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本篇内容介绍了“SpringBoot怎么使用Sharding-JDBC实现数据分片和读写分离”的有关知识,在实际案例的操作过程中,不少人都会遇到这样的困境,接下来就让小编带领大家学习一下如何处理这些情况吧!希望大家仔细阅读,能够学有所成!
一、Sharding-JDBC简介
二、具体的实现方式
1、maven引用
2、数据库准备
3、Spring配置
4、精准分片算法和范围分片算法的Java代码
5、测试
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。
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>
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https://www.yisu.com/article/226077.htm
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。
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>
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。
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。
“SpringBoot怎么使用Sharding-JDBC实现数据分片和读写分离”的内容就介绍到这里了,感谢大家的阅读。如果想了解更多行业相关的知识可以关注亿速云网站,小编将为大家输出更多高质量的实用文章!
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