一、Sharding-JDBC简介
Sharding-JDBC是Sharding-Sphere的一个产品，它有三个产品，分别是Sharding-JDBC、Sharding-Proxy和Sharding-Sidecar，这三个产品提供了标准化的数据分片、读写分离、柔性事务和数据治理功能。我们这里用的是Sharding-JDBC，所以想了解后面两个产品的话可以去它们官网查看。
Sharding-JDBC为轻量级Java框架，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，兼容性特别强。适用的ORM框架有JPA, Hibernate, Mybatis, Spring JDBC Template或直接使用JDBC；第三方的数据库连接池有DBCP, C3P0, BoneCP, Druid等；支持的数据库有MySQL，Oracle，SQLServer和PostgreSQL；多样化的配置文件Java，yaml，Spring Boot ，Spring命名空间。其实这里说的都是废话，大家可以不看，下面我们动手开始正式配置。
二、具体的实现方式
1、maven引用
我这里用的配置方式是Spring命名空间配置，所以只需要引用sharding-jdbc-spring-namespace就可以了，还有要注意的是我用的不是当当网的sharding，注意groupId是io.shardingsphere。如果用的是其它配置方式可以去http://maven.aliyun.com/nexus/#nexus-search;quick~io.shardingsphere网站查找相应maven引用
<dependency> <groupId>io.shardingsphere</groupId> <artifactId>sharding-jdbc-spring-namespace</artifactId> <version>3.0.0.M1</version> </dependency>
2、数据库准备
我这里用的是mysql数据库，根据我们项目的具体需求，我准备了三个主库和对应的从库。模拟的主库名有master，暂时没有做对应从库，所以对应的从库还是指向master；第二个主库有master_1，对应的从库有master_1_slaver_1，master_1_slave_2；第三个主库有master_2，对应的从库有master_2_slave_1，master_2_slave_2。
数据库中的表也做了分表，下面是对应的mysql截图。
这第一幅图上的主从库都应该在不同的服务器上的，但这里只是为了模拟所以就建在了本地服务器上了。我们读写分离中的写操作只会发生在主库上，从库会自动同步主库上的数据并为读提供数据。数据库的主从复制在上篇博文中做了详细的介绍，大家可以去看看http://www.zzvips.com/article/208668.html
这幅图作为我们本来的主库，下面做的分库和分表都是基于这个库中的订单表分的。所以分库中的表只有订单表和订单明细表。
第三幅图截的是第二个主库，里面对订单和订单明细表做了分表操作，具体的分片策略和分片算法下面再做介绍。第三个主表和第二个主表是一样的，所有的从表都和对应的主表是一致的。
3、Spring配置
数据库信息配置文件db.properties配置可以配置两份，分为开发版和测试版，如下：
# master Master.url=jdbc:mysql://localhost:3306/master?useUnicode=true&characterEncoding=utf8&autoReconnect=true&rewriteBatchedStatements=true Master.username=root Master.password=123456 Slave.url=jdbc:mysql://localhost:3306/master?useUnicode=true&characterEncoding=utf8&autoReconnect=true&rewriteBatchedStatements=true Slave.username=root Slave.password=123456 # maste_1 Master_1.url=jdbc:mysql://localhost:3306/master_1?useUnicode=true&characterEncoding=utf8&autoReconnect=true&rewriteBatchedStatements=true Master_1.username=root Master_1.password=123456 Master_1_Slave_1.url=jdbc:mysql://localhost:3306/master_1_slave_1?useUnicode=true&characterEncoding=utf8&autoReconnect=true&rewriteBatchedStatements=true Master_1_Slave_1.username=root Master_1_Slave_1.password=123456 Master_1_Slave_2.url=jdbc:mysql://localhost:3306/master_1_slave_2?useUnicode=true&characterEncoding=utf8&autoReconnect=true&rewriteBatchedStatements=true Master_1_Slave_2.username=root Master_1_Slave_2.password=123456 # master_2 Master_2.url=jdbc:mysql://localhost:3306/master_2?useUnicode=true&characterEncoding=utf8&autoReconnect=true&rewriteBatchedStatements=true Master_2.username=root Master_2.password=123456 Master_2_Slave_1.url=jdbc:mysql://localhost:3306/master_2_slave_1?useUnicode=true&characterEncoding=utf8&autoReconnect=true&rewriteBatchedStatements=true Master_2_Slave_1.username=root Master_2_Slave_1.password=123456 Master_2_Slave_2.url=jdbc:mysql://localhost:3306/master_2_slave_2?useUnicode=true&characterEncoding=utf8&autoReconnect=true&rewriteBatchedStatements=true Master_2_Slave_2.username=root Master_2_Slave_2.password=123456
Spring对应的配置：
Spring-Sphere官网中的demo里用的都是行表达式的分片策略，但是行表达式的策略不利于数据库和表的横向扩展，所以我这里用的是标准分片策略，精准分片算法和范围分片算法。因为我们项目中暂时用的分片键都是user_id单一键，所以说不存在复合分片策略，也用不到Hint分片策略，行表达式分片策略和不分片策略。
<?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:context="http://www.springframework.org/schema/context"
xmlns:tx="http://www.springframework.org/schema/tx"
xmlns:sharding="http://shardingsphere.io/schema/shardingsphere/sharding"
xmlns:master-slave="http://shardingsphere.io/schema/shardingsphere/masterslave"
xsi:schemaLocation="http://www.springframework.org/schema/beans
http://www.springframework.org/schema/beans/spring-beans.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://shardingsphere.io/schema/shardingsphere/sharding
http://shardingsphere.io/schema/shardingsphere/sharding/sharding.xsd
http://shardingsphere.io/schema/shardingsphere/masterslave
http://shardingsphere.io/schema/shardingsphere/masterslave/master-slave.xsd">
<context:component-scan base-package="com.jihao" />
<!-- db.properties数据库信息配置 -->
<bean id="property" class="org.springframework.beans.factory.config.PropertyPlaceholderConfigurer">
<property name="location" value="classpath:property/db_dev.properties" />
</bean>
<!-- 主库 -->
<bean id="master" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
<property name="driverClassName" value="com.mysql.jdbc.Driver"/>
<property name="url" value="${Master.url}"/>
<property name="username" value="${Master.username}"/>
<property name="password" value="${Master.password}"/>
</bean>
<!-- 主库的从库 -->
<bean id="slave" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
<property name="driverClassName" value="com.mysql.jdbc.Driver"/>
<property name="url" value="${Slave.url}"/>
<property name="username" value="${Slave.username}"/>
<property name="password" value="${Slave.password}"/>
</bean>
<!-- 主库的分库1 -->
<bean id="master_1" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
<property name="driverClassName" value="com.mysql.jdbc.Driver"/>
<property name="url" value="${Master_1.url}"/>
<property name="username" value="${Master_1.username}"/>
<property name="password" value="${Master_1.password}"/>
</bean>
<!-- 分库1的从库1 -->
<bean id="master_1_slave_1" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
<property name="driverClassName" value="com.mysql.jdbc.Driver"/>
<property name="url" value="${Master_1_Slave_1.url}"/>
<property name="username" value="${Master_1_Slave_1.username}"/>
<property name="password" value="${Master_1_Slave_1.password}"/>
</bean>
<!-- 分库1的从库2 -->
<bean id="master_1_slave_2" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
<property name="driverClassName" value="com.mysql.jdbc.Driver"/>
<property name="url" value="${Master_1_Slave_2.url}"/>
<property name="username" value="${Master_1_Slave_2.username}"/>
<property name="password" value="${Master_1_Slave_2.password}"/>
</bean>
<!-- 主库的分库2 -->
<bean id="master_2" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
<property name="driverClassName" value="com.mysql.jdbc.Driver"/>
<property name="url" value="${Master_2.url}"/>
<property name="username" value="${Master_2.username}"/>
<property name="password" value="${Master_2.password}"/>
</bean>
<!-- 分库2的从库1 -->
<bean id="master_2_slave_1" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
<property name="driverClassName" value="com.mysql.jdbc.Driver"/>
<property name="url" value="${Master_2_Slave_1.url}"/>
<property name="username" value="${Master_2_Slave_1.username}"/>
<property name="password" value="${Master_2_Slave_1.password}"/>
</bean>
<!-- 分库2的从库2 -->
<bean id="master_2_slave_2" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
<property name="driverClassName" value="com.mysql.jdbc.Driver"/>
<property name="url" value="${Master_2_Slave_2.url}"/>
<property name="username" value="${Master_2_Slave_2.username}"/>
<property name="password" value="${Master_2_Slave_2.password}"/>
</bean>
<!-- 主从关系配置 -->
<bean id="randomStrategy" class="io.shardingsphere.core.api.algorithm.masterslave.RandomMasterSlaveLoadBalanceAlgorithm" />
<master-slave:data-source id="ms_master" master-data-source-name="master" slave-data-source-names="slave" strategy-ref="randomStrategy" />
<master-slave:data-source id="ms_master_1" master-data-source-name="master_1" slave-data-source-names="master_1_slave_1, master_1_slave_2" strategy-ref="randomStrategy" />
<master-slave:data-source id="ms_master_2" master-data-source-name="master_2" slave-data-source-names="master_2_slave_1, master_2_slave_2" strategy-ref="randomStrategy" />
<!-- 分库策略 精确分片算法 -->
<bean id="preciseDatabaseStrategy" class="com.jihao.algorithm.PreciseModuleDatabaseShardingAlgorithm" />
<!-- 分库策略 范围分片算法 -->
<bean id="rangeDatabaseStrategy" class="com.jihao.algorithm.RangeModuleDatabaseShardingAlgorithm" />
<!-- 分表策略 精确分片算法 -->
<bean id="preciseTableStrategy" class="com.jihao.algorithm.PreciseModuleTableShardingAlgorithm" />
<!-- 分表策略 范围分片算法-->
<bean id="rangeTableStrategy" class="com.jihao.algorithm.RangeModuleTableShardingAlgorithm" />
<sharding:standard-strategy id="databaseStrategy" sharding-column="user_id" precise-algorithm-ref="preciseDatabaseStrategy" range-algorithm-ref="rangeDatabaseStrategy" />
<!-- 分表策略 -->
<sharding:standard-strategy id="tableStrategy" sharding-column="user_id" precise-algorithm-ref="preciseTableStrategy" range-algorithm-ref="rangeTableStrategy" />
<!-- 行表达式算法 -->
<!-- <sharding:inline-strategy id="databaseStrategy" sharding-column="user_id" algorithm-expression="demo_ds_ms_$->{user_id % 2}" />
<sharding:inline-strategy id="orderTableStrategy" sharding-column="order_id" algorithm-expression="t_order_$->{order_id % 2}" />
<sharding:inline-strategy id="orderItemTableStrategy" sharding-column="order_item_id" algorithm-expression="t_order_item_$->{order_item_id % 2}" /> -->
<sharding:data-source id="shardingDataSource">
<sharding:sharding-rule data-source-names="ms_master,ms_master_1,ms_master_2">
<sharding:table-rules>
<sharding:table-rule logic-table="t_order" actual-data-nodes="ms_master_$->{1..2}.t_order_$->{1..3}" database-strategy-ref="databaseStrategy" table-strategy-ref="tableStrategy" generate-key-column-name="order_id"/>
<sharding:table-rule logic-table="t_order_item" actual-data-nodes="ms_master_$->{1..2}.t_order_item_$->{1..3}" database-strategy-ref="databaseStrategy" table-strategy-ref="tableStrategy" generate-key-column-name="order_item_id"/>
</sharding:table-rules>
</sharding:sharding-rule>
</sharding:data-source>
<bean id="transactionManager" class="org.springframework.jdbc.datasource.DataSourceTransactionManager">
<property name="dataSource" ref="shardingDataSource" />
</bean>
<tx:annotation-driven />
<bean id="sqlSessionFactory" class="org.mybatis.spring.SqlSessionFactoryBean">
<!-- 用于在控制台打印sql（不需要的可以注释掉这一行） -->
<property name="configLocation" value="classpath:log/mybatis-config.xml"></property>
<property name="dataSource" ref="shardingDataSource"/>
<property name="mapperLocations" value="classpath*:com/jihao/mapper/*.xml"/>
</bean>
<bean class="org.mybatis.spring.mapper.MapperScannerConfigurer">
<property name="basePackage" value="com.jihao"/>
<property name="sqlSessionFactoryBeanName" value="sqlSessionFactory"/>
</bean>
</beans>
4、精准分片算法和范围分片算法的Java代码
标准分片策略，精准分片算法
package com.jihao.algorithm;
import io.shardingsphere.core.api.algorithm.sharding.PreciseShardingValue;
import io.shardingsphere.core.api.algorithm.sharding.standard.PreciseShardingAlgorithm;
import java.util.Collection;
import com.alibaba.fastjson.JSON;
/**
* 自定义标准分片策略，使用精确分片算法（=与IN）
* @author JiHao
*
*/
public class PreciseModuleDatabaseShardingAlgorithm implements PreciseShardingAlgorithm<Long>{
@Override
public String doSharding(Collection<String> availableTargetNames,
PreciseShardingValue<Long> preciseShardingValue) {
System.out.println("collection:" + JSON.toJSONString(availableTargetNames) + ",preciseShardingValue:" + JSON.toJSONString(preciseShardingValue));
for (String name : availableTargetNames) {
// =与IN中分片键对应的值
String value = String.valueOf(preciseShardingValue.getValue());
// 分库的后缀
int i = 1;
// 求分库后缀名的递归算法
if (name.endsWith("_" + countDatabaseNum(Long.parseLong(value), i))) {
return name;
}
}
throw new UnsupportedOperationException();
}
/**
* 计算该量级的数据在哪个数据库
* @return
*/
private String countDatabaseNum(long columnValue, int i){
// ShardingSphereConstants每个库中定义的数据量
long left = ShardingSphereConstants.databaseAmount * (i-1);
long right = ShardingSphereConstants.databaseAmount * i;
if(left < columnValue && columnValue <= right){
return String.valueOf(i);
}else{
i++;
return countDatabaseNum(columnValue, i);
}
}
}
标准分片策略，范围分片算法
package com.jihao.algorithm;
import io.shardingsphere.core.api.algorithm.sharding.RangeShardingValue;
import io.shardingsphere.core.api.algorithm.sharding.standard.RangeShardingAlgorithm;
import java.util.ArrayList;
import java.util.Collection;
import java.util.List;
import com.alibaba.fastjson.JSON;
import com.google.common.collect.Range;
/**
* 自定义标准分库策略，使用范围分片算法（BETWEEN AND）
* @author JiHao
*
*/
public class RangeModuleDatabaseShardingAlgorithm implements RangeShardingAlgorithm<Long>{
@Override
public Collection<String> doSharding(
Collection<String> availableTargetNames,
RangeShardingValue<Long> rangeShardingValue) {
System.out.println("Range collection:" + JSON.toJSONString(availableTargetNames) + ",rangeShardingValue:" + JSON.toJSONString(rangeShardingValue));
Collection<String> collect = new ArrayList<>();
Range<Long> valueRange = rangeShardingValue.getValueRange();
// BETWEEN AND中分片键对应的最小值
long lowerEndpoint = Long.parseLong(String.valueOf(valueRange.lowerEndpoint()));
// BETWEEN AND中分片键对应的最大值
long upperEndpoint = Long.parseLong(String.valueOf(valueRange.upperEndpoint()));
// 分表的后缀
int i = 1;
List<Integer> arrs = new ArrayList<Integer>();
// 求分表后缀名的递归算法
List<Integer> list = countDatabaseNum(i, lowerEndpoint, upperEndpoint, arrs);
for (Integer integer : list) {
for (String each : availableTargetNames) {
if (each.endsWith("_" + integer)) {
collect.add(each);
}
}
}
return collect;
}
/**
* 计算该量级的数据在哪个表
* @param columnValue
* @param i
* @param lowerEndpoint 最小区间
* @param upperEndpoint 最大区间
* @return
*/
private List<Integer> countDatabaseNum(int i, long lowerEndpoint, long upperEndpoint, List<Integer> arrs){
long left = ShardingSphereConstants.databaseAmount * (i-1);
long right = ShardingSphereConstants.databaseAmount * i;
// 区间最大值小于分库最大值
if(left < upperEndpoint && upperEndpoint <= right){
arrs.add(i);
return arrs;
}else{
if(left < lowerEndpoint && lowerEndpoint <= right){
arrs.add(i);
}
i++;
return countDatabaseNum(i, lowerEndpoint, upperEndpoint, arrs);
}
}
}
分库的策略用的和分库的代码是一样的，不同之处就是分库用的是databaseAmount，分表用的是tableAmount。下面的ShardingSphereConstants的代码。
package com.jihao.algorithm;
/**
* ShardingSphere中用到的常量
* @author JiHao
*
*/
public class ShardingSphereConstants {
/**
* 订单、优惠券相关的表，按用户数量分库，64w用户数据为一个库
* (0,64w]
*/
public static int databaseAmount = 640000;
/**
* 一个订单表里存10000的用户订单
* (0,1w]
*/
public static int tableAmount = 10000;
}
到这里所有的配置基本上都已经完成了，下面的测试。
5、测试
下面是测试的mybatis的测试文件，都是最基础的就不讲解了。
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN" "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
<mapper namespace="com.jihao.dao.TestShardingMapper">
<resultMap id="BaseResultMap" type="com.jihao.entity.Order">
<id column="order_id" jdbcType="INTEGER" property="orderId" />
<result column="user_id" jdbcType="INTEGER" property="userId" />
<result column="status" jdbcType="INTEGER" property="status" />
</resultMap>
<insert id="insert" parameterType="com.jihao.entity.Order" useGeneratedKeys="true" keyProperty="orderId">
INSERT INTO t_order (
user_id, status
)
VALUES (
#{userId,jdbcType=INTEGER},
#{status,jdbcType=VARCHAR}
)
</insert>
<insert id="insertItem" useGeneratedKeys="true" keyProperty="orderItemId">
INSERT INTO t_order_item (
order_id, user_id
)
VALUES (
#{orderId,jdbcType=INTEGER},
#{userId,jdbcType=INTEGER}
)
</insert>
<select id="searchOrder" resultMap="BaseResultMap">
SELECT * from t_order
</select>
<select id="queryWithEqual" resultMap="BaseResultMap">
SELECT * FROM t_order WHERE user_id=51
</select>
<select id="queryWithIn" resultMap="BaseResultMap">
SELECT * FROM t_order WHERE user_id IN (50, 51)
</select>
<select id="queryWithBetween" resultMap="BaseResultMap">
SELECT * FROM t_order WHERE user_id between 10000 and 30000
</select>
<select id="queryUser" resultType="Map">
SELECT * FROM t_user
</select>
</mapper>
下面对应的mapper的Java代码
package com.jihao.dao;
import java.util.List;
import java.util.Map;
import org.apache.ibatis.annotations.Mapper;
import com.jihao.entity.Order;
import com.jihao.entity.OrderItem;
@Mapper
public interface TestShardingMapper {
int insert(Order record);
int insertItem(OrderItem record);
List<Order> searchOrder();
List<Order> queryWithEqual();
List<Order> queryWithIn();
List<Order> queryWithBetween();
List<Map<String, Object>> queryUser();
}
下面是对应的订单entity代码
package com.jihao.entity;
/**
* 订单
* @author JiHao
*/
public class Order {
private Long orderId;
private Integer userId;
private String status;
public Long getOrderId() {
return orderId;
}
public void setOrderId(Long orderId) {
this.orderId = orderId;
}
public Integer getUserId() {
return userId;
}
public void setUserId(Integer userId) {
this.userId = userId;
}
public String getStatus() {
return status;
}
public void setStatus(String status) {
this.status = status;
}
}
下面是对应的订单明细entity代码
package com.jihao.entity;
/**
* 测试分片
* @author JiHao
*/
public class OrderItem {
private Long orderItemId;
private Long orderId;
private Integer userId;
public Long getOrderId() {
return orderId;
}
public void setOrderId(Long orderId) {
this.orderId = orderId;
}
public Integer getUserId() {
return userId;
}
public void setUserId(Integer userId) {
this.userId = userId;
}
public Long getOrderItemId() {
return orderItemId;
}
public void setOrderItemId(Long orderItemId) {
this.orderItemId = orderItemId;
}
}
下面是测试的controller，并没有写Junit测试。
package com.jihao.controller.test;
import java.util.List;
import java.util.Map;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.ResponseBody;
import com.jihao.dao.TestShardingMapper;
import com.jihao.entity.Order;
import com.jihao.entity.OrderItem;
import com.jihao.result.Result;
import com.jihao.result.ResultUtil;
/**
* 测试分片
* @author JiHao
*
*/
@Controller
@RequestMapping(value = "test")
public class TestShardingController {
@Autowired
private TestShardingMapper testShardingMapper;
/**
* 测试添加
* @return
*/
@ResponseBody
@GetMapping(value = "/testAdd")
public String testAdd(){
for (int i = 0; i < 10; i++) {
Order order = new Order();
// order.setUserId(50);
// order.setUserId(51);
// order.setUserId(10001);
order.setUserId(20001);
order.setStatus("INSERT_TEST");
int count = testShardingMapper.insert(order);
System.out.println(count);
long orderId = order.getOrderId();
System.out.println(order.getOrderId());
OrderItem item = new OrderItem();
item.setOrderId(orderId);
// order.setUserId(50);
// order.setUserId(51);
// order.setUserId(10001);
order.setUserId(20001);
testShardingMapper.insertItem(item);
}
return "success";
}
/**
* 测试搜索
* @return
*/
@ResponseBody
@GetMapping(value = "/testSearch")
public Result searchData(){
List<Order> list = testShardingMapper.searchOrder();
System.out.println(list.size() + " all");
List<Order> list1 = testShardingMapper.queryWithIn();
System.out.println(list1.size() + " In");
List<Order> list2 = testShardingMapper.queryWithEqual();
System.out.println(list2.size() + " Equal");
List<Order> list3 = testShardingMapper.queryWithBetween();
System.out.println(list3.size() + " Between");
List<Map<String, Object>> list4 = testShardingMapper.queryUser();
System.out.println(list4.size() + " user");
return ResultUtil.success(null);
}
}
这里要重点提出来的是做搜索测试的时候，因为主从库都在我本地服务器上，并没有做主从复制，大家可以根据我上篇博文配置一下就可以顺利操作了，如果没有配置的话从库里是不会有数据的，所以在做完写操作时把主库中的数据手动传输给从库，这样才能读出数据。
这里顺便给出Sharding-Sphere的官方地址http://shardingjdbc.io/index_zh.html，以及demo地址https://github.com/sharding-sphere/sharding-sphere-example（demo里Sharding-Sphere的maven配置我在跑的时候没跑通，需要把版本改成3.0.0.M1就ok了）。
到此这篇关于SpringBoot使用Sharding-JDBC实现数据分片和读写分离的文章就介绍到这了,更多相关SpringBoot使用Sharding-JDBC实现数据分片和读写分离内容请搜索服务器之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持服务器之家！
原文链接：https://blog.csdn.net/shijiemozujiejie/article/details/80786231