分庫分表背景:
數據庫性能瓶頸：主要分為按照業務來劃分或者按照數據量來劃分。
拆分方式：
水平拆分(每個表的結構都一樣)：訂單表數據量大，我們可以水平拆分 ，分成order表1、order表2、order表3 。。。
垂直拆分：一個多字段的表拆分成多個表
例如：order訂單表和oderItem訂單詳情表
一個訂單會購買多件商品，因此，訂單order表中會只有一條數據，orderItem訂單項表會對應這個訂單購買的多件商品。

文章目錄

• • • • • • 技術選型
          • 1. 引入 Maven 依賴
          • 2. 規則配置
          • 3. 實體
          • 4. 接口
          • 5. 表結構
          • 6. 測試類
          • 7. 完整pom

技術選型

組件/框架版本

spring-boot	2.4.3
jpa	2.4.3
shardingsphere	5.0.0-alpha
mysql	5.7.3
hikari	3.4.5

分庫分表

官網文檔：
https://shardingsphere.apache.org/document/current/cn/user-manual/shardingsphere-jdbc/usage/sharding/spring-boot-starter/

1. 引入 Maven 依賴

<dependency><groupId>org.apache.shardingsphere</groupId><artifactId>shardingsphere-jdbc-core-spring-boot-starter</artifactId><version>5.0.0-alpha</version></dependency>

2. 規則配置

#大多數企業選擇方案: 一個庫分表 場景：一個客戶多個訂單 按照order_id 分表# 配置真實數據源 spring.shardingsphere.datasource.names=ds0spring.shardingsphere.datasource.common.type=com.zaxxer.hikari.HikariDataSource spring.shardingsphere.datasource.common.driver-class-name=com.mysql.jdbc.Driver spring.shardingsphere.datasource.common.username=root spring.shardingsphere.datasource.common.password=rootspring.shardingsphere.datasource.ds_0.jdbc-url=jdbc:mysql://localhost:3306/ds0?serverTimezone=UTC&useSSL=false# 配置 t_order 表規則 spring.shardingsphere.rules.sharding.tables.t_order.actual-data-nodes=ds0.t_order_$->{0..1}# 配置分表策略 spring.shardingsphere.rules.sharding.tables.t_order.table-strategy.standard.sharding-column=order_id spring.shardingsphere.rules.sharding.tables.t_order.table-strategy.standard.sharding-algorithm-name=table-inline# 配置 分片算法 spring.shardingsphere.rules.sharding.sharding-algorithms.table-inline.type=INLINE spring.shardingsphere.rules.sharding.sharding-algorithms.table-inline.props.algorithm-expression=t_order_$->{order_id % 2}# 分片算法配置 spring.shardingsphere.rules.sharding.tables.t_order.key-generate-strategy.column=order_id spring.shardingsphere.rules.sharding.tables.t_order.key-generate-strategy.key-generator-name=snowflake# 分布式序列算法配置 spring.shardingsphere.rules.sharding.key-generators.snowflake.type=SNOWFLAKE spring.shardingsphere.rules.sharding.key-generators.snowflake.props.worker-id=123# 具體的屬性配置 spring.shardingsphere.props.sql-show=true

3. 實體

package com.gblfy.distributedsharding.entity;import lombok.Data;import javax.persistence.*;@Data @Entity @Table(name = "t_order") public class OrderEntity {@Id@GeneratedValue(strategy = GenerationType.IDENTITY)private Long orderId;private Integer userId; }

4. 接口

package com.gblfy.distributedsharding.mapper;import com.gblfy.distributedsharding.entity.OrderEntity; import org.springframework.data.jpa.repository.JpaRepository;import java.util.List;public interface OrderMapper extends JpaRepository<OrderEntity, Long> {OrderEntity findByOrderId(Long orderId);List<OrderEntity> findByUserId(Integer userId); }

5. 表結構

CREATE DATABASE ds0; use ds0; CREATE TABLE `t_order_0` (`order_id` bigint(20) unsigned NOT NULL,`user_id` int(11) DEFAULT NULL,PRIMARY KEY (`order_id`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;CREATE TABLE `t_order_1` (`order_id` bigint(20) unsigned NOT NULL,`user_id` int(11) DEFAULT NULL,PRIMARY KEY (`order_id`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

6. 測試類

package com.gblfy.distributedsharding;import com.gblfy.distributedsharding.entity.OrderEntity; import com.gblfy.distributedsharding.mapper.OrderMapper; import org.junit.jupiter.api.Test; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.boot.test.context.SpringBootTest;import java.util.Random;@SpringBootTest class DistributedShardingApplicationTests {@Autowiredprivate OrderMapper orderMapper;@Testvoid insert() {OrderEntity entity = new OrderEntity();entity.setUserId(new Random().nextInt(999));orderMapper.save(entity);}@Testvoid findByOrderId() {//按照order_id分表 ，會查詢1次，通過order_id分表orderMapper.findByOrderId(570271967295811584L);}@Testvoid findByUserId() {//會查詢2次，知道user_id，但是不知道哪個表orderMapper.findByUserId(556);}@Testvoid updateByOrderId() {OrderEntity byOrderId = orderMapper.findByOrderId(570279923689172992L);byOrderId.setUserId(1000);orderMapper.save(byOrderId);} }

7. 完整pom

<dependencies><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-data-jpa</artifactId></dependency><dependency><groupId>mysql</groupId><artifactId>mysql-connector-java</artifactId><scope>runtime</scope></dependency><dependency><groupId>org.projectlombok</groupId><artifactId>lombok</artifactId><optional>true</optional></dependency><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-test</artifactId><scope>test</scope></dependency><dependency><groupId>org.apache.shardingsphere</groupId><artifactId>shardingsphere-jdbc-core-spring-boot-starter</artifactId><version>5.0.0-alpha</version></dependency>

總結

以上是生活随笔為你收集整理的Springboot2.x +JPA 集成 Apache ShardingSphere 同库分表的全部內容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網站內容還不錯，歡迎將生活随笔推薦給好友。