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:

Java 实战:教你如何进行数据库分库分表_数据库

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 ApacheShardingSphere,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。ApacheShardingSphere 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.IService;
import com.example.wyd.dao.Bill;
public interface BillService extends IService<Bill> {


}
} 

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置(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

Java 实战:教你如何进行数据库分库分表_分表_02

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

Java 实战:教你如何进行数据库分库分表_分表_03

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

Java 实战:教你如何进行数据库分库分表_Java_04

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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