Mybatis + Sharding JDBC分库分表
1 水平分表
1.1需求说明
使用Sharding-JDBC完成对订单表的水平分表，通过快速入门程序的开发，快速体验Sharding-JDBC的使用 方法。 人工创建两张表，t_order_1和t_order_2，这两张表是订单表拆分后的表，通过Sharding-Jdbc向订单表插入数据， 按照一定的分片规则，主键为偶数的进入t_order_1，另一部分数据进入t_order_2，通过Sharding-Jdbc 查询数 据，根据 SQL语句的内容从t_order_1或t_order_2查询数据。
1.2.环境搭建
1.2.1 环境说明
操作系统：Win10
数据库：MySQL-5.7.25
JDK：64位 jdk1.8.0_201
应用框架：spring-boot-2.1.3.RELEASE，Mybatis3.5.0
Sharding-JDBC：sharding-jdbc-spring-boot-starter-4.0.0-RC1
1.2.2 创建数据库
创建订单库order_db
CREATE DATABASE `order_db` CHARACTER SET 'utf8' COLLATE 'utf8_general_ci';在order_db中创建t_order_1、t_order_2表
DROP TABLE IF EXISTS `t_order_1`;
CREATE TABLE `t_order_1` (
`order_id` bigint(20) NOT NULL COMMENT '订单id',
`price` decimal(10, 2) NOT NULL COMMENT '订单价格',
`user_id` bigint(20) NOT NULL COMMENT '下单用户id',
`status` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '订单状态',
PRIMARY KEY (`order_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;
DROP TABLE IF EXISTS `t_order_2`;
CREATE TABLE `t_order_2` (
`order_id` bigint(20) NOT NULL COMMENT '订单id',
`price` decimal(10, 2) NOT NULL COMMENT '订单价格',
`user_id` bigint(20) NOT NULL COMMENT '下单用户id',
`status` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '订单状态',
PRIMARY KEY (`order_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;1.2.3.引入maven依赖
引入 sharding-jdbc和SpringBoot整合的Jar包：
org.apache.shardingsphere
sharding‐jdbc‐spring‐boot‐starter
4.0.0‐RC1
1.3 编写程序
1.3.1 分片规则配置
分片规则配置是sharding-jdbc进行对分库分表操作的重要依据，配置内容包括：数据源、主键生成策略、分片策 略等。
在application.properties中配置
server.port=56081
spring.application.name = sharding‐jdbc‐simple‐demo
server.servlet.context‐path = /sharding‐jdbc‐simple‐demo
spring.http.encoding.enabled = true
spring.http.encoding.charset = UTF‐8
spring.http.encoding.force = true
spring.main.allow‐bean‐definition‐overriding = true
mybatis.configuration.map‐underscore‐to‐camel‐case = true
# 以下是分片规则配置
# 定义数据源
spring.shardingsphere.datasource.names = m1
spring.shardingsphere.datasource.m1.type = com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m1.driver‐class‐name = com.mysql.jdbc.Driver
spring.shardingsphere.datasource.m1.url = jdbc:mysql://localhost:3306/order_db?useUnicode=true
spring.shardingsphere.datasource.m1.username = root
spring.shardingsphere.datasource.m1.password = root
# 指定t_order表的数据分布情况，配置数据节点
spring.shardingsphere.sharding.tables.t_order.actual‐data‐nodes = m1.t_order_$‐>{1..2}
# 指定t_order表的主键生成策略为SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order.key‐generator.column=order_id
spring.shardingsphere.sharding.tables.t_order.key‐generator.type=SNOWFLAKE
# 指定t_order表的分片策略，分片策略包括分片键和分片算法
spring.shardingsphere.sharding.tables.t_order.table‐strategy.inline.sharding‐column = order_id
spring.shardingsphere.sharding.tables.t_order.table‐strategy.inline.algorithm‐expression =
t_order_$‐>{order_id % 2 + 1}
# 打开sql输出日志
spring.shardingsphere.props.sql.show = true
swagger.enable = true
logging.level.root = info
logging.level.org.springframework.web = info
logging.level.com.itheima.dbsharding = debug
logging.level.druid.sql = debug1.3.2.数据操作
@Mapper
@Component
public interface OrderDao {
/**
* 新增订单
* @param price 订单价格
* @param userId 用户id
* @param status 订单状态
* @return
*/
@Insert("insert into t_order(price,user_id,status) value(#{price},#{userId},#
{status})")
int insertOrder(@Param("price") BigDecimal price, @Param("userId")Long userId,
@Param("status")String status);
/**
* 根据id列表查询多个订单
* @param orderIds 订单id列表
* @return
*/
@Select({""})
List1.3.3.测试
编写单元测试：
@RunWith(SpringRunner.class)
@SpringBootTest(classes = {ShardingJdbcSimpleDemoBootstrap.class})
public class OrderDaoTest {
@Autowired
private OrderDao orderDao;
@Test
public void testInsertOrder(){
for (int i = 0 ; i<10; i++){
orderDao.insertOrder(new BigDecimal((i+1)*5),1L,"WAIT_PAY");
}
}
@Test
public void testSelectOrderbyIds(){
List ids = new ArrayList<>();
ids.add(373771636085620736L);
ids.add(373771635804602369L);
List 2. 水平分库
水平分库是把同一个表的数据按一定规则拆到不同的数据库中，每个库可以放在不同的服务器 上。
2.1 创建数据库
将原有order_db库拆分为order_db_1、order_db_2
2.2 分片规则修改
由于数据库拆分了两个，这里需要配置两个数据源。
分库需要配置分库的策略，和分表策略的意义类似，通过分库策略实现数据操作针对分库的数据库进行操作。
server.port=56081
spring.application.name = sharding-jdbc-simple-demo
server.servlet.context-path = /sharding-jdbc-simple-demo
spring.http.encoding.enabled = true
spring.http.encoding.charset = UTF-8
spring.http.encoding.force = true
spring.main.allow-bean-definition-overriding = true
mybatis.configuration.map-underscore-to-camel-case = true
#sharding-jdbc分片规则配置
#数据源
spring.shardingsphere.datasource.names = m1,m2
spring.shardingsphere.datasource.m1.type = com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m1.driver-class-name = com.mysql.jdbc.Driver
spring.shardingsphere.datasource.m1.url = jdbc:mysql://localhost:3306/order_db_1?useUnicode=true
spring.shardingsphere.datasource.m1.username = root
spring.shardingsphere.datasource.m1.password = root
spring.shardingsphere.datasource.m2.type = com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m2.driver-class-name = com.mysql.jdbc.Driver
spring.shardingsphere.datasource.m2.url = jdbc:mysql://localhost:3306/order_db_2?useUnicode=true
spring.shardingsphere.datasource.m2.username = root
spring.shardingsphere.datasource.m2.password = root
# 分库策略，以user_id为分片键，分片策略为user_id % 2 + 1，user_id为偶数操作m1数据源，否则操作m2。
spring.shardingsphere.sharding.tables.t_order.database-strategy.inline.sharding-column = user_id
spring.shardingsphere.sharding.tables.t_order.database-strategy.inline.algorithm-expression = m$->{user_id % 2 + 1}
# 指定t_order表的数据分布情况，配置数据节点 m1.t_order_1,m1.t_order_2,m2.t_order_1,m2.t_order_2
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes = m$->{1..2}.t_order_$->{1..2}
# 指定t_order表的主键生成策略为SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order.key-generator.column=order_id
spring.shardingsphere.sharding.tables.t_order.key-generator.type=SNOWFLAKE
# 指定t_order表的分片策略，分片策略包括分片键和分片算法
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.sharding-column = order_id
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.algorithm-expression = t_order_$->{order_id % 2 + 1}
# 打开sql输出日志
spring.shardingsphere.props.sql.show = true
swagger.enable = true
logging.level.root = info
logging.level.org.springframework.web = info
logging.level.com.itheima.dbsharding = debug
logging.level.druid.sql = debug
2.3 插入测试
修改testInsertOrder方法，插入数据中包含不同的user_id
@Test
public void testInsertOrder(){
for (int i = 0 ; i<10; i++){
orderDao.insertOrder(new BigDecimal((i+1)*5),1L,"WAIT_PAY");
}
for (int i = 0 ; i<10; i++){
orderDao.insertOrder(new BigDecimal((i+1)*10),2L,"WAIT_PAY");
}
}
2.4 查询测试
调用快速入门的查询接口进行测试：
List@Test
public void testSelectOrderbyUserAndIds(){
List orderIds = new ArrayList<>();
orderIds.add(373422416644276224L);
orderIds.add(373422415830581248L);
//查询条件中包括分库的键user_id
int user_id = 1;
List 3. 垂直分库
垂直分库是指按照业务将表进行分类，分布到不同的数据库上面，每个库可以放在不同的服务器 上，它的核心理念是专库专用。
3.1 创建数据库
创建数据库user_db
CREATE DATABASE `user_db` CHARACTER SET 'utf8' COLLATE 'utf8_general_ci';在user_db中创建t_user表
DROP TABLE IF EXISTS `t_user`;
CREATE TABLE `t_user` (
`user_id` bigint(20) NOT NULL COMMENT '用户id',
`fullname` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '用户姓名',
`user_type` char(1) DEFAULT NULL COMMENT '用户类型',
PRIMARY KEY (`user_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;
3.2 在Sharding-JDBC规则中修改
server.port=56081
spring.application.name = sharding-jdbc-simple-demo
server.servlet.context-path = /sharding-jdbc-simple-demo
spring.http.encoding.enabled = true
spring.http.encoding.charset = UTF-8
spring.http.encoding.force = true
spring.main.allow-bean-definition-overriding = true
mybatis.configuration.map-underscore-to-camel-case = true
#sharding-jdbc分片规则配置
#数据源
spring.shardingsphere.datasource.names = m0,m1,m2
spring.shardingsphere.datasource.m0.type = com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m0.driver-class-name = com.mysql.jdbc.Driver
spring.shardingsphere.datasource.m0.url = jdbc:mysql://localhost:3306/user_db?useUnicode=true
spring.shardingsphere.datasource.m0.username = root
spring.shardingsphere.datasource.m0.password = root
spring.shardingsphere.datasource.m1.type = com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m1.driver-class-name = com.mysql.jdbc.Driver
spring.shardingsphere.datasource.m1.url = jdbc:mysql://localhost:3306/order_db_1?useUnicode=true
spring.shardingsphere.datasource.m1.username = root
spring.shardingsphere.datasource.m1.password = root
spring.shardingsphere.datasource.m2.type = com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m2.driver-class-name = com.mysql.jdbc.Driver
spring.shardingsphere.datasource.m2.url = jdbc:mysql://localhost:3306/order_db_2?useUnicode=true
spring.shardingsphere.datasource.m2.username = root
spring.shardingsphere.datasource.m2.password = root
# 分库策略，以user_id为分片键，分片策略为user_id % 2 + 1，user_id为偶数操作m1数据源，否则操作m2。
spring.shardingsphere.sharding.tables.t_order.database-strategy.inline.sharding-column = user_id
spring.shardingsphere.sharding.tables.t_order.database-strategy.inline.algorithm-expression = m$->{user_id % 2 + 1}
# 指定t_order表的数据分布情况，配置数据节点 m1.t_order_1,m1.t_order_2,m2.t_order_1,m2.t_order_2
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes = m$->{1..2}.t_order_$->{1..2}
spring.shardingsphere.sharding.tables.t_user.actual-data-nodes = m$->{0}.t_user
# 指定t_order表的主键生成策略为SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order.key-generator.column=order_id
spring.shardingsphere.sharding.tables.t_order.key-generator.type=SNOWFLAKE
# 指定t_order表的分片策略，分片策略包括分片键和分片算法
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 + 1}
spring.shardingsphere.sharding.tables.t_user.table-strategy.inline.sharding-column = user_id
spring.shardingsphere.sharding.tables.t_user.table-strategy.inline.algorithm-expression = t_user
# 打开sql输出日志
spring.shardingsphere.props.sql.show = true
swagger.enable = true
logging.level.root = info
logging.level.org.springframework.web = info
logging.level.com.itheima.dbsharding = debug
logging.level.druid.sql = debug
3.3 数据操作
新增UserDao:
@Mapper
@Component
public interface UserDao {
/**
* 新增用户
* @param userId 用户id
* @param fullname 用户姓名
* @return
*/
@Insert("insert into t_user(user_id, fullname) value(#{userId},#{fullname})")
int insertUser(@Param("userId")Long userId,@Param("fullname")String fullname);
/**
* 根据id列表查询多个用户
* @param userIds 用户id列表
* @return
*/
@Select({""
})
List3.4 测试
新增单元测试方法
@Test
public void testInsertUser(){
for (int i = 0 ; i<10; i++){
Long id = i + 1L;
userDao.insertUser(id,"姓名"+ id );
}
}
@Test
public void testSelectUserbyIds(){
List userIds = new ArrayList<>();
userIds.add(1L);
userIds.add(2L);
List