一、簡介
Sharding-jdbc官網:http://shardingsphere.apache.org/
1.概述
a、Sharding-jdbc是一個開源的分布式的關系型資料庫中間件
b、Sharding-jdbc是用戶端代理模式
c、定位為輕量級的Java架構,以jar包提供服務;可以了解為增強版的jdbc驅動
d、完全相容各種ORM架構,如Mybatis等
架構圖:
![](https://img.laitimes.com/img/__Qf2AjLwojIjJCLyojI0JCLiAzNfRHLGZkRGZkRfJ3bs92YsYTMfVmepNHL5tmeOl3Zq1UeRpHW4Z0MMBjVtJWd0ckW65UbM5WOHJWa5kHT20ESjBjUIF2X0hXZ0xCMx81dvRWYoNHLrdEZwZ1Rh5WNXp1bwNjW1ZUba9VZwlHdssmch1mclRXY39CXldWYtlWPzNXZj9mcw1ycz9WL49zZuBnL5ITM3EjNxYTMwETMwEjMwIzLc52YucWbp5GZzNmLn9Gbi1yZtl2Lc9CX6MHc0RHaiojIsJye.png)
2.與Mycat之間的差别
a、Mycat是服務端代理,sharding-jdbc是用戶端代理
b、MyCat不支援同一庫内的水準切分,Sharding-jdbc支援
二、使用
準備:使用前先準備兩台Mysql資料庫,作為分片節點
本項目使用的兩台資料庫節點分别為131和132
1.建立一個spring boot項目
a、通過idea建立一個springboot項目
b、通過Maven引入依賴
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-jpa</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.mybatis.spring.boot</groupId>
<artifactId>mybatis-spring-boot-starter</artifactId>
<version>2.1.0</version>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<optional>true</optional>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
<!--sharding-jdbc for spring -->
<!--<dependency>-->
<!--<groupId>org.apache.shardingsphere</groupId>-->
<!--<artifactId>sharding-jdbc-spring-namespace</artifactId>-->
<!--<version>4.0.0-RC2</version>-->
<!--</dependency>-->
<!--sharding-jdbc for springboot -->
<dependency>
<groupId>org.apache.shardingsphere</groupId>
<artifactId>sharding-jdbc-spring-boot-starter</artifactId>
<version>4.0.0-RC2</version>
</dependency>
</dependencies>
2.配置Sharding-jdbc
注意: a、Sharding-jdbc的配置在spring和springboot項目中是不同的
b、同時,在spring項目和spring-boot項目中,jar的引入方式也是不同的,請注意maven中sharding-jdbc的依賴包的引入方式
(1)第一種方式,使用spring名稱空間的方式進行配置
a、建立sharding-jdbc.xml檔案
檔案位置:
檔案内容:
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:p="http://www.springframework.org/schema/p"
xmlns:context="http://www.springframework.org/schema/context"
xmlns:tx="http://www.springframework.org/schema/tx"
xmlns:sharding="http://shardingsphere.apache.org/schema/shardingsphere/sharding"
xmlns:master-slave="http://shardingsphere.apache.org/schema/shardingsphere/masterslave"
xmlns:bean="http://www.springframework.org/schema/util"
xsi:schemaLocation="http://www.springframework.org/schema/beans
http://www.springframework.org/schema/beans/spring-beans.xsd
http://shardingsphere.apache.org/schema/shardingsphere/sharding
http://shardingsphere.apache.org/schema/shardingsphere/sharding/sharding.xsd
http://shardingsphere.apache.org/schema/shardingsphere/masterslave
http://shardingsphere.apache.org/schema/shardingsphere/masterslave/master-slave.xsd
http://www.springframework.org/schema/context
http://www.springframework.org/schema/context/spring-context.xsd
http://www.springframework.org/schema/tx
http://www.springframework.org/schema/tx/spring-tx.xsd http://www.springframework.org/schema/util https://www.springframework.org/schema/util/spring-util.xsd">
<!--第一個資料源 主-->
<bean name="ds0" class="com.zaxxer.hikari.HikariDataSource" destroy-method="close" >
<property name="driverClassName" value="com.mysql.cj.jdbc.Driver"/>
<property name="username" value="root"/>
<property name="password" value="root" />
<property name="jdbcUrl" value="jdbc:mysql://192.168.73.131/sharding_order?serverTimezone=Asia/Shanghai&useSSL=false"/>
</bean>
<!--第一個資料源 從-->
<bean id="slave0" class="com.zaxxer.hikari.HikariDataSource" destroy-method="close">
<property name="driverClassName" value="com.mysql.cj.jdbc.Driver" />
<property name="username" value="root" />
<property name="password" value="root" />
<property name="jdbcUrl" value="jdbc:mysql://192.168.73.130/sharding_order?serverTimezone=Asia/Shanghai&useSSL=false"/>
</bean>
<!--第二個資料源-->
<bean id="ms1" class="com.zaxxer.hikari.HikariDataSource" destroy-method="close">
<property name="driverClassName" value="com.mysql.cj.jdbc.Driver" />
<property name="username" value="root" />
<property name="password" value="root" />
<property name="jdbcUrl" value="jdbc:mysql://192.168.73.132/sharding_order?serverTimezone=Asia/Shanghai&useSSL=false"/>
</bean>
<!--主從之間的負載均衡政策-->
<master-slave:load-balance-algorithm id="msStrategy" type="RANDOM"/>
<sharding:data-source id="sharding-data-source">
<!--
data-source-names: 該規則表示針對哪幾個資料源;
-->
<sharding:sharding-rule data-source-names="ds0,slave0,ms1" default-data-source-name="ms0">
<!--主從關系,在這裡主從共同建構成為一個一體的資料源-->
<sharding:master-slave-rules>
<sharding:master-slave-rule id="ms0" master-data-source-name="ds0" slave-data-source-names="slave0"
strategy-ref="msStrategy" />
</sharding:master-slave-rules>
<!--針對表的規則-->
<sharding:table-rules>
<!--
logic-table: sharding-jdbc 中的邏輯表
actual-data-nodes: 真實的資料節點,内容格式:庫名.表名
$->:占位符,相當于spring中的${}
database-strategy-ref:資料庫的分片政策
table-strategy-ref: 表的分片政策
-->
<sharding:table-rule logic-table="t_order" actual-data-nodes="ms$->{0..1}.t_order_$->{1..2}"
database-strategy-ref="databaseStrategy" table-strategy-ref="tableStrategy"
key-generator-ref="uuid" />
<sharding:table-rule logic-table="t_order_item" actual-data-nodes="ms$->{0..1}.t_order_item_$->{1..2}"
database-strategy-ref="databaseStrategy" table-strategy-ref="tableOrderItemStrategy"
key-generator-ref="uuid" />
</sharding:table-rules>
<!--全局表配置-->
<sharding:broadcast-table-rules>
<sharding:broadcast-table-rule table="area"/>
</sharding:broadcast-table-rules>
<!--子表(綁定表) 在4.0.0-RC2 這個版本中,存在bug,綁定表無法使用,若要使用請關注sharding-jdbc的更新-->
<sharding:binding-table-rules>
<!--
父表:t_order order_id(主鍵,且同一個庫中,使用該字段進行分别); user_id,入庫時,使用user_id進行分庫
子表:t_order_item 關聯字段:order_id(t_order的主鍵),user_id,入庫時使用該字段判斷父表所在的庫
注意:sharding-jdbc不能指定綁定字段,是以,子表和父表必須要有相同的字段,并以該字段作為關聯字段-->
<sharding:binding-table-rule logic-tables="t_order,t_order_item"/>
</sharding:binding-table-rules>
</sharding:sharding-rule>
</sharding:data-source>
<!--key 生成政策-->
<sharding:key-generator id="uuid" column="order_id" type="UUID"/>
<!--<sharding:key-generator id="snowflake" column="order_id" type="SNOWFLAKE" props-ref="snow"/>-->
<!--<bean:properties id="snow">-->
<!--<prop key="worker.id">678</prop>-->
<!--<prop key="max.tolerate.time.difference.milliseconds">10</prop>-->
<!--</bean:properties>-->
<!--
sharding-column: 分片列
algorithm-expression:表達式
-->
<sharding:inline-strategy id="databaseStrategy" sharding-column="user_id"
algorithm-expression="ms$->{user_id % 2}"/>
<!--分表政策-->
<!--<sharding:inline-strategy id="tableStrategy" sharding-column="order_id"-->
<!--algorithm-expression="t_order_$->{order_id % 2 + 1}"/>-->
<sharding:standard-strategy id="tableStrategy"
sharding-column="order_id"
precise-algorithm-ref="myShard"/>
<bean id="myShard" class="com.example.shardingjdbcdemo.sharding.MySharding"/>
<!--<sharding:inline-strategy id="tableOrderItemStrategy" sharding-column="order_id"-->
<!--algorithm-expression="t_order_item_$->{order_id % 2 + 1}"/>-->
<sharding:standard-strategy id="tableOrderItemStrategy"
sharding-column="order_id"
precise-algorithm-ref="myShard"/>
<!--接下來配置spring的SqlSessionFactory-->
<bean class="org.mybatis.spring.SqlSessionFactoryBean">
<property name="dataSource" ref="sharding-data-source"/>
<property name="mapperLocations" value="classpath*:/mybatis/*.xml"/>
</bean>
<!--注意:以上配置完成後,請檢查mapper中被分片的表的表名,不要使用實際表明,需要使用sharding:data-source配置的邏輯表名-->
</beans>
b、springBoot中引入該配置檔案
c.整體項目結構
d、自定義的分片表達式處理類
package com.example.shardingjdbcdemo.sharding;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingValue;
import java.util.Collection;
/**
* 自定義的處理分片表達式的類
* 本次用例中,需要處理order_id 的分片規則
* order_id 做為庫内分片的字段,它既是t_order表的主鍵,同時也是子表t_order_item中的字段
* order_id 使用了全局唯一主鍵 UUID
*/
public class MySharding implements PreciseShardingAlgorithm<String> {
@Override
public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<String> shardingValue) {
String id = shardingValue.getValue();
int mode = id.hashCode() % availableTargetNames.size();
String[] strings = availableTargetNames.toArray(new String[0]);
//取絕對值
mode = Math.abs(mode);
System.out.println(strings[0]+"---------"+strings[1]);
System.out.println("mode="+mode);
return strings[mode];
}
}
e.分布式id解決方案之雪花算法
概述:
snowFlake 時Twitter提出的分布式ID算法
一個64bit的long型數字
引入了時間戳,保持自增
基本概念
基本保持全局唯一,毫秒内并發最大4096個ID
時間回調可能會引起ID重複
可設定最大容忍回調時間
應用
配置:
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:p="http://www.springframework.org/schema/p"
xmlns:context="http://www.springframework.org/schema/context"
xmlns:tx="http://www.springframework.org/schema/tx"
xmlns:sharding="http://shardingsphere.apache.org/schema/shardingsphere/sharding"
xmlns:master-slave="http://shardingsphere.apache.org/schema/shardingsphere/masterslave"
xmlns:bean="http://www.springframework.org/schema/util"
xsi:schemaLocation="http://www.springframework.org/schema/beans
http://www.springframework.org/schema/beans/spring-beans.xsd
http://shardingsphere.apache.org/schema/shardingsphere/sharding
http://shardingsphere.apache.org/schema/shardingsphere/sharding/sharding.xsd
http://shardingsphere.apache.org/schema/shardingsphere/masterslave
http://shardingsphere.apache.org/schema/shardingsphere/masterslave/master-slave.xsd
http://www.springframework.org/schema/context
http://www.springframework.org/schema/context/spring-context.xsd
http://www.springframework.org/schema/tx
http://www.springframework.org/schema/tx/spring-tx.xsd http://www.springframework.org/schema/util https://www.springframework.org/schema/util/spring-util.xsd">
<bean id="ds0" class="com.zaxxer.hikari.HikariDataSource" destroy-method="close">
<property name="driverClassName" value="com.mysql.cj.jdbc.Driver" />
<property name="username" value="imooc" />
<property name="password" value="[email protected]" />
<property name="jdbcUrl" value="jdbc:mysql://192.168.73.131/sharding_order?serverTimezone=Asia/Shanghai&useSSL=false"/>
</bean>
<bean id="slave0" class="com.zaxxer.hikari.HikariDataSource" destroy-method="close">
<property name="driverClassName" value="com.mysql.cj.jdbc.Driver" />
<property name="username" value="imooc" />
<property name="password" value="[email protected]" />
<property name="jdbcUrl" value="jdbc:mysql://192.168.73.130/sharding_order?serverTimezone=Asia/Shanghai&useSSL=false"/>
</bean>
<bean id="ms1" class="com.zaxxer.hikari.HikariDataSource" destroy-method="close">
<property name="driverClassName" value="com.mysql.cj.jdbc.Driver" />
<property name="username" value="imooc" />
<property name="password" value="[email protected]" />
<property name="jdbcUrl" value="jdbc:mysql://192.168.73.132/shard_order?serverTimezone=Asia/Shanghai&useSSL=false"/>
</bean>
<master-slave:load-balance-algorithm id="msStrategy" type="RANDOM"/>
<sharding:data-source id="sharding-data-source">
<sharding:sharding-rule data-source-names="ds0,slave0,ms1" >
<sharding:master-slave-rules>
<sharding:master-slave-rule id="ms0" master-data-source-name="ds0" slave-data-source-names="slave0"
strategy-ref="msStrategy"
/>
</sharding:master-slave-rules>
<sharding:table-rules>
<sharding:table-rule logic-table="t_order" actual-data-nodes="ms$->{0..1}.t_order_$->{1..2}"
database-strategy-ref="databaseStrategy" table-strategy-ref="standard"
key-generator-ref="snowflake"
/>
</sharding:table-rules>
<sharding:broadcast-table-rules>
<sharding:broadcast-table-rule table="area"/>
</sharding:broadcast-table-rules>
<!--<sharding:binding-table-rules>-->
<!--<sharding:binding-table-rule logic-tables="t_order,t_order_item" />-->
<!--</sharding:binding-table-rules>-->
</sharding:sharding-rule>
</sharding:data-source>
<sharding:key-generator id="snowflake" column="order_id" type="SNOWFLAKE" props-ref="snow"/>
<bean:properties id="snow">
<prop key="worker.id">678</prop>
<prop key="max.tolerate.time.difference.milliseconds">10</prop>
</bean:properties>
<sharding:inline-strategy id="databaseStrategy" sharding-column="user_id"
algorithm-expression="ms$->{user_id % 2}" />
<bean id="myShard" class="com.example.shardingjdbcdemo.sharding.MySharding"/>
<sharding:standard-strategy id="standard" sharding-column="order_id" precise-algorithm-ref="myShard"/>
<sharding:inline-strategy id="tableStrategy" sharding-column="order_id"
algorithm-expression="t_order_$->{order_id % 2 +1}" />
<bean class="org.mybatis.spring.SqlSessionFactoryBean">
<property name="dataSource" ref="sharding-data-source"/>
<property name="mapperLocations" value="classpath*:/mybatis/*.xml"/>
</bean>
</beans>
對應的自定義分片處理邏輯類
package com.example.shardingjdbcdemo.sharding;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingValue;
import java.util.Collection;
/**
* 自定義的處理分片表達式的類
* 本次用例中,需要處理order_id 的分片規則
* order_id 做為庫内分片的字段,它既是t_order表的主鍵,同時也是子表t_order_item中的字段
* order_id 使用了全局唯一主鍵 雪花算法
*/
public class MySharding implements PreciseShardingAlgorithm<Long> {
@Override
public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<Long> shardingValue) {
Long id = shardingValue.getValue();
long mode = id % availableTargetNames.size();
String[] strings = availableTargetNames.toArray(new String[0]);
//取絕對值
mode = Math.abs(mode);
System.out.println(strings[0]+"---------"+strings[1]);
System.out.println("mode="+mode);
return strings[(int) mode];
}
}
(2)第二種方式,使用springboot starter 的配置方式
a、注釋關于spring名稱空間的引用
b、修改maven依賴
c、修改application.properties檔案如下
# 配置真實資料源
spring.shardingsphere.datasource.names=ds0,ms1,slave0
# 配置第 1 個資料源 -主庫(131與130構成主從關系)
spring.shardingsphere.datasource.ds0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.ds0.jdbcUrl=jdbc:mysql://192.168.73.131/sharding_order?serverTimezone=Asia/Shanghai&useSSL=false
spring.shardingsphere.datasource.ds0.username=root
spring.shardingsphere.datasource.ds0.password=root
#從庫
spring.shardingsphere.datasource.slave0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.slave0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.slave0.jdbcUrl=jdbc:mysql://192.168.73.130/sharding_order?serverTimezone=Asia/Shanghai&useSSL=false
spring.shardingsphere.datasource.slave0.username=root
spring.shardingsphere.datasource.slave0.password=root
# 配置第 2 個資料源
spring.shardingsphere.datasource.ms1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ms1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.ms1.jdbcUrl=jdbc:mysql://192.168.73.132/sharding_order?serverTimezone=Asia/Shanghai&useSSL=false
spring.shardingsphere.datasource.ms1.username=root
spring.shardingsphere.datasource.ms1.password=root
#讀寫分離配置
spring.shardingsphere.sharding.master-slave-rules.ms0.master-data-source-name=ds0
spring.shardingsphere.sharding.master-slave-rules.ms0.slave-data-source-names=slave0
spring.shardingsphere.sharding.master-slave-rules.ms0.load-balance-algorithm-type=RANDOM
# 配置 t_order 表規則
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ms$->{0..1}.t_order_$->{0..1}
# 配置分庫政策
spring.shardingsphere.sharding.tables.t_order.database-strategy.inline.sharding-column=user_id
#相應的分片算法
spring.shardingsphere.sharding.tables.t_order.database-strategy.inline.algorithm-expression=ms$->{user_id % 2}
# 配置分表政策
spring.shardingsphere.sharding.tables.t_order.table-strategy.standard.sharding-column=user_id
#自定義的分片算法
spring.shardingsphere.sharding.tables.t_order.table-strategy.standard.precise-algorithm-class-name=com.example.shardingjdbcdemo.sharding.MySharding
#配置t_order的主鍵生成政策
spring.shardingsphere.sharding.tables.t_order.key-generator.column=order_id
spring.shardingsphere.sharding.tables.t_order.key-generator.type=UUID
#全局表
spring.shardingsphere.sharding.broadcast-tables=area
#mybatis mapper 位置
mybatis.mapper-locations=/mybatis/*.xml
d、自定義的分片表達式處理類
package com.example.shardingjdbcdemo.sharding;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingValue;
import java.util.Collection;
/**
* 自定義的處理分片表達式的類
* 本次用例中,需要處理order_id 的分片規則
* order_id 做為庫内分片的字段,它既是t_order表的主鍵,同時也是子表t_order_item中的字段
* order_id 使用了全局唯一主鍵 UUID
*/
public class MySharding implements PreciseShardingAlgorithm<String> {
@Override
public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<String> shardingValue) {
String id = shardingValue.getValue();
int mode = id.hashCode() % availableTargetNames.size();
String[] strings = availableTargetNames.toArray(new String[0]);
//取絕對值
mode = Math.abs(mode);
System.out.println(strings[0]+"---------"+strings[1]);
System.out.println("mode="+mode);
return strings[mode];
}
}
e.分布式id解決方案之雪花算法
概述:
snowFlake 時Twitter提出的分布式ID算法
一個64bit的long型數字
引入了時間戳,保持自增
基本概念
基本保持全局唯一,毫秒内并發最大4096個ID
時間回調可能會引起ID重複
可設定最大容忍回調時間
應用
配置:
# 配置真實資料源
spring.shardingsphere.datasource.names=ds0,ms1,slave0
# 配置第 1 個資料源 -主庫(131與130構成主從關系)
spring.shardingsphere.datasource.ds0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.ds0.jdbcUrl=jdbc:mysql://192.168.73.131/sharding_order?serverTimezone=Asia/Shanghai&useSSL=false
spring.shardingsphere.datasource.ds0.username=root
spring.shardingsphere.datasource.ds0.password=root
#從庫
spring.shardingsphere.datasource.slave0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.slave0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.slave0.jdbcUrl=jdbc:mysql://192.168.73.130/sharding_order?serverTimezone=Asia/Shanghai&useSSL=false
spring.shardingsphere.datasource.slave0.username=root
spring.shardingsphere.datasource.slave0.password=root
# 配置第 2 個資料源
spring.shardingsphere.datasource.ms1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ms1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.ms1.jdbcUrl=jdbc:mysql://192.168.73.132/sharding_order?serverTimezone=Asia/Shanghai&useSSL=false
spring.shardingsphere.datasource.ms1.username=root
spring.shardingsphere.datasource.ms1.password=root
#讀寫分離配置
spring.shardingsphere.sharding.master-slave-rules.ms0.master-data-source-name=ds0
spring.shardingsphere.sharding.master-slave-rules.ms0.slave-data-source-names=slave0
spring.shardingsphere.sharding.master-slave-rules.ms0.load-balance-algorithm-type=RANDOM
# 配置 t_order 表規則
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ms$->{0..1}.t_order_$->{0..1}
# 配置分庫政策
spring.shardingsphere.sharding.tables.t_order.database-strategy.inline.sharding-column=user_id
#相應的分片算法
spring.shardingsphere.sharding.tables.t_order.database-strategy.inline.algorithm-expression=ms$->{user_id % 2}
# 配置分表政策
spring.shardingsphere.sharding.tables.t_order.table-strategy.standard.sharding-column=user_id
#自定義的分片算法
spring.shardingsphere.sharding.tables.t_order.table-strategy.standard.precise-algorithm-class-name=com.example.shardingjdbcdemo.sharding.MySharding
#配置t_order的主鍵生成政策
spring.shardingsphere.sharding.tables.t_order.key-generator.column=order_id
#spring.shardingsphere.sharding.tables.t_order.key-generator.type=UUID 全局id生成政策 UUID
#全局ID生成政策之雪花算法相關配置
spring.shardingsphere.sharding.tables.t_order.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order.key-generator.props.worker.id=345
spring.shardingsphere.sharding.tables.t_order.key-generator.props.max.tolerate.time.difference.milliseconds=10
#全局表
spring.shardingsphere.sharding.broadcast-tables=area
#mybatis mapper 位置
mybatis.mapper-locations=/mybatis/*.xml
對應的自定義分片處理邏輯類:
package com.example.shardingjdbcdemo.sharding;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingValue;
import java.util.Collection;
/**
* 自定義的處理分片表達式的類
* 本次用例中,需要處理order_id 的分片規則
* order_id 做為庫内分片的字段,它既是t_order表的主鍵,同時也是子表t_order_item中的字段
* order_id 使用了全局唯一主鍵 雪花算法
*/
public class MySharding implements PreciseShardingAlgorithm<Long> {
@Override
public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<Long> shardingValue) {
Long id = shardingValue.getValue();
long mode = id % availableTargetNames.size();
String[] strings = availableTargetNames.toArray(new String[0]);
//取絕對值
mode = Math.abs(mode);
System.out.println(strings[0]+"---------"+strings[1]);
System.out.println("mode="+mode);
return strings[(int) mode];
}
}