摘要:本文通過實際案例,說明如何按日期來對訂單資料進行水平分庫和分表,實現資料的分散式查詢和操作。
本文分享自華為雲社群《資料庫分庫分表Java實戰經驗總結 丨【綻放吧!資料庫】》,作者: jackwangcumt。
我們知道,當前的應用都離不開資料庫,隨著資料庫中的資料越來越多,單表突破效能上限記錄時,如MySQL單表上線估計在近千萬條內,當記錄數繼續增長時,從效能考慮,則需要進行拆分處理。而拆分分為橫向拆分和縱向拆分。一般來說,採用橫向拆分較多,這樣的表結構是一致的,只是不同的資料儲存在不同的資料庫表中。其中橫向拆分也分為分庫和分表。
1 示例資料庫準備
為了說清楚如何用Java語言和相關框架實現業務表的分庫和分表處理。這裡首先用MySQL資料庫中建立兩個獨立的資料庫例項,名字為mydb和mydb2,此可演示分庫操作。另外在每個資料庫例項中,建立12個業務表,按年月進行資料拆分。具體的建立表指令碼如下:
CREATE TABLE `t_bill_2021_1` (
`order_id` bigint(20) NOT NULL COMMENT '訂單id',
`user_id` int(20) NOT NULL COMMENT '使用者id',
`address_id` bigint(20) NOT NULL COMMENT '地址id',
`status` char(1) DEFAULT NULL COMMENT '訂單狀態',
`create_time` datetime DEFAULT NULL COMMENT '建立時間',
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 '訂單id',
`user_id` int(20) NOT NULL COMMENT '使用者id',
`address_id` bigint(20) NOT NULL COMMENT '地址id',
`status` char(1) DEFAULT NULL COMMENT '訂單狀態',
`create_time` datetime DEFAULT NULL COMMENT '建立時間',
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 '訂單id',
`user_id` int(20) NOT NULL COMMENT '使用者id',
`address_id` bigint(20) NOT NULL COMMENT '地址id',
`status` char(1) DEFAULT NULL COMMENT '訂單狀態',
`create_time` datetime DEFAULT NULL COMMENT '建立時間',
PRIMARY KEY (`order_id`) USING BTREE
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci;
成功執行指令碼後,在MySQL管理工具中可以看到如下的示例介面:
2 分庫分表實現
在Java語言下的框架中,有眾多的開源框架,其中關於分庫分表的框架,可以選擇Apache ShardingSphere,其官網介紹說:ShardingSphere 是一套開源的分散式資料庫解決方案組成的生態圈,它由 JDBC、Proxy 和 Sidecar(規劃中)這 3 款既能夠獨立部署,又支援混合部署配合使用的產品組成。 它們均提供標準化的資料水平擴充套件、分散式事務和分散式治理等功能,可適用於如 Java 同構、異構語言、雲原生等各種多樣化的應用場景。Apache ShardingSphere 5.x 版本開始致力於可插拔架構。 目前,資料分片、讀寫分離、資料加密、影子庫壓測等功能,以及 MySQL、PostgreSQL、SQLServer、Oracle 等 SQL 與協議的支援,均通過外掛的方式織入專案。官網地址為: https://shardingsphere.apache.org/index_zh.html 。
下面的示例採用Spring Boot框架來實現,相關的庫通過Maven進行管理。首先給出pom.xml配置檔案的定義:
<?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,給出一個實體類,它對應於上述建立的資料庫表t_bill,其定義如下:
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;
}
}
對映類BillMapper定義如下:
package com.example.wyd.mapper;
import com.baomidou.mybatisplus.core.mapper.BaseMapper;
import com.example.wyd.dao.Bill;
public interface BillMapper extends BaseMapper<Bill> { }
服務類介面定義如下:
package com.example.wyd.service;
import com.baomidou.mybatisplus.extension.service.IService;
import com.example.wyd.dao.Bill;
public interface BillService extends IService<Bill> { }
服務類介面的實現類定義如下:
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 { }
這裡我們採用了MybatisPlus框架,它可以很方便的進行資料庫相關操作,而無需過多寫SQL來實現具體業務邏輯。通過上述定義,通過繼承介面的方式,並提供實體類的定義,MybatisPlus框架會通過反射機制來根據資料庫設定來生成SQL語句,其中包含增刪改查介面,具體的實現我們並未具體定義。
下面定義一個自定義的分庫演算法,具體實現如下:
package com.example.wyd;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingValue;
import java.util.Collection;
//自定義資料庫分片演算法
public class DBShardingAlgorithm implements PreciseShardingAlgorithm<Long> {
@Override
public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<Long> shardingValue) {
//真實資料庫節點
availableTargetNames.stream().forEach((item) -> {
System.out.println("actual db:" + item);
});
//邏輯表以及分片的欄位名
System.out.println("logicTable:"+shardingValue.getLogicTableName()+";shardingColumn:"+ shardingValue.getColumnName());
//分片資料欄位值
System.out.println("shardingColumn value:"+ shardingValue.getValue().toString());
//獲取欄位值
long orderId = shardingValue.getValue();
//分片索引計算 0 , 1
long db_index = orderId & (2 - 1);
for (String each : availableTargetNames) {
if (each.equals("ds"+db_index)) {
//匹配的話,返回資料庫名
return each;
}
}
throw new IllegalArgumentException();
}
}
下面給出資料的分表邏輯,這個定義稍顯複雜一點,就是根據業務資料的日期欄位值,根據月份落入對應的物理資料表中。實現示例程式碼如下:
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;
//表按日期自定義分片
public class TableShardingAlgorithm implements PreciseShardingAlgorithm<Date> {
@Override
public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<Date> shardingValue) {
//真實資料庫節點
availableTargetNames.stream().forEach((item) -> {
System.out.println("actual db:" + item);
});
//邏輯表以及分片的欄位名
System.out.println("logicTable:"+shardingValue.getLogicTableName()+";shardingColumn:"+ shardingValue.getColumnName());
//分片資料欄位值
System.out.println("shardingColumn value:"+ shardingValue.getValue().toString());
//獲取表名字首
String tb_name = shardingValue.getLogicTableName() + "_";
//根據日期分表
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); //也可以安裝年月日來分表
// 選擇表
tb_name = tb_name + year + "_" + mon;
//實際的表名
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();
}
}
資料的分庫分表可以在Spring Boot的屬性配置檔案中進行設(application.properties):
server.port=8080
#########################################################################################################
# 配置ds0 和ds1兩個資料來源
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
#########################################################################################################
# 預設的分庫策略: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}
#資料庫分片欄位
spring.shardingsphere.sharding.tables.t_bill.database-strategy.standard.sharding-column=order_id
#自定義資料庫分片策略
spring.shardingsphere.sharding.tables.t_bill.database-strategy.standard.precise-algorithm-class-name=com.example.wyd.DBShardingAlgorithm
#表分片欄位
spring.shardingsphere.sharding.tables.t_bill.table-strategy.standard.sharding-column=create_time
#自定義表分片策略
spring.shardingsphere.sharding.tables.t_bill.table-strategy.standard.precise-algorithm-class-name=com.example.wyd.TableShardingAlgorithm
#########################################################################################################
# 使用SNOWFLAKE演算法生成主鍵
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
最後,我們給出一個定義的Controller型別,來測試分庫分表的查詢和儲存操作是否正確。HomeController類定義如下:
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,我們可以用測試類初始化一些資料,並做一些初步的資料操作測試:
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; //根據資料修改,無資料會報錯
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();
} }
}
執行上述測試,通過後會生成測試資料。
3 驗證
開啟瀏覽器,輸入網址進行查詢測試:http://localhost:8080/api/query?start=2021-02-07%2000:00:00&end=2021-03-07%2000:00:00
輸入如下網址進行資料新增測試:http://localhost:8080/api/save?userid=999&addressId=999&status=M&date=2021-03-07%2000:00:00
通過跟蹤分析,此資料落入如下的表中,SQL語句如下:
SELECT * FROM mydb2.t_bill_2021_3 LIMIT 0, 1000
這裡還需要注意,ShardingSphere 還支援分散式事務,感興趣的可以閱讀官網相關資料進行學習。