利用ShardingSphere-JDBC实现分库分表

利用ShardingSphere-JDBC实现分库分表

1. ShardingSphere概述

1.1 概述

业务发展到一定程度,分库分表是一种必然的要求,分库可以实现资源隔离,分表则可以降低单表数据量,提高访问效率。

分库分表的技术方案,很久以来都有两种理念:

  • 集中式的Proxy,实现MySQL客户端协议,使用户无感知
  • 分布式的Proxy,在代码层面进行增强,实现一个路由程序

这两种方式是各有利弊的,集中式Proxy的好处是业务没有感知,一切交给DBA把控,分布式的Proxy其支持的语言有限,比如本文要提及的ShardingShpere-JDBC就只支持Java。

我们需要了解一点,集中式的Proxy其实现非常复杂,这要从MySQL处理SQL语句的原理说起,因为不是本文要论述的重点,因此只是简单的提及几点:

  1. SQL语句要被Parser解析成抽象语法树
  2. SQL要被优化器解析出执行计划
  3. SQL语句完成解析后,发给存储引擎

因此大部分的中间件都选择了自己实现SQL的解析器和查询优化器,下面是著名的中间件dble的实现示意图:

只要有解析的过程,其性能损耗就是比较可观的,我们也可以认为这是一种重量级的解决方案。

与之形成对比的是ShardingSphere-JDBC,其原理示意图如下:

每一个服务都持有一个Sharing-JDBC,这个JDBC以Jar包的形式提供,基本上可以认为是一个增强版的jdbc驱动,需要一些分库分表的配置,业务开发人员不需要去对代码进行任何的修改。可以很轻松的移植到SpringBoot,ORM等框架上。

但是这个中结构也不是完美的,每一个服务持有一个proxy意味着会在MySQL服务端新建大量的连接,维持连接会增加MySQL服务器的负载,虽然这种负载提升一般无法察觉。

1.2 概念

逻辑表

**

即水平拆分的表的总称。比如订单业务会被拆分成t_order0,t_order1两张表,但是他们同属于一个逻辑表:t_order

绑定表

分片规则一直的主表和子表。比如还是上面的t_order表,其分片键是order_id,其子表t_order_item的分片键也是order_id。在规则配置时将两个表配置成绑定关系,就不会在查询时出现笛卡尔积。

在关联查询时,如果没有绑定关系,则t_order和t_order_item的关联会出现这样一种场景:

select * from t_order0 inner join t_order_item0 on order_id = order_id where order_id in (0, 1);
select * from t_order0 inner join t_order_item1 on order_id = order_id where order_id in (0, 1;
select * from t_order1 inner join t_order_item0 on order_id = order_id where order_id in (0, 1;
select * from t_order1 inner join t_order_item1 on order_id = order_id where order_id in (0, 1;

如果配置了绑定关系,则会精确地定位到order_id所在的表,消除笛卡尔积。

广播表

有一些表是没有分片的必要的,比如省份信息表,全国也就30多条数据,这种表在每一个节点上都是一样的,这种表叫做广播表。

2. 利用SpringBoot实现分库分表

要分库分表首先需要有不同的数据源,我们启动两个mysqld进行,监听3306和3307两个端口,以多实例的形式模拟多数据源。

我们的分库是以用户ID为依据的,分表是以表本身的主键为依据的。下面是一张示意表:

-- 注意,这是逻辑表,实际不存在
create table t_order
(
  order_id bigint not null auto_increment primary key,
  user_id bigint not null,
  name varchar(100)
);

CREATE TABLE `t_order_item` (
  `order_id` bigint(20) NOT NULL,
  `item` varchar(100) DEFAULT NULL,
  `user_id` bigint(20) NOT NULL,
  PRIMARY KEY (`order_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

我现在有两个数据源,每个数据源上根据order_id分成2两表,也就是说每个实例上都应该有这两张表:

create table t_order0
(
  order_id bigint not null auto_increment primary key,
  user_id bigint not null,
  name varchar(100)
);

create table t_order1
(
  order_id bigint not null auto_increment primary key,
  user_id bigint not null,
  name varchar(100)
);

-- 这是广播表,新建在其中一个节点上就可以
CREATE TABLE `t_config` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `user_id` bigint(20) DEFAULT NULL,
  `config` varchar(100) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB;

CREATE TABLE `t_order_item0` (
  `order_id` bigint(20) NOT NULL,
  `item` varchar(100) DEFAULT NULL,
  `user_id` bigint(20) NOT NULL,
  PRIMARY KEY (`order_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

CREATE TABLE `t_order_item1` (
  `order_id` bigint(20) NOT NULL,
  `item` varchar(100) DEFAULT NULL,
  `user_id` bigint(20) NOT NULL,
  PRIMARY KEY (`order_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

利用SpringBoot技术可以很快的构建一个RESTful的Web服务,下面是application.properties的内容:

# 这里要注册所有的数据源
spring.shardingsphere.datasource.names=ds0,ds1

# 这是数据源0的配置
spring.shardingsphere.datasource.ds0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds0.jdbc-url=jdbc:mysql://localhost:3306/test?serverTimezone=GMT%2B8
spring.shardingsphere.datasource.ds0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds0.username=root
spring.shardingsphere.datasource.ds0.password=

# 这是数据源1的配置
spring.shardingsphere.datasource.ds1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds1.jdbc-url=jdbc:mysql://localhost:3307/test?serverTimezone=GMT%2B8
spring.shardingsphere.datasource.ds1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds1.username=root
spring.shardingsphere.datasource.ds1.password=

# 分库策略
# 分库的列是user_id
spring.shardingsphere.sharding.default-database-strategy.standard.sharding-column=user_id
spring.shardingsphere.sharding.default-database-strategy.standard.precise-algorithm-class-name=com.sinosun.demo.sharding.PreciseShardingAlgorithmImpl

# 分表策略
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ds$->{0..1}.t_order$->{0..1}
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.algorithm-expression=t_order$->{order_id % 2}
spring.shardingsphere.sharding.tables.t_order.key-generator.column=order_id
spring.shardingsphere.sharding.tables.t_order.key-generator.type=SNOWFLAKE

spring.shardingsphere.sharding.tables.t_order_item.actual-data-nodes=ds$->{0..1}.t_order_item$->{0..1}
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.algorithm-expression=t_order_item$->{order_id % 2}

spring.shardingsphere.sharding.binding-tables=t_order, t_order_item

# 广播表, 其主节点是ds0
spring.shardingsphere.sharding.broadcast-tables=t_config
spring.shardingsphere.sharding.tables.t_config.actual-data-nodes=ds$->{0}.t_config

spring.jpa.show-sql=true
server.address=10.1.20.96
server.port=8080

这是buid.gradle内容,只列举ShardingSphere相关的:

dependencies {
    compile group: 'org.apache.shardingsphere', name: 'sharding-jdbc-spring-boot-starter', version: '4.0.0-RC1'
    compile group: 'org.apache.shardingsphere', name: 'sharding-jdbc-spring-namespace', version: '4.0.0-RC1'
}

下图是工程的代码结构,供参考:

现在开始列举代码:

Order.java:

**

package com.example.demo.entity;


import javax.persistence.Column;
import javax.persistence.Entity;
import javax.persistence.GeneratedValue;
import javax.persistence.GenerationType;
import javax.persistence.Id;
import javax.persistence.Table;
import java.util.StringJoiner;

@Entity
@Table(name = "t_order")
public class Order {
    @Id
    @GeneratedValue(strategy = GenerationType.IDENTITY)
    private long orderId;

    @Column(name = "user_id")
    private long userId;

    @Column(name = "name")
    private String name;

    public long getOrderId() {
        return orderId;
    }

    public void setOrderId(long orderId) {
        this.orderId = orderId;
    }

    public String getName() {
        return name;
    }

    public void setName(String name) {
        this.name = name;
    }

    public long getUserId() {
        return userId;
    }

    public void setUserId(long userId) {
        this.userId = userId;
    }

    @Override
    public String toString() {
        return new StringJoiner(", ", Order.class.getSimpleName() + "[", "]")
                .add("orderId=" + orderId)
                .add("userId=" + userId)
                .add("name='" + name + "'")
                .toString();
    }
}

OrderItem.java:

**

package com.example.demo.entity;

import com.google.common.base.MoreObjects;

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

@Entity
@Table(name = "t_order_item")
public class OrderItem {
    @Id
    @Column(name = "order_id")
    private long orderId;

    @Column(name = "user_id")
    private long userId;

    @Column(name = "item")
    private String item;

    public long getOrderId() {
        return orderId;
    }

    public void setOrderId(long orderId) {
        this.orderId = orderId;
    }

    public long getUserId() {
        return userId;
    }

    public void setUserId(long userId) {
        this.userId = userId;
    }

    public String getItem() {
        return item;
    }

    public void setItem(String item) {
        this.item = item;
    }

    @Override
    public String toString() {
        return MoreObjects.toStringHelper(this)
                .add("orderId", orderId)
                .add("userId", userId)
                .add("item", item)
                .toString();
    }
}

TConfig.java:

**

package com.example.demo.entity;

import com.google.common.base.MoreObjects;

import javax.persistence.Column;
import javax.persistence.Entity;
import javax.persistence.GeneratedValue;
import javax.persistence.GenerationType;
import javax.persistence.Id;
import javax.persistence.Table;

@Entity
@Table(name = "t_config")
public class TConfig {
    @Id
    @GeneratedValue(strategy = GenerationType.IDENTITY)
    private int id;

    @Column(name = "user_id")
    private long userId;

    @Column(name = "config")
    private String config;

    public int getId() {
        return id;
    }

    public void setId(int id) {
        this.id = id;
    }

    public long getUserId() {
        return userId;
    }

    public void setUserId(long userId) {
        this.userId = userId;
    }

    public String getConfig() {
        return config;
    }

    public void setConfig(String config) {
        this.config = config;
    }

    @Override
    public String toString() {
        return MoreObjects.toStringHelper(this)
                .add("id", id)
                .add("userId", userId)
                .add("config", config)
                .toString();
    }
}

OrderDao.java:

**

package com.example.demo.dao;

import com.example.demo.entity.Order;
import org.springframework.data.jpa.repository.JpaRepository;

public interface OrderDao extends JpaRepository<Order, Long> {
}

OrderItemDao.java:

**

package com.example.demo.dao;

import com.example.demo.entity.OrderItem;
import org.springframework.data.jpa.repository.JpaRepository;
import org.springframework.data.jpa.repository.Query;
import org.springframework.data.repository.query.Param;

import java.util.Optional;

public interface OrderItemDao extends JpaRepository<OrderItem, Long> {
    //为了测试绑定表
    @Query(value = "select n from Order t inner join OrderItem n on t.orderId = n.orderId where n.orderId=:orderId")
    Optional<OrderItem> getOrderItemByOrderId(@Param("orderId") Long orderId);
}

ConfigDao.java:

**

package com.example.demo.dao;

import com.sinosun.demo.entity.TConfig;
import org.springframework.data.jpa.repository.JpaRepository;

public interface ConfigDao extends JpaRepository<TConfig, Integer> {
}

OrderController.java:

**

package com.example.demo.controller;

import com.example.demo.dao.OrderDao;
import com.example.demo.entity.Order;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestMethod;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;

import java.util.Optional;

@RestController
public class OrderController {
    @Autowired
    private OrderDao orderDao;

    @RequestMapping(value = "/order", method = RequestMethod.GET)
    public Optional<Order> getOrderById(@RequestParam("id") Long id) {
        return this.orderDao.findById(id);
    }

    @RequestMapping(value = "/order/save", method = RequestMethod.POST)
    public Order saveOrder(@RequestParam("name") String name, @RequestParam("userid") Long userId) {
        Order order = new Order();
        order.setName(name);
        order.setUserId(userId);
        return this.orderDao.save(order);
    }
}

OrderItemController.java:

**

package com.example.demo.controller;

import com.example.demo.dao.OrderItemDao;
import com.example.demo.entity.OrderItem;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestMethod;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;

import java.util.Optional;

@RestController
public class OrderItemController {
    @Autowired
    private OrderItemDao orderItemDao;

    @RequestMapping(value = "/orderItem", method = RequestMethod.GET)
    public Optional<OrderItem> getOrderItemById(@RequestParam(name = "id") Long id) {
        return this.orderItemDao.findById(id);
    }

    @RequestMapping(value = "/orderItem/save", method = RequestMethod.POST)
    public OrderItem saveOrderItem(@RequestParam("item") String item, @RequestParam("userid") Long userId, @RequestParam("orderid") Long orderId) {
        OrderItem orderItem = new OrderItem();
        orderItem.setUserId(userId);
        orderItem.setItem(item);
        orderItem.setOrderId(orderId);
        return this.orderItemDao.save(orderItem);
    }

    @RequestMapping(value = "/orderItem/query", method = RequestMethod.GET)
    public Optional<OrderItem> getOrderItemByOrderId(@RequestParam(name = "orderid") Long orderId) {
        return this.orderItemDao.getOrderItemByOrderId(orderId);
    }
}

ConfigController.java:

**

package com.example.demo.controller;

import com.example.demo.dao.ConfigDao;
import com.example.demo.entity.TConfig;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestMethod;
import org.springframework.web.bind.annotation.RestController;

import java.util.List;

@RestController
public class ConfigController {
    @Autowired
    private ConfigDao configDao;

    @RequestMapping(value = "/listConfig", method = RequestMethod.GET)
    public List<TConfig> getConfig() {
        return this.configDao.findAll();
    }
}

这三段代码写完基本的功能就完备了,但是刚才配置的时候提过,我们的目的是按照user_id进行分库,比如user_id=0则分配这条数据到ds0去,如果为1则将数据分配到ds1去,这就要求我们自己实现分库的算法,ShardingSphere提供了接口,只需要去实现就可以了:

package com.example.demo.sharding;

import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingValue;

import java.util.Collection;

public class PreciseShardingAlgorithmImpl implements PreciseShardingAlgorithm<Long> {

    @Override
    public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<Long> shardingValue) {
        String dbName = "ds";
        Long val = shardingValue.getValue();
        dbName += val;
        for (String each : availableTargetNames) {
            if (each.equals(dbName)) {
                return each;
            }
        }
        throw new IllegalArgumentException();
    }
}

这段代码很简单,其中有几个地方只需要讲明白了就可以。

  • availableTargetNames:这是datasource的名字列表,在这里应该是ds0和ds1;
  • shardingValue:这是分片列的值,我们只要其value部分就可以。

之后用一个循环遍历["ds0", "ds1"]集合,当我们的dbName和其中一个相等时,就能的到正确的数据源。这就简单的实现了根据user_id精确分配数据的目的。

这是实测例子中,shardingValue和availableTargetNames的实际值:

本次测试的请求是:

curl -X POST \
  'http://10.1.20.96:8080/order/save?name=LiLei&userid=0' \
  -H 'Postman-Token: d5e15e85-c760-4252-a7d4-ef57b5e95c2e' \
  -H 'cache-control: no-cache'

下面看看实际效果,这是ds0的数据:

这是ds1的数据:

可以看到,所有的数据都根据user_id分布到了不同的库中,所有的数据都根据order_id的奇偶分布到了不同的表中。

记录下保存t_order请求返回的order_id,组装一条POST请求写t_order_item表:

curl -X POST \
  'http://10.1.20.96:8080/orderItem/save?item=pen&userid=0&orderid=371698107924086785' \
  -H 'Accept: */*' \
  -H 'Cache-Control: no-cache' \
  -H 'Connection: keep-alive' \
  -H 'Host: 10.1.20.96:8080' \
  -H 'Postman-Token: 347b6c4d-0e2c-474f-b53e-6f0994db5871,24b362da-e77e-4b04-94e1-fa20dcb15845' \
  -H 'User-Agent: PostmanRuntime/7.15.0' \
  -H 'accept-encoding: gzip, deflate' \
  -H 'cache-control: no-cache' \
  -H 'content-length: '

得到结果如下:

使用这个order_id去进行联合查询:

curl -X GET \
  'http://10.1.20.96:8080/orderItem/query?orderid=371698107924086785' \
  -H 'Accept: */*' \
  -H 'Cache-Control: no-cache' \
  -H 'Connection: keep-alive' \
  -H 'Host: 10.1.20.96:8080' \
  -H 'Postman-Token: d0da0523-d46e-429f-a8db-9f844cd77fe6,b61c6089-253d-4535-b473-158c037850be' \
  -H 'User-Agent: PostmanRuntime/7.15.0' \
  -H 'accept-encoding: gzip, deflate' \
  -H 'cache-control: no-cache'

得到返回如下:

测试广播表,可以用下面的请求:

curl -X GET \
  http://10.1.20.96:8080/listConfig \
  -H 'Accept: */*' \
  -H 'Cache-Control: no-cache' \
  -H 'Connection: keep-alive' \
  -H 'Host: 10.1.20.96:8080' \
  -H 'Postman-Token: 1c9d0349-4b6d-4a2c-834f-4e2f94194649,3dff68f4-2e10-4e96-926a-344faa5f0a19' \
  -H 'User-Agent: PostmanRuntime/7.15.0' \
  -H 'accept-encoding: gzip, deflate' \
  -H 'cache-control: no-cache'

得到的结果:

3. 利用SpringBoot实现读写分离

上一小节中展示了如何利用SharingSphere+SpringBoot进行数据的分片,这一小节着重描述一下如何进行读写分离,下一小节计划展示如何将读写分离和分片结合起来。

首先还是会利用多实例来模拟,为了简单,我没有配置复制,而是预置了几条数据进去,判断能否将读写请求分发到不同的节点上。

首先我们新建一张表:

create table t_order
(
  order_id bigint not null auto_increment primary key,
  user_id bigint not null,
  name varchar(100)
);

-- master
insert into t_order(user_id, name) values (0, 'zhiquan');

-- slave 
insert into t_order(user_id, name) values (1, 'LiLei');

我会配置slave为读数据源,那么读出的数据一定是user_id=1这一条。

数据是这样的,首先是master:

然后是slave:

接下来开始粘贴代码,首先是配置:

application.properties:

**

spring.shardingsphere.datasource.names=ds0,ds1

spring.shardingsphere.datasource.ds0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds0.jdbc-url=jdbc:mysql://localhost:3306/test?serverTimezone=GMT%2B8
spring.shardingsphere.datasource.ds0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds0.username=root
spring.shardingsphere.datasource.ds0.password=

spring.shardingsphere.datasource.ds1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds1.jdbc-url=jdbc:mysql://localhost:3307/test?serverTimezone=GMT%2B8
spring.shardingsphere.datasource.ds1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds1.username=root
spring.shardingsphere.datasource.ds1.password=

spring.shardingsphere.masterslave.name=ms
spring.shardingsphere.masterslave.master-data-source-name=ds0
spring.shardingsphere.masterslave.slave-data-source-names=ds1

server.port=8080
spring.jpa.show-sql=true

具体的实现代码就不粘贴了,和之前的小节没有什么区别。下面开始测试,首先是一个GET请求:

curl -X GET \
  'http://localhost:8080/getOrder?orderId=2' \
  -H 'Accept: */*' \
  -H 'Accept-Encoding: gzip, deflate' \
  -H 'Cache-Control: no-cache' \
  -H 'Connection: keep-alive' \
  -H 'Host: localhost:8080' \
  -H 'Postman-Token: 028a4539-a727-47f2-8862-2eed637883d0,ffbe396f-5c33-4266-a00e-d2a0246283f3' \
  -H 'User-Agent: PostmanRuntime/7.15.2' \
  -H 'cache-control: no-cache'

如上图,和预期是一样的,读取到了slave上的数据,那么现在看看写操作:

curl -X POST \
  'http://localhost:8080/saveOrder?userId=123&name=HanMeimei' \
  -H 'Accept: */*' \
  -H 'Accept-Encoding: gzip, deflate' \
  -H 'Cache-Control: no-cache' \
  -H 'Connection: keep-alive' \
  -H 'Content-Length: ' \
  -H 'Host: localhost:8080' \
  -H 'Postman-Token: f0497259-a82a-4dcf-9849-3dcdae431742,77fd1308-b5e8-4882-be07-fa128e6efc4d' \
  -H 'User-Agent: PostmanRuntime/7.15.2' \
  -H 'cache-control: no-cache'

现在看看主节点的表:

如上图,这条数据已经成功的写入了master。

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