Java实战：教你如何进行数据库分库分表

摘要：本文通过实际案例，说明如何按日期来对订单数据进行水平分库和分表，实现数据的分布式查询和操作。

本文分享自华为云社区《数据库分库分表Java实战经验总结丨【绽放吧！数据库】》，作者： jackwangcumt。

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向拆分。一般来说，采用横向拆分较多，这样的表结构是一致的，只是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。

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，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/> <!-- lookup parent from repository -->

    </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，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。

3 验证

打开浏览器，输入网址进行查询测试：http://localhost:8080/api/query?start=2021-02-07%2000:00:00&end=2021-03-07%2000:00:00

输入如下网址进行数据新增测试：http://localhost:8080/api/save?userid=999&addressId=999&status=M&date=2021-03-07%2000:00:00

通过跟踪分析，此数据落入如下的表中，SQL语句如下：

SELECT * FROM mydb2.t_bill_2021_3 LIMIT 0, 1000

这里还需要注意，ShardingSphere 还支持分布式事务，感兴趣的可以阅读官网相关资料进行学习。

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