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分库分表之第二篇

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2. Sharding-JDBC快速入门

2.1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。人工创建两张表,t_order_1和t_order_2,这张表是订单表替换后的表,通过Shading-JDBC向订单表插入数据,按照一定的分片规则,主键为偶数的尽入t_order_1,另一部分数据进入t_order_2,通过Shading-Jdbc查询数据,根据SQL语句的内容从t_order_1或order_2查询数据。

2.2. 环境建设

2.2.1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

2.2.2创建数据库

创建订单表

CREATE DATABASE`order_db`字符集‘UTF8‘COLLATE‘utf8_general_ci‘; ```在order_db中创建t_order_1,t_order_2表如果存在java DROP TABLE t_order_1; CREATE TABLE`t_order_1`(`order_id` BIGINT(20)非空注释‘订单ID‘,`price`十进制(10,2)非空注释‘订单价格‘,`user_id` BIGINT(20)非空注释“下一个单用户id”,“状态” varchar(50)字符集utf8集合utf8_general_ci NOT NULL COMMENT“订单状态”,主键(`order_id`)使用BTREE)引擎= InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = 如果存在表t_order_2; CREATE TABLE`t_order_2`(`order_id` BIGINT(20)非空注释‘订单ID‘,`price`十进制(10,2)非空注释‘订单价格‘,`user_id` BIGINT(20)非空注释‘下一个单用户id‘,`status` varchar(50)字符集utf8集合utf8_general_ci NOT NULL COMMENT‘订单状态‘,主键(`order_id`)使用BTREE 
)ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT =动态; 

2.2.3约会maven依赖

sharding-jdbc和SpringBoot整合的Jar包:

<dependency>
<groupId>org.apache.shardingsphere</groupId> 
<artifactId>sharding‐jdbc‐spring‐boot‐starter</artifactId> 
<version>4.0.0‐RC1</version>
   </dependency>

2.3 编写程序

2.3.1 分片规则配置

分片规则配置是sharding-jdbc进行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 = debug
  1. 首先定义数据源m1,并对m1进行实际的参数配置
  2. 指定t_order表的数据分布情况,它分布在m1.t_order_1、m1.t_order_2
  3. 指定t_order表的主键生成策略为SNOWFLAKE,SNOWFLAKE是一种分布式自增算法,保证id全局唯一
  4. 定义t_order分片策略,order_id为偶数的数据落在t_order_1,为奇数的落在t_order_2,分表策略的表达式为t_order_$->{order_id % 2 + 1}

2.3.2 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({"<script>" + "select " +
	"*"+
	" from t_order t" +
	" where t.order_id in " +
	"<foreach collection=‘orderIds‘ item=‘id‘ open=‘(‘ separator=‘,‘ close=‘)‘>" + " #{id} " +
	"</foreach>"+
	"</script>"})
	List<Map> selectOrderbyIds(@Param("orderIds")List<Long> orderIds); 
}

2.3.3 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<Long> ids = new ArrayList<>(); ids.add(373771636085620736L); ids.add(373771635804602369L);
		List<Map> maps = orderDao.selectOrderbyIds(ids); System.out.println(maps);
	} 
}

执行testInsertOrder:
技术图片
通过日志可以发现order_id为奇数的被插入到t_order_2表,为偶数的被插入到t_order_1表,达到预期目标。
执行testSelectOrderbyIds:
技术图片
通过日志可以发现,根据传入的order_id的奇偶不同,分片-JDBC分别去不同的表检索数据,达到预期目标。

2.4. 流程分析

通过日志分析,Sharding-JDBC在拿到用户要执行的sql之后干了那些事儿 :
(1)解析sql,获取片键值,在本例中是order_id
(2)Sharding-JDBC通过规则配置t_order_$->{order_id% 2 + 1},知道类当order_id为偶数时,应该往t_order_1表插数据,为奇数时,往t_order_2插数据。
(3)于是Sharding-JDBC根据order_id的值改写sql语句,改写后的SQL语句是真实所要执行的SQL语句。
(4)执行改写后的真实sql语句
(5)将所有真正执行sql的结果进行汇总合并,返回。

2.5 其他集成方式

Sharding-JDBC不仅可以与Spring boot良好集成,它还支持其他配置方式,共支持以下四种集成方式。
Spring Boot Yaml配置
定义application.yml,内容如下 :

server:
     port: 56081
     servlet:
context‐path: /sharding‐jdbc‐simple‐demo spring:
application:
name: sharding‐jdbc‐simple‐demo
     http:
       encoding:
enabled: true charset: utf‐8 force: true
main:
allow‐bean‐definition‐overriding: true
     shardingsphere:
       datasource:
         names: m1
m1:
type: com.alibaba.druid.pool.DruidDataSource driverClassName: com.mysql.jdbc.Driver
url: jdbc:mysql://localhost:3306/order_db?useUnicode=true username: root
password: mysql
       sharding:
         tables:
t_order:
actualDataNodes: m1.t_order_$‐>{1..2} tableStrategy:
inline:
shardingColumn: order_id
algorithmExpression: t_order_$‐>{order_id % 2 + 1}
             keyGenerator:
               type: SNOWFLAKE
               column: order_id
props: sql:
           show: true
   mybatis:
configuration: map‐underscore‐to‐camel‐case: true
   swagger:
     enable: true
   logging:
     level:
root: info
 org.springframework.web: info 
 com.itheima.dbsharding: debug 
 druid.sql: debug

如果使用application.yml则需要屏蔽原来的application.properties文件。
Java配置
添加配置类 :

@Configuration
   public class ShardingJdbcConfig {
// 定义数据源
Map<String, DataSource> createDataSourceMap() {
DruidDataSource dataSource1 = new DruidDataSource(); dataSource1.setDriverClassName("com.mysql.jdbc.Driver"); dataSource1.setUrl("jdbc:mysql://localhost:3306/order_db?useUnicode=true"); dataSource1.setUsername("root");
dataSource1.setPassword("root");
Map<String, DataSource> result = new HashMap<>(); result.put("m1", dataSource1);
return result;
}
// 定义主键生成策略
private static KeyGeneratorConfiguration getKeyGeneratorConfiguration() {
KeyGeneratorConfiguration result = new KeyGeneratorConfiguration("SNOWFLAKE","order_id");
           return result;
       }
// 定义t_order表的分片策略
TableRuleConfiguration getOrderTableRuleConfiguration() {
TableRuleConfiguration result = new TableRuleConfiguration("t_order","m1.t_order_$‐> {1..2}");
result.setTableShardingStrategyConfig(new InlineShardingStrategyConfiguration("order_id", "t_order_$‐>{order_id % 2 + 1}"));
result.setKeyGeneratorConfig(getKeyGeneratorConfiguration()); return result;
}
// 定义sharding‐Jdbc数据源
@Bean
DataSource getShardingDataSource() throws SQLException {
ShardingRuleConfiguration shardingRuleConfig = new ShardingRuleConfiguration(); shardingRuleConfig.getTableRuleConfigs().add(getOrderTableRuleConfiguration()); //spring.shardingsphere.props.sql.show = true
Properties properties = new Properties();
properties.put("sql.show","true");
return ShardingDataSourceFactory.createDataSource(createDataSourceMap(),
     shardingRuleConfig,properties);
       }
}

由于采用类配置类所以需要屏蔽原来application.properties文件中spring.shardingsphere开头的配置信息。还需要在SpringBoot启动类中屏蔽使用spring.shardingsphere配置项的类 :

@SpringBootApplication(exclude = {SpringBootConfiguration.class}) public class ShardingJdbcSimpleDemoBootstrap {....}

Spring命名空间配置 此方式使用xml方式配置,不推荐使用。

<?xml version="1.0" encoding="UTF‐8"?>
<beans xmlns="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema‐instance" xmlns:p="http://www.springframework.org/schema/p" xmlns:context="http://www.springframework.org/schema/context" xmlns:tx="http://www.springframework.org/schema/tx"
   xmlns:sharding="http://shardingsphere.apache.org/schema/shardingsphere/sharding"
    xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring‐beans.xsd
http://shardingsphere.apache.org/schema/shardingsphere/sharding
http://shardingsphere.apache.org/schema/shardingsphere/sharding/sharding.xsd http://www.springframework.org/schema/context
http://www.springframework.org/schema/context/spring‐context.xsd http://www.springframework.org/schema/tx http://www.springframework.org/schema/tx/spring‐tx.xsd">
<context:annotation‐config />
<!‐‐定义多个数据源‐‐>
<bean id="m1" class="com.alibaba.druid.pool.DruidDataSource" destroy‐method="close">
<property name="driverClassName" value="com.mysql.jdbc.Driver" />
<property name="url" value="jdbc:mysql://localhost:3306/order_db_1?useUnicode=true" /> 
<property name="username" value="root" />
<property name="password" value="root" />
</bean>
<!‐‐定义分库策略‐‐>
<sharding:inline‐strategy id="tableShardingStrategy" sharding‐column="order_id" algorithm‐
expression="t_order_$‐>{order_id % 2 + 1}" /> 
<!‐‐定义主键生成策略‐‐>
<sharding:key‐generator id="orderKeyGenerator" type="SNOWFLAKE" column="order_id" />
<!‐‐定义sharding‐Jdbc数据源‐‐> <sharding:data‐source id="shardingDataSource">
<sharding:sharding‐rule data‐source‐names="m1"> 
<sharding:table‐rules>
<sharding:table‐rule logic‐table="t_order" table‐strategy‐ ref="tableShardingStrategy" key‐generator‐ref="orderKeyGenerator" />
</sharding:table‐rules> 
</sharding:sharding‐rule>
</sharding:data‐source> 
</beans>

分库分表之第二篇

标签:core   存在   xmlns   www   启动   oid   deb   rri   maven   

原文地址:https://www.cnblogs.com/haizai/p/12079273.html

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