要求对逻辑表查询时，必须带上分⽚键。

1. yml 配置

### -------------------------------数据源配置-------------------------------------------------
# 指定对应的库
spring.shardingsphere.datasource.names=m0,m1

spring.shardingsphere.datasource.m0.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m0.url=jdbc:mysql://localhost:3306/shardingdb1?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m0.username=root
spring.shardingsphere.datasource.m0.password=root

spring.shardingsphere.datasource.m1.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m1.url=jdbc:mysql://localhost:3306/shardingdb2?serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m1.username=root
spring.shardingsphere.datasource.m1.password=root
### -------------------------------数据源配置-------------------------------------------------

### --------------------------------分布式序列算法配置---------------------------------------------------------
# 指定分布式主键生成策略
spring.shardingsphere.rules.sharding.tables.course.key-generate-strategy.column=cid
spring.shardingsphere.rules.sharding.tables.course.key-generate-strategy.key-generator-name=alg_snowflake
# 雪花算法，生成Long类型主键。
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.type=SNOWFLAKE
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.worker-id=1
spring.shardingsphere.rules.sharding.key-generators.alg_snowflake.props.max-vibration-offset=8
### --------------------------------分布式序列算法配置---------------------------------------------------------


### --------------------------------------配置实际分片节点------------------------------------------------
spring.shardingsphere.rules.sharding.tables.course.actual-data-nodes=m$->{0..1}.course_$->{1..2}
### --------------------------------------配置实际分片节点------------------------------------------------

### ---------------------------standard 分库配置--------------------------------------------------------------
# 分库字段
spring.shardingsphere.rules.sharding.tables.course.database-strategy.standard.sharding-column=user_id
# 分库算法名称
spring.shardingsphere.rules.sharding.tables.course.database-strategy.standard.sharding-algorithm-name=db_standard_algorithm
# 分库算法
spring.shardingsphere.rules.sharding.sharding-algorithms.db_standard_algorithm.type=MOD
spring.shardingsphere.rules.sharding.sharding-algorithms.db_standard_algorithm.props.sharding-count=2
### ---------------------------standard 分库配置--------------------------------------------------------------


### ---------------------------standard 分表配置--------------------------------------------------------------
# 分表字段
spring.shardingsphere.rules.sharding.tables.course.table-strategy.standard.sharding-column=user_id
# 分表算法名称
spring.shardingsphere.rules.sharding.tables.course.table-strategy.standard.sharding-algorithm-name=table_standard_algorithm

# 算法类型配置
spring.shardingsphere.rules.sharding.sharding-algorithms.table_standard_algorithm.type=CLASS_BASED
# 策略类型参数
# 分表算法 --> 四种数据分片方式 INLINE|STANDARD|COMPLEX|HINT
# 自定义算法需要实现对应的接口
# STANDARD-> StandardShardingAlgorithm
# COMPLEX->ComplexKeysShardingAlgorithm
# HINT -> HintShardingAlgorithm
spring.shardingsphere.rules.sharding.sharding-algorithms.table_standard_algorithm.props.strategy = STANDARD
# 自定义算法类
spring.shardingsphere.rules.sharding.sharding-algorithms.table_standard_algorithm.props.algorithmClassName=com.gorgor.shardingjdbc.algorithm.CustomizeStandardShardingAlgorithm
### ---------------------------standard 分表配置--------------------------------------------------------------


spring.shardingsphere.rules.sharding.sharding-algorithms.table_standard_algorithm.props.sharding-count=2

### ---------------------------分片审计 分表配置--------------------------------------------------------------
# 分片审计规则： SQL查询必须带上分片键
spring.shardingsphere.rules.sharding.tables.course.audit-strategy.auditor-names[0]=course_auditor
spring.shardingsphere.rules.sharding.tables.course.audit-strategy.allow-hint-disable=true

spring.shardingsphere.rules.sharding.auditors.course_auditor.type=DML_SHARDING_CONDITIONS
### ---------------------------分片审计 分表配置--------------------------------------------------------------

2. 单元测试

单元测试类：com.gorgor.shardingjdbc.AuditorTest

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