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Java实战：教你如何进行数据库分库分表

亿华云2025-10-03 02:16:52【应用开发】5人已围观

简介我们知道，当前的应用都离不开数据库，随着数据库中的数据越来越多，单表突破性能上限记录时，如MySQL单表上线估计在近千万条内，当记录数继续增长时，从性能考虑，则需要进行拆分处理。而拆分分为横向拆分和纵

我们知道，实战数据当前的教何进行应用都离不开数据库，随着数据库中的库分库分数据越来越多，单表突破性能上限记录时，实战数据如MySQL单表上线估计在近千万条内，教何进行当记录数继续增长时，库分库分从性能考虑，实战数据则需要进行拆分处理。教何进行而拆分分为横向拆分和纵向拆分。库分库分一般来说，实战数据采用横向拆分较多，教何进行这样的库分库分表结构是一致的，只是实战数据不同的数据存储在不同的数据库表中。其中横向拆分也分为分库和分表。教何进行

1.示例数据库准备

为了说清楚如何用Java语言和相关框架实现业务表的库分库分分库和分表处理。这里首先用MySQL数据库中创建两个独立的数据库实例，名字为mydb和mydb2，此可演示分库操作。另外在每个数据库实例中，创建12个业务表，按年月进行数据拆分。具体的创建表脚本如下：

CREATE TABLE `t_bill_2021_1` ( `order_id` bigint(20) NOT NULL COMMENT 订单id, `user_id` int(20) NOT NULL COMMENT 用户id, `address_id` bigint(20) NOT NULL COMMENT 地址id, `status` char(1) DEFAULT NULL COMMENT 订单状态, `create_time` datetime DEFAULT NULL COMMENT 创建时间, PRIMARY KEY (`order_id`) USING BTREE ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci; CREATE TABLE `t_bill_2021_2` ( `order_id` bigint(20) NOT NULL COMMENT 订单id, `user_id` int(20) NOT NULL COMMENT 用户id, `address_id` bigint(20) NOT NULL COMMENT 地址id, `status` char(1) DEFAULT NULL COMMENT 订单状态, `create_time` datetime DEFAULT NULL COMMENT 创建时间, PRIMARY KEY (`order_id`) USING BTREE ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci; -- 省略.... CREATE TABLE `t_bill_2021_12` ( `order_id` bigint(20) NOT NULL COMMENT 订单id, `user_id` int(20) NOT NULL COMMENT 用户id, `address_id` bigint(20) NOT NULL COMMENT 地址id, `status` char(1) DEFAULT NULL COMMENT 订单状态, `create_time` datetime DEFAULT NULL COMMENT 创建时间, PRIMARY KEY (`order_id`) USING BTREE ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci;

成功执行脚本后，在MySQL管理工具中可以看到如下的站群服务器示例界面：

2.分库分表实现

在Java语言下的框架中，有众多的开源框架，其中关于分库分表的框架，可以选择Apache ShardingSphere，其官网介绍说：ShardingSphere 是一套开源的分布式数据库解决方案组成的生态圈，它由 JDBC、Proxy 和 Sidecar（规划中）这 3 款既能够独立部署，又支持混合部署配合使用的产品组成。它们均提供标准化的数据水平扩展、分布式事务和分布式治理等功能，可适用于如 Java 同构、异构语言、云原生等各种多样化的应用场景。Apache ShardingSphere 5.x 版本开始致力于可插拔架构。目前，数据分片、读写分离、数据加密、影子库压测等功能，以及 MySQL、PostgreSQL、SQLServer、Oracle 等 SQL 与协议的支持，亿华云均通过插件的方式织入项目。官网地址为： https://shardingsphere.apache.org/index_zh.html 。

下面的示例采用Spring Boot框架来实现，相关的库通过Maven进行管理。首先给出pom.xml配置文件的定义：

<?xml version="1.0" encoding="UTF-8"?> <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd"> <modelVersion>4.0.0</modelVersion> <parent> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-parent</artifactId> <version>2.5.3</version> <relativePath/>  </parent> <groupId>com.example</groupId> <artifactId>wyd</artifactId> <version>0.0.1-SNAPSHOT</version> <name>wyd</name> <description>Demo project for Spring Boot</description> <properties> <java.version>1.8</java.version> <mybatis-plus.version>3.1.1</mybatis-plus.version> <sharding-sphere.version>4.0.0-RC2</sharding-sphere.version> <shardingsphere.version>5.0.0-beta</shardingsphere.version> </properties> <dependencies> <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>2.0.1</version> </dependency> <dependency> <groupId>com.baomidou</groupId> <artifactId>mybatis-plus-boot-starter</artifactId> <version>${ mybatis-plus.version}</version> </dependency> <dependency> <groupId>org.projectlombok</groupId> <artifactId>lombok</artifactId> <optional>true</optional> </dependency> <dependency> <groupId>joda-time</groupId> <artifactId>joda-time</artifactId> <version>2.9.8</version> </dependency> <dependency> <groupId>org.apache.shardingsphere</groupId> <artifactId>sharding-jdbc-spring-boot-starter</artifactId> <version>${ sharding-sphere.version}</version> </dependency> <dependency> <groupId>org.apache.shardingsphere</groupId> <artifactId>sharding-jdbc-spring-namespace</artifactId> <version>${ sharding-sphere.version}</version> </dependency> <dependency> <groupId>mysql</groupId> <artifactId>mysql-connector-java</artifactId> <scope>runtime</scope> </dependency> <dependency> <groupId>org.postgresql</groupId> <artifactId>postgresql</artifactId> <scope>runtime</scope> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-test</artifactId> <scope>test</scope> </dependency> </dependencies> <build> <plugins> <plugin> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-maven-plugin</artifactId> </plugin> </plugins> </build> </project>

其次，给出一个实体类，它对应于上述创建的数据库表t_bill，其定义如下：

package com.example.wyd.dao; import com.baomidou.mybatisplus.annotation.TableName; import lombok.Data; import java.util.Date; @Data @TableName("t_bill") public class Bill { private Long orderId; private Integer userId; private Long addressId; private String status; private Date createTime; public void setOrderId(Long orderId) { this.orderId = orderId; } public void setUserId(Integer userId) { this.userId = userId; } public void setAddressId(Long addressId) { this.addressId = addressId; } public void setStatus(String status) { this.status = status; } public void setCreateTime(Date createTime) { this.createTime = createTime; } } 映射类BillMapper定义如下： package com.example.wyd.mapper; import com.baomidou.mybatisplus.core.mapper.BaseMapper; import com.example.wyd.dao.Bill; public interface BillMapper extends BaseMapper<Bill> { }

服务类接口定义如下：

package com.example.wyd.service; import com.baomidou.mybatisplus.extension.service.IService; import com.example.wyd.dao.Bill; public interface BillService extends IService<Bill> { }

服务类接口的实现类定义如下：

package com.example.wyd.service; import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl; import com.example.wyd.dao.Bill; import com.example.wyd.mapper.BillMapper; import org.springframework.stereotype.Service; @Service public class BillServiceImpl extends ServiceImpl<BillMapper, Bill> implements BillService { }

这里我们采用了MybatisPlus框架，它可以很方便的进行数据库相关操作，而无需过多写SQL来实现具体业务逻辑。通过上述定义，通过继承接口的方式，并提供实体类的定义，MybatisPlus框架会通过反射机制来根据数据库设置来生成SQL语句，其中包含增删改查接口，具体的实现我们并未具体定义。

下面定义一个自定义的分库算法，具体实现如下：

package com.example.wyd; import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm; import org.apache.shardingsphere.api.sharding.standard.PreciseShardingValue; import java.util.Collection; //自定义数据库分片算法 public class DBShardingAlgorithm implements PreciseShardingAlgorithm<Long> { @Override public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<Long> shardingValue) { //真实数据库节点 availableTargetNames.stream().forEach((item) -> { System.out.println("actual db:" + item); }); //逻辑表以及分片的字段名 System.out.println("logicTable:"+shardingValue.getLogicTableName()+";shardingColumn:"+ shardingValue.getColumnName()); //分片数据字段值 System.out.println("shardingColumn value:"+ shardingValue.getValue().toString()); //获取字段值 long orderId = shardingValue.getValue(); //分片索引计算 0 , 1 long db_index = orderId & (2 - 1); for (String each : availableTargetNames) { if (each.equals("ds"+db_index)) { //匹配的话，返回数据库名 return each; } } throw new IllegalArgumentException(); } }

下面给出数据的分表逻辑，网站模板这个定义稍显复杂一点，就是根据业务数据的日期字段值，根据月份落入对应的物理数据表中。实现示例代码如下：

package com.example.wyd; import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm; import org.apache.shardingsphere.api.sharding.standard.PreciseShardingValue; import java.util.Collection; import java.util.Date; //表按日期自定义分片 public class TableShardingAlgorithm implements PreciseShardingAlgorithm<Date> { @Override public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<Date> shardingValue) { //真实数据库节点 availableTargetNames.stream().forEach((item) -> { System.out.println("actual db:" + item); }); //逻辑表以及分片的字段名 System.out.println("logicTable:"+shardingValue.getLogicTableName()+";shardingColumn:"+ shardingValue.getColumnName()); //分片数据字段值 System.out.println("shardingColumn value:"+ shardingValue.getValue().toString()); //获取表名前缀 String tb_name = shardingValue.getLogicTableName() + "_"; //根据日期分表 Date date = shardingValue.getValue(); String year = String.format("%tY", date); String mon =String.valueOf(Integer.parseInt(String.format("%tm", date))); //String dat = String.format("%td", date); //也可以安装年月日来分表 // 选择表 tb_name = tb_name + year + "_" + mon; //实际的表名 System.out.println("tb_name:" + tb_name); for (String each : availableTargetNames) { //System.out.println("availableTableName:" + each); if (each.equals(tb_name)) { //返回物理表名 return each; } } throw new IllegalArgumentException(); } }

数据的分库分表可以在Spring Boot的属性配置文件中进行设（ application.properties ）：

server.port=8080 ######################################################################################################### # 配置ds0 和ds1两个数据源 spring.shardingsphere.datasource.names = ds0,ds1 #ds0 配置 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.jdbc-url = jdbc:mysql://127.0.0.1:3306/mydb?characterEncoding=utf8 spring.shardingsphere.datasource.ds0.username = uname spring.shardingsphere.datasource.ds0.password = pwd #ds1 配置 spring.shardingsphere.datasource.ds1.type = com.zaxxer.hikari.HikariDataSource spring.shardingsphere.datasource.ds1.driver-class-name = com.mysql.cj.jdbc.Driver spring.shardingsphere.datasource.ds1.jdbc-url = jdbc:mysql://127.0.0.1:3306/mydb2characterEncoding=utf8 spring.shardingsphere.datasource.ds1.username = uname spring.shardingsphere.datasource.ds1.password = pwd ######################################################################################################### # 默认的分库策略：id取模 spring.shardingsphere.sharding.default-database-strategy.inline.sharding-column = id spring.shardingsphere.sharding.default-database-strategy.inline.algorithm-expression = ds$->{ id % 2} ######################################################################################################### spring.shardingsphere.sharding.tables.t_bill.actual-data-nodes=ds$->{ 0..1}.t_bill_$->{ 2021..2021}_$->{ 1..12} #数据库分片字段 spring.shardingsphere.sharding.tables.t_bill.database-strategy.standard.sharding-column=order_id #自定义数据库分片策略 spring.shardingsphere.sharding.tables.t_bill.database-strategy.standard.precise-algorithm-class-name=com.example.wyd.DBShardingAlgorithm #表分片字段 spring.shardingsphere.sharding.tables.t_bill.table-strategy.standard.sharding-column=create_time #自定义表分片策略 spring.shardingsphere.sharding.tables.t_bill.table-strategy.standard.precise-algorithm-class-name=com.example.wyd.TableShardingAlgorithm ######################################################################################################### # 使用SNOWFLAKE算法生成主键 spring.shardingsphere.sharding.tables.t_bill.key-generator.column = order_id spring.shardingsphere.sharding.tables.t_bill.key-generator.type = SNOWFLAKE spring.shardingsphere.sharding.tables.t_bill.key-generator.props.worker.id=123 ######################################################################################################### spring.shardingsphere.props.sql.show = true

最后，我们给出一个定义的Controller类型，来测试分库分表的查询和保存操作是否正确。HomeController类定义如下：

package com.example.wyd.controller; import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper; import com.example.wyd.dao.Bill; import com.example.wyd.service.BillService; import org.joda.time.DateTime; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.web.bind.annotation.RequestMapping; import org.springframework.web.bind.annotation.RequestParam; import org.springframework.web.bind.annotation.RestController; import java.text.ParseException; import java.text.SimpleDateFormat; import java.util.Date; import java.util.List; @RestController @RequestMapping("/api") public class HomeController { @Autowired private BillService billService; //http://localhost:8080/api/query?start=2021-02-07%2000:00:00&end=2021-03-07%2000:00:00 @RequestMapping("/query") public List<Bill> queryList(@RequestParam("start") String start, @RequestParam("end") String end) { SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss"); try { Date date = sdf.parse(start); Date date2 = sdf.parse(end); QueryWrapper<Bill> queryWrapper = new QueryWrapper<>(); queryWrapper.ge("create_time",date) .and(qw-> qw.le("create_time", date2)).last("limit 1,10"); List<Bill> billIPage = billService.list(queryWrapper); System.out.println(billIPage.size()); billIPage.forEach(System.out::println); return billIPage; } catch (ParseException e) { e.printStackTrace(); } return null; } //http://localhost:8080/api/save?userid=999&addressId=999&status=M&date=2021-03-07%2000:00:00 @RequestMapping("/save") public String Save(@RequestParam("userid") int userId, @RequestParam("addressId") long AddressId, @RequestParam("status") String status ,@RequestParam("date") String strDate) { String ret ="0"; SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss"); try { Date date = sdf.parse(strDate); Bill bill = new Bill(); bill.setUserId(userId); bill.setAddressId(AddressId); bill.setStatus(status); bill.setCreateTime(date); boolean isOk = billService.save(bill); if (isOk){ ret ="1"; } } catch (ParseException e) { e.printStackTrace(); } return ret; } }

至此，我们可以用测试类初始化一些数据，并做一些初步的数据操作测试：

package com.example.wyd; import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper; import com.example.wyd.dao.Bill; import com.example.wyd.dao.Order; import com.example.wyd.service.BillService; import com.example.wyd.service.OrderService; import org.joda.time.DateTime; import org.junit.jupiter.api.Test; import org.springframework.beans.factory.annotation.Autowired; import java.text.ParseException; import java.text.SimpleDateFormat; import java.util.*; public class OrderServiceImplTest extends WydApplicationTests { @Autowired private BillService billService; @Test public void testBillSave(){ for (int i = 0 ; i< 120 ; i++){ Bill bill = new Bill(); bill.setUserId(i); bill.setAddressId((long)i); bill.setStatus("K"); bill.setCreateTime((new Date(new DateTime(2021,(i % 11)+1,7,00, 00,00,000).getMillis()))); billService.save(bill); } } @Test public void testGetByOrderId(){ long id = 626038622575374337L; //根据数据修改，无数据会报错 QueryWrapper<Bill> queryWrapper = new QueryWrapper<>(); queryWrapper.eq("order_id", id); Bill bill = billService.getOne(queryWrapper); System.out.println(bill.toString()); } @Test public void testGetByDate(){ SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss"); try { Date date = sdf.parse("2021-02-07 00:00:00"); QueryWrapper<Bill> queryWrapper = new QueryWrapper<>(); queryWrapper.eq("create_time",date); List<Bill> billIPage = billService.list(queryWrapper); System.out.println(billIPage.size()); System.out.println(billIPage.toString()); } catch (ParseException e) { e.printStackTrace(); } } @Test public void testGetByDate2(){ SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss"); try { Date date = sdf.parse("2021-02-07 00:00:00"); Date date2 = sdf.parse("2021-03-07 00:00:00"); QueryWrapper<Bill> queryWrapper = new QueryWrapper<>(); queryWrapper.ge("create_time",date) .and(qw-> qw.le("create_time", date2)); List<Bill> billIPage = billService.list(queryWrapper); System.out.println(billIPage.size()); billIPage.forEach(System.out::println); } catch (ParseException e) { e.printStackTrace(); } } }

执行上述测试，通过后会生成测试数据。