springboot sharding-jdbc分库分表

Sharding jdbc 分库分表

​ 一共有三个库，m(mian),ds0,ds1,其中m库是不分库分表的，ds0，ds1是走分库分表的，每个库三张表，也就是2库6表

数据库结构

├─192.168.43.200
│  ├─dsm
│  │  └─leader
│  ├─ds0
│  │  └─order_000
│  │  └─order_001
│  │  └─order_002
│  ├─ds1
│  │  └─order_000
│  │  └─order_001
│  │  └─order_002
│  │  │  

依赖

pom.xml

<dependency>
    <groupId>io.shardingsphere</groupId>
    <artifactId>sharding-jdbc-spring-boot-starter</artifactId>
    <version>3.0.0.M3</version>
</dependency>
<dependency>
    <groupId>com.alibaba</groupId>
    <artifactId>druid</artifactId>
    <version>1.1.22</version>
</dependency>

如果启动有冲突，配置文件加这个

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

行表达式分片策略

​ 对应InlineShardingStrategy。使用Groovy的表达式，提供对SQL语句中的=和IN的分片操作支持，只支持单分片键。对于简单的分片算法，可以通过简单的配置使用，从而避免繁琐的Java代码开发，如: t_order_000$->{order_id % 3} 表示t_order_000表根据order_id 模3，而分成3张表，表名称为t_order_0000到t_order_0002。

只需要编写配置文件即可

###########################Sharding Jdbc配置###########################

sharding.jdbc.datasource.names=m,ds0,ds1

sharding.jdbc.datasource.m.type=com.alibaba.druid.pool.DruidDataSource
sharding.jdbc.datasource.m.driver-class-name=com.mysql.jdbc.Driver
sharding.jdbc.datasource.m.url=jdbc:mysql://192.168.79.131:3306/grp_leader
sharding.jdbc.datasource.m.username=root
sharding.jdbc.datasource.m.password=123456

sharding.jdbc.datasource.ds0.type=com.alibaba.druid.pool.DruidDataSource
sharding.jdbc.datasource.ds0.driver-class-name=com.mysql.jdbc.Driver
sharding.jdbc.datasource.ds0.url=jdbc:mysql://192.168.79.131:3306/grp_manage_01
sharding.jdbc.datasource.ds0.username=root
sharding.jdbc.datasource.ds0.password=123456

sharding.jdbc.datasource.ds1.type=com.alibaba.druid.pool.DruidDataSource
sharding.jdbc.datasource.ds1.driver-class-name=com.mysql.jdbc.Driver
sharding.jdbc.datasource.ds1.url=jdbc:mysql://192.168.79.131:3306/grp_manage_02
sharding.jdbc.datasource.ds1.username=root
sharding.jdbc.datasource.ds1.password=123456

sharding.jdbc.config.sharding.default-database-strategy.inline.sharding-column=order_id
sharding.jdbc.config.sharding.default-database-strategy.inline.algorithm-expression=ds$->{order_id % 2}


sharding.jdbc.config.sharding.tables.t_order.actual-data-nodes=ds$->{0..1}.t_order_000$->{0..1}
sharding.jdbc.config.sharding.tables.t_order.table-strategy.inline.sharding-column=order_id
sharding.jdbc.config.sharding.tables.t_order.table-strategy.inline.algorithm-expression=t_order_000$->{order_id % 3}

sharding.jdbc.config.sharding.tables.leader.actual-data-nodes=m.leader
sharding.jdbc.config.sharding.tables.leader.table-strategy.inline.sharding-column=id
sharding.jdbc.config.sharding.tables.leader.table-strategy.inline.algorithm-expression=leader

sharding.jdbc.config.sharding.props.sql.show=true

标准分片策略

​ 对应StandardShardingStrategy。提供对SQL语句中的=, >, <, >=, <=, IN和BETWEEN AND的分片操作支持。StandardShardingStrategy只支持单分片键，提供PreciseShardingAlgorithm和RangeShardingAlgorithm两个分片算法。PreciseShardingAlgorithm是必选的，用于处理=和IN的分片。RangeShardingAlgorithm是可选的，用于处理BETWEEN AND, >, <, >=, <=分片，如果不配置RangeShardingAlgorithm，SQL中的BETWEEN AND将按照全库路由处理。

PreciseShardingAlgorithm

自定义精准分库分表策略

这里分库分表都是取mod运算 和上面的行表达式分片策略一样（分库分表可以设置两个策略）

/**
 * sharding jdbc 精准 `分库` 策略
 * */
@Slf4j
public class PreciseShardingDatabaseAlgorithm implements PreciseShardingAlgorithm<Long> {
    
    

    /**
     * @param collection 拆分的所有库名 比如 [ds0,ds1]
     * @param preciseShardingValue database-strategy.standard.sharding-column
     * */
    @Override
    public String doSharding(Collection<String> collection, PreciseShardingValue<Long> preciseShardingValue) {
    
    

        log.info("[Database PreciseShardingAlgorithm] collection:{} ,preciseShardingValue: {}",
                JSON.toJSONString(collection),JSON.toJSONString(preciseShardingValue));
        for (String name : collection) {
    
    
            // 分库的规则
            if (name.endsWith(preciseShardingValue.getValue() % collection.size() + "")) {
    
    
                log.info("[Database PreciseShardingAlgorithm ] return database name:{}",name);
                return name;
            }
        }
        throw new UnsupportedOperationException();
    }
}

/**
 * sharding jdbc 精准`分表`策略
 * */
@Slf4j
public class PreciseShardingTableAlgorithm implements PreciseShardingAlgorithm<Long> {
    
    

    /**
     * @param collection 拆分的所有表 比如 [t_order0000,t_order0001,t_order0002]
     * @param preciseShardingValue table-strategy.standard.sharding-column
     * */
    @Override
    public String doSharding(Collection<String> collection, PreciseShardingValue<Long> preciseShardingValue) {
    
    

        log.info("[Table PreciseShardingAlgorithm ] collection:{} ,preciseShardingValue: {}",
                JSON.toJSONString(collection),JSON.toJSONString(preciseShardingValue));
        for (String name : collection) {
    
    
            // 分表的规则
            if (name.endsWith(preciseShardingValue.getValue() % collection.size() + "")) {
    
    
                log.info("[Table PreciseShardingAlgorithm ] return table name:{}",name);
                return name;
            }
        }
        throw new UnsupportedOperationException();
    }
}

配置文件

###########################Sharding Jdbc配置###########################

sharding.jdbc.datasource.names=m,ds0,ds1

sharding.jdbc.datasource.m.type=com.alibaba.druid.pool.DruidDataSource
sharding.jdbc.datasource.m.driver-class-name=com.mysql.jdbc.Driver
sharding.jdbc.datasource.m.url=jdbc:mysql://192.168.79.131:3306/grp_leader
sharding.jdbc.datasource.m.username=root
sharding.jdbc.datasource.m.password=123456
sharding.jdbc.datasource.m.initialSize=${initialSize}
sharding.jdbc.datasource.m.minIdle=${minIdle}
sharding.jdbc.datasource.m.maxActive=${maxActive}
sharding.jdbc.datasource.m.maxWait=${maxWait}
sharding.jdbc.datasource.m.validationQuery=SELECT 1 FROM DUAL
sharding.jdbc.datasource.m.timeBetweenEvictionRunsMillis=${timeBetweenEvictionRunsMillis}
sharding.jdbc.datasource.m.minEvictableIdleTimeMillis=${minEvictableIdleTimeMillis}

sharding.jdbc.datasource.ds0.type=com.alibaba.druid.pool.DruidDataSource
sharding.jdbc.datasource.ds0.driver-class-name=com.mysql.jdbc.Driver
sharding.jdbc.datasource.ds0.url=jdbc:mysql://192.168.79.131:3306/grp_manage_01
sharding.jdbc.datasource.ds0.username=root
sharding.jdbc.datasource.ds0.password=123456
sharding.jdbc.datasource.ds0.initialSize=${initialSize}
sharding.jdbc.datasource.ds0.minIdle=${minIdle}
sharding.jdbc.datasource.ds0.maxActive=${maxActive}
sharding.jdbc.datasource.ds0.maxWait=${maxWait}
sharding.jdbc.datasource.ds0.validationQuery=SELECT 1 FROM DUAL
sharding.jdbc.datasource.ds0.timeBetweenEvictionRunsMillis=${timeBetweenEvictionRunsMillis}
sharding.jdbc.datasource.ds0.minEvictableIdleTimeMillis=${minEvictableIdleTimeMillis}

sharding.jdbc.datasource.ds1.type=com.alibaba.druid.pool.DruidDataSource
sharding.jdbc.datasource.ds1.driver-class-name=com.mysql.jdbc.Driver
sharding.jdbc.datasource.ds1.url=jdbc:mysql://192.168.79.131:3306/grp_manage_02
sharding.jdbc.datasource.ds1.username=root
sharding.jdbc.datasource.ds1.password=123456
sharding.jdbc.datasource.ds1.initialSize=${initialSize}
sharding.jdbc.datasource.ds1.minIdle=${minIdle}
sharding.jdbc.datasource.ds1.maxActive=${maxActive}
sharding.jdbc.datasource.ds1.maxWait=${maxWait}
sharding.jdbc.datasource.ds1.validationQuery=SELECT 1 FROM DUAL
sharding.jdbc.datasource.ds1.timeBetweenEvictionRunsMillis=${timeBetweenEvictionRunsMillis}
sharding.jdbc.datasource.ds1.minEvictableIdleTimeMillis=${minEvictableIdleTimeMillis}


#分库配置
sharding.jdbc.config.sharding.default-database-strategy.standard.sharding-column=order_id
sharding.jdbc.config.sharding.default-database-strategy.standard.precise-algorithm-class-name=cn.hujinbo.sharding.config.database.PreciseShardingDatabaseAlgorithm

sharding.jdbc.config.sharding.tables.t_order.actual-data-nodes=ds$->{0..1}.t_order_000$->{0..2}
sharding.jdbc.config.sharding.tables.t_order.table-strategy.standard.sharding-column=order_id
sharding.jdbc.config.sharding.tables.t_order.table-strategy.standard.precise-algorithm-class-name=cn.hujinbo.sharding.config.database.PreciseShardingTableAlgorithm


sharding.jdbc.config.sharding.tables.leader.actual-data-nodes=m.leader
sharding.jdbc.config.sharding.tables.leader.table-strategy.inline.sharding-column=id
sharding.jdbc.config.sharding.tables.leader.table-strategy.inline.algorithm-expression=leader

sharding.jdbc.config.sharding.props.sql.show=true

RangeShardingAlgorithm

项目地址

springboot-sharding-jdbc

文档

• sharding-jdbc多表查询示例

参考文章

• sharding-jdbc官方文档（中文）

• 【分库分表】sharding-jdbc—分片策略

• Sharding JDBC(四) 分片策略一：标准分片策略StandardShardingStrategy