ShardingSphere-Proxy 分库分表 简单示例
ShardingSphere-Proxy 分库分表 简单示例
简要说明
对一张简单的订单表数据表进行水平分库分表，拆分2个库，每个库16张表并在新结构在演示常见的增删改查操作
环境配置
设置MySQL
使用docker设置mysql
# 启动两个mysql
docker run --name mysql11 -p 3311:3306 -e MYSQL_ROOT_PASSWORD=root -e MYSQL_ROOT_HOST=% -d mysql:latest
docker run --name mysql12 -p 3312:3306 -e MYSQL_ROOT_PASSWORD=root -e MYSQL_ROOT_HOST=% -d mysql:latest
# 在11上创建数据库demo_ds_0
docker exec -ti mysql11 mysql -u root -p
create database demo_ds_0;
# 在12上创建数据库demo_ds_1
docker exec -ti mysql11 mysql -u root -p
create database demo_ds_1;
ShardingSphere-Proxy 5.0.0 alpha 设置
docker一直不能设置成功，有点奇怪，这里就直接下载使用了
- 1.下载ShardingSphere-Proxy，下载完成后放到自己相应的目录下
- 2.下载MySQL-connect.jar,下载完成后将jar文件放到Sharding根目录的lib目录下
下面需要配置两个文件：server.yaml、config-sharding.yaml,示例如下（配置都有默认示例说明的，相应进行修改即可）
server.yaml
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
######################################################################################################
#
# If you want to configure governance, authorization and proxy properties, please refer to this file.
#
######################################################################################################
#
#governance:
# name: governance_ds
# registryCenter:
# type: ZooKeeper
# serverLists: localhost:2181
# props:
# retryIntervalMilliseconds: 500
# timeToLiveSeconds: 60
# maxRetries: 3
# operationTimeoutMilliseconds: 500
# overwrite: false
authentication:
users:
root:
password: root
sharding:
password: sharding
authorizedSchemas: sharding_db
props:
max-connections-size-per-query: 1
acceptor-size: 16 # The default value is available processors count * 2.
executor-size: 16 # Infinite by default.
proxy-frontend-flush-threshold: 128 # The default value is 128.
# LOCAL: Proxy will run with LOCAL transaction.
# XA: Proxy will run with XA transaction.
# BASE: Proxy will run with B.A.S.E transaction.
proxy-transaction-type: LOCAL
proxy-opentracing-enabled: false
proxy-hint-enabled: false
query-with-cipher-column: true
sql-show: true
check-table-metadata-enabled: false
config-sharding.yaml
######################################################################################################
#
# If you want to connect to MySQL, you should manually copy MySQL driver to lib directory.
#
######################################################################################################
schemaName: sharding_db
dataSourceCommon:
username: root
password: root
connectionTimeoutMilliseconds: 30000
idleTimeoutMilliseconds: 60000
maxLifetimeMilliseconds: 1800000
maxPoolSize: 50
minPoolSize: 1
maintenanceIntervalMilliseconds: 30000
dataSources:
ds_0:
url: jdbc:mysql://127.0.0.1:3311/demo_ds_0?serverTimezone=UTC&useUnicode=true&characterEncoding=utf-8&useSSL=false&allowPublicKeyRetrieval=true
ds_1:
url: jdbc:mysql://127.0.0.1:3312/demo_ds_1?serverTimezone=UTC&useUnicode=true&characterEncoding=utf-8&useSSL=false&allowPublicKeyRetrieval=true
rules:
- !SHARDING
tables:
t_order:
actualDataNodes: ds_${0..1}.t_order_${0..15}
tableStrategy:
standard:
shardingColumn: order_id
shardingAlgorithmName: t_order_inline
# keyGenerateStrategy:
# column: order_id
# keyGeneratorName: snowflake
# t_order_item:
# actualDataNodes: ds_${0..1}.t_order_item_${0..1}
# tableStrategy:
# standard:
# shardingColumn: order_id
# shardingAlgorithmName: t_order_item_inline
# keyGenerateStrategy:
# column: order_item_id
# keyGeneratorName: snowflake
# bindingTables:
# - t_order,t_order_item
defaultDatabaseStrategy:
standard:
shardingColumn: user_id
shardingAlgorithmName: database_inline
# defaultTableStrategy:
# none:
#
shardingAlgorithms:
database_inline:
type: INLINE
props:
algorithm-expression: ds_${user_id % 2}
t_order_inline:
type: INLINE
props:
algorithm-expression: t_order_${order_id % 16}
# t_order_item_inline:
# type: INLINE
# props:
# algorithm-expression: t_order_item_${order_id % 2}
#
# keyGenerators:
# snowflake:
# type: SNOWFLAKE
# props:
# worker-id: 123
OK，一切准备就绪，直接进入sharding的根目录下的bin目录中运行：start.bat即可（也可以在命令行中运行）
# 使用命令行运行可以指定运行端口
./start.bat 13306
成功以后刷刷刷的一排日志打出，没有错误就说明可以运行了
使用mysql命令或者mysqlworkbench连接上sharding，运行下面的SQL语句生成测试的表，运行成功看到日志中一大批SQL语句，
CREATE TABLE IF NOT EXISTS `t_order` (
`order_id` int(11) NOT NULL,
`user_id` int(11) NOT NULL,
PRIMARY KEY (`order_id`)
) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=latin1;
SpringBoot Mybatis配置
需要修改数据库连接配置，大致如下：
# mybatis的config文件位置配置
mybatis.config-location=classpath:mybatis/mybatis-config.xml
# 各个表的xml文件位置配置
mybatis.mapper-locations=classpath:mybatis/mapper/*.xml
mybatis.type-aliases-package=com.neo.model
# 数据库连接信息配置，自行更换数据库，用户名和密码,配置为ShardingSphereProxy
spring.datasource.url=jdbc:mysql://localhost:13306/sharding_db?serverTimezone=UTC&useUnicode=true&characterEncoding=utf-8\
&useSSL=false&allowPublicKeyRetrieval=true
spring.datasource.username=root
spring.datasource.password=root
spring.datasource.driver-class-name=com.mysql.cj.jdbc.Driver
实体类、Mapper设置这里就不详细赘述了，看GitHub上的工程即可
测试类进行测试，代码如下：
package week0802.week0802.mappers;
import com.zaxxer.hikari.HikariDataSource;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.extension.ExtendWith;
import org.mybatis.spring.annotation.MapperScan;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.test.context.junit.jupiter.SpringExtension;
import org.springframework.transaction.annotation.Transactional;
import week0802.week0802.models.Order;
import javax.sql.DataSource;
import java.sql.Connection;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.sql.Statement;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
@SpringBootTest
@ExtendWith(SpringExtension.class)
@MapperScan("week0802.week0802.mappers")
public class OrderMapperTest {
@Autowired
private OrderMapper orderMapper;
/**
* 通过不同的查询条件的传入，可以体会到分库分表是需要设计的
* 一个设计不好，查询难搞
*/
@Test @Transactional
public void test() throws SQLException {
// 通过sharding插入数据，通过sharding自己的日志输出看出插入不同的数据库和表
orderMapper.insertOne(new Order(1L, 1L));
orderMapper.insertOne(new Order(2L, 2L));
// 只传user_id，看到单库进行了所有表的查询
Map<String, Object> condition = new HashMap<>(1);
condition.put("user_id", 1L);
List<Map<String, Object>> orderQuery = orderMapper.query(condition);
assert orderQuery.size() == 1;
for (Map item: orderQuery) {
System.out.println(item.toString());
}
// 只传order_id，看到进行了多库单表的查询
condition = new HashMap<>(1);
condition.put("order_id", 1L);
orderQuery = orderMapper.query(condition);
assert orderQuery.size() == 1;
for (Map item: orderQuery) {
System.out.println(item.toString());
}
// 传入order_id和user_id，看到进行单库单表的查询
condition = new HashMap<>(2);
condition.put("order_id", 2L);
condition.put("user_id", 2L);
orderQuery = orderMapper.query(condition);
assert orderQuery.size() == 1;
for (Map item: orderQuery) {
System.out.println(item.toString());
}
}
}
