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SpringBoot使用Sharding-JDBC分库分表

2019.02.01 11:54 1970浏览

本文介绍SpringBoot使用当当Sharding-JDBC进行分库分表。

1.有关Sharding-JDBC

有关Sharding-JDBC介绍这里就不在多说,之前Sharding-JDBC是当当网自研的关系型数据库的水平扩展框架,现在已经捐献给Apache,具体可以查看Github,地址是:https://shardingsphere.apache.org/document/current/cn/overview/

目前貌似还不能从Maven仓库下载依赖,需要手动下载源码打包使用,所以本文使用的还是当当网的依赖。

2.本文场景

2.1 数据库

接下来介绍一下本文的场景,本文是分别创建了2个数据库database0和database1。其中每个数据库都创建了2个数据表,goods_0和goods_1,如图所示。这里蓝色的代表database0中的表,红色的代表database1中的表。绿色goods表是虚拟表(图画的比较丑,审美不好,凑合看吧)。

2.2 分库

本文分库样例比较简单,根据数据库表中字段goods_id的大小进行判断,如果goods_id大于20则使用database0,否则使用database1。

2.3 分表

分样例比较简单,根据数据库表中字段goods_type的数值的奇偶进行判断,奇数使用goods_1表,偶数使用goods_0表。

2.4 代码流程

流程大致是这样,在应用程序中我们操作虚拟表goods,但是当真正操作数据库的时候,会根据我们的分库分表规则进行匹配然后操作。

3.代码实现

本文使用SpringBoot2.0.3,SpringData-JPA,Druid连接池,和当当的sharding-jdbc。

3.1 建表SQL

创建表和数据库的SQL如下所示。

CREATE DATABASE database0;
USE database0;
DROP TABLE IF EXISTS `goods_0`;
CREATE TABLE `goods_0` (
  `goods_id` bigint(20) NOT NULL,
  `goods_name` varchar(100) COLLATE utf8_bin NOT NULL,
  `goods_type` bigint(20) DEFAULT NULL,
  PRIMARY KEY (`goods_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_bin;
DROP TABLE IF EXISTS `goods_1`;
CREATE TABLE `goods_1` (
  `goods_id` bigint(20) NOT NULL,
  `goods_name` varchar(100) COLLATE utf8_bin NOT NULL,
  `goods_type` bigint(20) DEFAULT NULL,
  PRIMARY KEY (`goods_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_bin;
CREATE DATABASE database1;
USE database1;
DROP TABLE IF EXISTS `goods_0`;
CREATE TABLE `goods_0` (
  `goods_id` bigint(20) NOT NULL,
  `goods_name` varchar(100) COLLATE utf8_bin NOT NULL,
  `goods_type` bigint(20) DEFAULT NULL,
  PRIMARY KEY (`goods_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_bin;

DROP TABLE IF EXISTS `goods_1`;
CREATE TABLE `goods_1` (
  `goods_id` bigint(20) NOT NULL,
  `goods_name` varchar(100) COLLATE utf8_bin NOT NULL,
  `goods_type` bigint(20) DEFAULT NULL,
  PRIMARY KEY (`goods_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_bin;

3.2 依赖文件

新建项目,加入当当的sharding-jdbc-core依赖和druid连接池,完整pom如下所示。

<?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 http://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>2.0.3.RELEASE</version>
        <relativePath/> <!-- lookup parent from repository -->
    </parent>
    <groupId>com.dalaoyang</groupId>
    <artifactId>springboot2_shardingjdbc_fkfb</artifactId>
    <version>0.0.1-SNAPSHOT</version>
    <name>springboot2_shardingjdbc_fkfb</name>
    <description>springboot2_shardingjdbc_fkfb</description>

    <properties>
        <java.version>1.8</java.version>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-data-jpa</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>

        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-devtools</artifactId>
            <scope>runtime</scope>
        </dependency>
        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <scope>runtime</scope>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
        <!-- lombok -->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <!-- druid -->
        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>druid</artifactId>
            <version>1.1.9</version>
        </dependency>
        <!-- sharding-jdbc -->
        <dependency>
            <groupId>com.dangdang</groupId>
            <artifactId>sharding-jdbc-core</artifactId>
            <version>1.5.4</version>
        </dependency>

    </dependencies>

    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>

</project>

3.3 配置信息

在配置信息中配置了两个数据库的信息和JPA的简单配置。

##Jpa配置
spring.jpa.database=mysql
spring.jpa.show-sql=true
spring.jpa.hibernate.ddl-auto=none

##数据库配置
##数据库database0地址
database0.url=jdbc:mysql://localhost:3306/database0?characterEncoding=utf8&useSSL=false
##数据库database0用户名
database0.username=root
##数据库database0密码
database0.password=root
##数据库database0驱动
database0.driverClassName=com.mysql.jdbc.Driver
##数据库database0名称
database0.databaseName=database0

##数据库database1地址
database1.url=jdbc:mysql://localhost:3306/database1?characterEncoding=utf8&useSSL=false
##数据库database1用户名
database1.username=root
##数据库database1密码
database1.password=root
##数据库database1驱动
database1.driverClassName=com.mysql.jdbc.Driver
##数据库database1名称
database1.databaseName=database1

3.4 启动类

启动类加入了@EnableAutoConfiguration取出数据库自动配置,使用@EnableTransactionManagement开启事务,使用@EnableConfigurationProperties注解加入配置实体,启动类完整代码请入所示。

package com.dalaoyang;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
import org.springframework.boot.context.properties.EnableConfigurationProperties;
import org.springframework.context.annotation.ComponentScan;
import org.springframework.transaction.annotation.EnableTransactionManagement;

@SpringBootApplication
@EnableAutoConfiguration(exclude={DataSourceAutoConfiguration.class})
@EnableTransactionManagement(proxyTargetClass = true)
@EnableConfigurationProperties
public class Springboot2ShardingjdbcFkfbApplication {

    public static void main(String[] args) {
        SpringApplication.run(Springboot2ShardingjdbcFkfbApplication.class, args);
    }

}

3.5 实体类和数据库操作层

这里没什么好说的,就是简单的实体和Repository,只不过在Repository内加入between方法和in方法用于测试,代码如下所示。

Goods实体类。

package com.dalaoyang.entity;

import lombok.Data;

import javax.persistence.Entity;
import javax.persistence.Id;
import javax.persistence.Table;

/**
 * @author yangyang
 * @date 2019/1/29
 */
@Entity
@Table(name="goods")
@Data
public class Goods {
    @Id
    private Long goodsId;

    private String goodsName;

    private Long goodsType;
}

GoodsRepository类。

package com.dalaoyang.repository;

import com.dalaoyang.entity.Goods;
import org.springframework.data.jpa.repository.JpaRepository;

import java.util.List;

/**
 * @author yangyang
 * @date 2019/1/29
 */
public interface GoodsRepository extends JpaRepository<Goods, Long> {

    List<Goods> findAllByGoodsIdBetween(Long goodsId1,Long goodsId2);

    List<Goods> findAllByGoodsIdIn(List<Long> goodsIds);
}

3.6 数据库配置

本文使用了两个实体来接收数据库信息,并且创建数据源,也可以采用别的方式。首先看一下Database0Config和Database1Config两个类的代码。

Database0Config类。

package com.dalaoyang.database;

import com.alibaba.druid.pool.DruidDataSource;
import lombok.Data;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.stereotype.Component;

import javax.sql.DataSource;

/**
 * @author yangyang
 * @date 2019/1/30
 */
@Data
@ConfigurationProperties(prefix = "database0")
@Component
public class Database0Config {
    private String url;
    private String username;
    private String password;
    private String driverClassName;
    private String databaseName;

    public DataSource createDataSource() {
        DruidDataSource result = new DruidDataSource();
        result.setDriverClassName(getDriverClassName());
        result.setUrl(getUrl());
        result.setUsername(getUsername());
        result.setPassword(getPassword());
        return result;
    }
}

Database1Config类。

package com.dalaoyang.database;

import com.alibaba.druid.pool.DruidDataSource;
import lombok.Data;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.stereotype.Component;

import javax.sql.DataSource;

/**
 * @author yangyang
 * @date 2019/1/30
 */
@Data
@ConfigurationProperties(prefix = "database1")
@Component
public class Database1Config {
    private String url;
    private String username;
    private String password;
    private String driverClassName;
    private String databaseName;

    public DataSource createDataSource() {
        DruidDataSource result = new DruidDataSource();
        result.setDriverClassName(getDriverClassName());
        result.setUrl(getUrl());
        result.setUsername(getUsername());
        result.setPassword(getPassword());
        return result;
    }
}

接下来新建DataSourceConfig用于创建数据源和使用分库分表策略,其中分库分表策略会调用分库算法类和分表算法类,DataSourceConfig类代码如下所示。

package com.dalaoyang.database;


import com.dalaoyang.config.DatabaseShardingAlgorithm;
import com.dalaoyang.config.TableShardingAlgorithm;
import com.dangdang.ddframe.rdb.sharding.api.ShardingDataSourceFactory;
import com.dangdang.ddframe.rdb.sharding.api.rule.DataSourceRule;
import com.dangdang.ddframe.rdb.sharding.api.rule.ShardingRule;
import com.dangdang.ddframe.rdb.sharding.api.rule.TableRule;
import com.dangdang.ddframe.rdb.sharding.api.strategy.database.DatabaseShardingStrategy;
import com.dangdang.ddframe.rdb.sharding.api.strategy.table.TableShardingStrategy;
import com.dangdang.ddframe.rdb.sharding.keygen.DefaultKeyGenerator;
import com.dangdang.ddframe.rdb.sharding.keygen.KeyGenerator;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

import javax.sql.DataSource;
import java.sql.SQLException;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;

/**
 * @author yangyang
 * @date 2019/1/29
 */
@Configuration
public class DataSourceConfig {

    @Autowired
    private Database0Config database0Config;

    @Autowired
    private Database1Config database1Config;

    @Autowired
    private DatabaseShardingAlgorithm databaseShardingAlgorithm;

    @Autowired
    private TableShardingAlgorithm tableShardingAlgorithm;

    @Bean
    public DataSource getDataSource() throws SQLException {
        return buildDataSource();
    }

    private DataSource buildDataSource() throws SQLException {
        //分库设置
        Map<String, DataSource> dataSourceMap = new HashMap<>(2);
        //添加两个数据库database0和database1
        dataSourceMap.put(database0Config.getDatabaseName(), database0Config.createDataSource());
        dataSourceMap.put(database1Config.getDatabaseName(), database1Config.createDataSource());
        //设置默认数据库
        DataSourceRule dataSourceRule = new DataSourceRule(dataSourceMap, database0Config.getDatabaseName());

        //分表设置,大致思想就是将查询虚拟表Goods根据一定规则映射到真实表中去
        TableRule orderTableRule = TableRule.builder("goods")
                .actualTables(Arrays.asList("goods_0", "goods_1"))
                .dataSourceRule(dataSourceRule)
                .build();

        //分库分表策略
        ShardingRule shardingRule = ShardingRule.builder()
                .dataSourceRule(dataSourceRule)
                .tableRules(Arrays.asList(orderTableRule))
                .databaseShardingStrategy(new DatabaseShardingStrategy("goods_id", databaseShardingAlgorithm))
                .tableShardingStrategy(new TableShardingStrategy("goods_type", tableShardingAlgorithm)).build();
        DataSource dataSource = ShardingDataSourceFactory.createDataSource(shardingRule);
        return dataSource;
    }


    @Bean
    public KeyGenerator keyGenerator() {
        return new DefaultKeyGenerator();
    }

}

3.7 分库分表算法

由于这里只是简单的分库分表样例,所以分库类这里实现SingleKeyDatabaseShardingAlgorithm类,采用了单分片键数据源分片算法,需要重写三个方法,分别是:

  • doEqualSharding:SQL中==的规则。
  • doInSharding:SQL中in的规则。
  • doBetweenSharding:SQL中between的规则。

本文分库规则是基于值大于20则使用database0,其余使用database1,所以简单if,else就搞定了,分库算法类DatabaseShardingAlgorithm代码如下所示。

package com.dalaoyang.config;

import com.dalaoyang.database.Database0Config;
import com.dalaoyang.database.Database1Config;
import com.dangdang.ddframe.rdb.sharding.api.ShardingValue;
import com.dangdang.ddframe.rdb.sharding.api.strategy.database.SingleKeyDatabaseShardingAlgorithm;
import com.google.common.collect.Range;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;

import java.util.Collection;
import java.util.LinkedHashSet;

/**
 * 这里使用的都是单键分片策略
 * 示例分库策略是:
 * GoodsId<=20使用database0库
 * 其余使用database1库
 * @author yangyang
 * @date 2019/1/30
 */
@Component
public class DatabaseShardingAlgorithm implements SingleKeyDatabaseShardingAlgorithm<Long> {

    @Autowired
    private Database0Config database0Config;

    @Autowired
    private Database1Config database1Config;

    @Override
    public String doEqualSharding(Collection<String> availableTargetNames, ShardingValue<Long> shardingValue) {
        Long value = shardingValue.getValue();
        if (value <= 20L) {
            return database0Config.getDatabaseName();
        } else {
            return database1Config.getDatabaseName();
        }
    }

    @Override
    public Collection<String> doInSharding(Collection<String> availableTargetNames, ShardingValue<Long> shardingValue) {
        Collection<String> result = new LinkedHashSet<>(availableTargetNames.size());
        for (Long value : shardingValue.getValues()) {
            if (value <= 20L) {
                result.add(database0Config.getDatabaseName());
            } else {
                result.add(database1Config.getDatabaseName());
            }
        }
        return result;
    }

    @Override
    public Collection<String> doBetweenSharding(Collection<String> availableTargetNames,
                                                ShardingValue<Long> shardingValue) {
        Collection<String> result = new LinkedHashSet<>(availableTargetNames.size());
        Range<Long> range = shardingValue.getValueRange();
        for (Long value = range.lowerEndpoint(); value <= range.upperEndpoint(); value++) {
            if (value <= 20L) {
                result.add(database0Config.getDatabaseName());
            } else {
                result.add(database1Config.getDatabaseName());
            }
        }
        return result;
    }
}

分表和分库类似,无非就是实现的类不一样,实现了SingleKeyTableShardingAlgorithm类,策略使用值奇偶分表,分表算法类TableShardingAlgorithm如代码清单所示。

package com.dalaoyang.config;

import com.dangdang.ddframe.rdb.sharding.api.ShardingValue;
import com.dangdang.ddframe.rdb.sharding.api.strategy.table.SingleKeyTableShardingAlgorithm;
import com.google.common.collect.Range;
import org.springframework.stereotype.Component;

import java.util.Collection;
import java.util.LinkedHashSet;

/**
 * 这里使用的都是单键分片策略
 * 示例分表策略是:
 * GoodsType为奇数使用goods_1表
 * GoodsType为偶数使用goods_0表
 * @author yangyang
 * @date 2019/1/30
 */
@Component
public class TableShardingAlgorithm implements SingleKeyTableShardingAlgorithm<Long> {

    @Override
    public String doEqualSharding(final Collection<String> tableNames, final ShardingValue<Long> shardingValue) {
        for (String each : tableNames) {
            if (each.endsWith(shardingValue.getValue() % 2 + "")) {
                return each;
            }
        }
        throw new IllegalArgumentException();
    }

    @Override
    public Collection<String> doInSharding(final Collection<String> tableNames, final ShardingValue<Long> shardingValue) {
        Collection<String> result = new LinkedHashSet<>(tableNames.size());
        for (Long value : shardingValue.getValues()) {
            for (String tableName : tableNames) {
                if (tableName.endsWith(value % 2 + "")) {
                    result.add(tableName);
                }
            }
        }
        return result;
    }

    @Override
    public Collection<String> doBetweenSharding(final Collection<String> tableNames,
                                                final ShardingValue<Long> shardingValue) {
        Collection<String> result = new LinkedHashSet<>(tableNames.size());
        Range<Long> range = shardingValue.getValueRange();
        for (Long i = range.lowerEndpoint(); i <= range.upperEndpoint(); i++) {
            for (String each : tableNames) {
                if (each.endsWith(i % 2 + "")) {
                    result.add(each);
                }
            }
        }
        return result;
    }
}

3.8 Controller

接下来创建一个Controller进行测试,保存方法使用了插入40条数据,根据我们的规则,会每个库插入20条,同时我这里还创建了三个查询方法,分别是查询全部,between查询,in查询,还有删除全部方法。Controller类代码如下所示。

package com.dalaoyang.controller;

import com.dalaoyang.entity.Goods;
import com.dalaoyang.repository.GoodsRepository;
import com.dangdang.ddframe.rdb.sharding.keygen.KeyGenerator;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RestController;

import java.util.ArrayList;
import java.util.List;

/**
 * @author yangyang
 * @date 2019/1/29
 */
@RestController
public class GoodsController {

    @Autowired
    private KeyGenerator keyGenerator;

    @Autowired
    private GoodsRepository goodsRepository;

    @GetMapping("save")
    public String save(){
        for(int i= 1 ; i <= 40 ; i ++){
            Goods goods = new Goods();
            goods.setGoodsId((long) i);
            goods.setGoodsName( "shangpin" + i);
            goods.setGoodsType((long) (i+1));
            goodsRepository.save(goods);
        }
        return "success";
    }

    @GetMapping("select")
    public String select(){
        return goodsRepository.findAll().toString();
    }

    @GetMapping("delete")
    public void delete(){
         goodsRepository.deleteAll();
    }

    @GetMapping("query1")
    public Object query1(){
        return goodsRepository.findAllByGoodsIdBetween(10L, 30L);
    }

    @GetMapping("query2")
    public Object query2(){
        List<Long> goodsIds = new ArrayList<>();
        goodsIds.add(10L);
        goodsIds.add(15L);
        goodsIds.add(20L);
        goodsIds.add(25L);
        return goodsRepository.findAllByGoodsIdIn(goodsIds);
    }
}

4.测试

启动应用,在浏览器或HTTP请求工具访问http://localhost:8080/save,如图所示,返回success。

接下来在测试一下查询方法,访问http://localhost:8080/select,如图所示,可以看到插入数据没问题。

然后查看一下数据库,首先看database0,如图,每个表都有十条数据,如下所示。

接下来看database1,如下所示。

从上面几张图可以看出分库分表已经按照我们的策略来进行插入,至于其他几个测试这里就不做介绍了,无论是查询和删除都是可以成功的。

5 源码

点击查看更多内容

本文首次发布于慕课网 ,转载请注明出处,谢谢合作

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