Sharding-jdbc整合综合案例

数据库设计
数据库设计如下，其中商品与店铺信息之间进行了垂直分库，分为了PRODUCT_DB(商品库)和STORE_DB(店铺
库)；商品信息还进行了垂直分表，分为了商品基本信息(product_info)和商品描述信息(product_descript)，地理区
域信息(region)作为公共表，冗余在两库中：

考虑到商品信息的数据增长性，对PRODUCT_DB(商品库)进行了水平分库，分片键使用店铺id，分片策略为店铺
ID%2 + 1，因此商品描述信息对所属店铺ID进行了冗余；
对商品基本信息(product_info)和商品描述信息(product_descript)进行水平分表，分片键使用商品id，分片策略为
商品ID%2 + 1,并将为这两个表设置为绑定表，避免笛卡尔积join；
为避免主键冲突，ID生成策略采用雪花算法来生成全局唯一ID，最终数据库设计为下图：

初始化数据库
创建store_db数据库，并执行以下脚本创建表：

DROP TABLE IF EXISTS `region`;
CREATE TABLE `region`(
`id` bigint(20) NOT NULL COMMENT 'id',
`region_code`varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '地理区域编码',
`region_name`varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '地理区域名称',
`level` tinyint(1) NULL DEFAULT NULL COMMENT '地理',
`parent_region_code` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT'上级地理区域编码',
PRIMARY KEY (`id`) USING BTREE
)ENGINE=InnoDB CHARACTER SET=utf8 COLLATE=utf8_general_ci ROW_FORMAT=Dynamic;

INSERT INTO `region` VALUES(1,'110000','北京',0,NULL);
INSERT INTO `region` VALUES(2,'410000','河南省',0,NULL);
INSERT INTO `region` VALUES(3,'110100','北京市',1,'110000');
INSERT INTO `region` VALUES(4,'410100','郑州市',1,'410000');




DROP TABLE IF EXISTS `store_info`;
CREATE TABLE `store_info`(
`id` bigint(20) NOT NULL COMMENT 'id',
`store_name` varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '店铺名称',
`reputation` int(11) NULL DEFAULT NULL COMMENT '信誉等级',
`region_code` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '店铺所在地',
PRIMARY KEY (`id`) USING BTREE
)ENGINE=InnoDB CHARACTER SET=utf8 COLLATE=utf8_general_ci ROW_FORMAT=Dynamic;
INSERT INTO `store_info` VALUES(1,'XX零食店',4,'110100');
INSERT INTO `store_info` VALUES(2,'XX饮品店',3,'410100');

创建product_db_1、product_db_2数据库，并分别对两库执行以下脚本创建表：

DROP TABLE IF EXISTS `product_descript_1`;
CREATE TABLE `product_descript_1`(
`id`bigint(20) NOT NULL COMMENT 'id',
`product_info_id`bigint(20) NULL DEFAULT NULL COMMENT '所属商品id',`descript` longtext CHARACTER SET utf8 COLLATE utf8_general_ci NULL COMMENT '商品描述',
`store_info_id`bigint(20) NULL DEFAULT NULL COMMENT '所属店铺id',
PRIMARY KEY(`id`) USING BTREE,
INDEX`FK_Reference_2`(`product_info_id`) USING BTREE
)ENGINE=InnoDB CHARACTER SET=utf8 COLLATE=utf8_general_ci ROW_FORMAT=Dynamic;


DROP TABLE IF EXISTS `product_descript_2`;
CREATE TABLE `product_descript_2`(
`id`bigint(20) NOT NULL COMMENT 'id',
`product_info_id`bigint(20) NULL DEFAULT NULL COMMENT '所属商品id',`descript` longtext CHARACTER SET utf8 COLLATE utf8_general_ci NULL COMMENT '商品描述',
`store_info_id`bigint(20) NULL DEFAULT NULL COMMENT '所属店铺id',
PRIMARY KEY(`id`) USING BTREE,
INDEX`FK_Reference_2`(`product_info_id`) USING BTREE
)ENGINE=InnoDB CHARACTER SET=utf8 COLLATE=utf8_general_ci ROW_FORMAT=Dynamic;

DROP TABLE IF EXISTS `product_info_1`;
CREATE TABLE `product_info_1`(
`product_info_id`bigint(20) NOT NULL COMMENT 'id',
`store_info_id`bigint(20) NULL DEFAULT NULL COMMENT '所属店铺id',
`product_name`varchar(100)CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL
COMMENT'商品名称',
`spec`varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '规格',
`region_code`varchar(50)CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT 
'产地',
`price`decimal(10,0) NULL DEFAULT NULL COMMENT '商品价格',
`image_url`varchar(100)CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT 
'商品图片',
PRIMARY KEY(`product_info_id`) USING BTREE,
INDEX`FK_Reference_1`(`store_info_id`) USING BTREE
)ENGINE=InnoDB CHARACTER SET=utf8 COLLATE=utf8_general_ci ROW_FORMAT=Dynamic;


DROP TABLE IF EXISTS `product_info_2`;
CREATE TABLE `product_info_2`(
`product_info_id`bigint(20) NOT NULL COMMENT 'id',
`store_info_id`bigint(20) NULL DEFAULT NULL COMMENT '所属店铺id',
`product_name`varchar(100)CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL
COMMENT'商品名称',
`spec`varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '规格',
`region_code`varchar(50)CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT 
'产地',
`price`decimal(10,0) NULL DEFAULT NULL COMMENT '商品价格',
`image_url`varchar(100)CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT 
'商品图片',
PRIMARY KEY(`product_info_id`) USING BTREE,
INDEX`FK_Reference_1`(`store_info_id`) USING BTREE
)ENGINE=InnoDB CHARACTER SET=utf8 COLLATE=utf8_general_ci ROW_FORMAT=Dynamic;

DROP TABLE IF EXISTS `region`;
CREATE TABLE `region`(
`id` bigint(20) NOT NULL COMMENT 'id',
`region_code`varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '地理区域编码',
`region_name`varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '地理区域名称',
`level` tinyint(1) NULL DEFAULT NULL COMMENT '地理',
`parent_region_code` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT'上级地理区域编码',
PRIMARY KEY (`id`) USING BTREE
)ENGINE=InnoDB CHARACTER SET=utf8 COLLATE=utf8_general_ci ROW_FORMAT=Dynamic;

INSERT INTO `region` VALUES(1,'110000','北京',0,NULL);
INSERT INTO `region` VALUES(2,'410000','河南省',0,NULL);
INSERT INTO `region` VALUES(3,'110100','北京市',1,'110000');
INSERT INTO `region` VALUES(4,'410100','郑州市',1,'410000');

搭建maven工程
（1）搭建工程maven工程shopping，导入资料中基础代码shopping，以dbsharding为总体父工程，并做好
spring boot相关配置。
（2）引入maven依赖

 <dependencies>

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

        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-actuator</artifactId>
        </dependency>

        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-configuration-processor</artifactId>
            <optional>true</optional>
        </dependency>

        <dependency>
            <groupId>org.mybatis.spring.boot</groupId>
            <artifactId>mybatis-spring-boot-starter</artifactId>
        </dependency>

        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>druid-spring-boot-starter</artifactId>
        </dependency>



        <dependency>
            <groupId>io.springfox</groupId>
            <artifactId>springfox-swagger2</artifactId>
        </dependency>

        <dependency>
            <groupId>io.springfox</groupId>
            <artifactId>springfox-swagger-ui</artifactId>
        </dependency>

        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
        </dependency>


        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
        </dependency>

        <dependency>
            <groupId>org.mybatis.spring.boot</groupId>
            <artifactId>mybatis-spring-boot-starter</artifactId>
        </dependency>

        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>druid-spring-boot-starter</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
        </dependency>

        <dependency>
            <groupId>org.apache.shardingsphere</groupId>
            <artifactId>sharding-jdbc-spring-boot-starter</artifactId>
        </dependency>

    </dependencies>

配置：

server.port=56082

spring.application.name = shopping
spring.profiles.active = local

server.servlet.context-path = /shopping
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 m0,m1,m2,s0,s1,s2
spring.shardingsphere.datasource.names = m0,m1,m2,s0,s1,s2

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://xxxxxxx:3306/store_db?useUnicode=true
spring.shardingsphere.datasource.m0.username = root
spring.shardingsphere.datasource.m0.password = 123456

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://xxxxxxx:3306/product_db_1?useUnicode=true
spring.shardingsphere.datasource.m1.username = root
spring.shardingsphere.datasource.m1.password = 123456

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://xxxxxxx:3306/product_db_2?useUnicode=true
spring.shardingsphere.datasource.m2.username = root
spring.shardingsphere.datasource.m2.password = 123456

spring.shardingsphere.datasource.s0.type = com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.s0.driver-class-name = com.mysql.jdbc.Driver
spring.shardingsphere.datasource.s0.url = jdbc:mysql://xxxxxx:3306/store_db?useUnicode=true
spring.shardingsphere.datasource.s0.username = root
spring.shardingsphere.datasource.s0.password = 123456

spring.shardingsphere.datasource.s1.type = com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.s1.driver-class-name = com.mysql.jdbc.Driver
spring.shardingsphere.datasource.s1.url = jdbc:mysql://xxxxxxxx:3306/product_db_1?useUnicode=true
spring.shardingsphere.datasource.s1.username = root
spring.shardingsphere.datasource.s1.password = 123456

spring.shardingsphere.datasource.s2.type = com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.s2.driver-class-name = com.mysql.jdbc.Driver
spring.shardingsphere.datasource.s2.url = jdbc:mysql://xxxxxxx:3306/product_db_2?useUnicode=true
spring.shardingsphere.datasource.s2.username = root
spring.shardingsphere.datasource.s2.password = 123456

#主从关系
spring.shardingsphere.sharding.master-slave-rules.ds0.master-data-source-name=m0
spring.shardingsphere.sharding.master-slave-rules.ds0.slave-data-source-names=s0
spring.shardingsphere.sharding.master-slave-rules.ds1.master-data-source-name=m1
spring.shardingsphere.sharding.master-slave-rules.ds1.slave-data-source-names=s1
spring.shardingsphere.sharding.master-slave-rules.ds2.master-data-source-name=m2
spring.shardingsphere.sharding.master-slave-rules.ds2.slave-data-source-names=s2

#分库策略（水平）
spring.shardingsphere.sharding.default-database-strategy.inline.sharding-column = store_info_id
spring.shardingsphere.sharding.default-database-strategy.inline.algorithm-expression = ds$->{store_info_id % 2 + 1}

#分表策略
# store_info分表策略
spring.shardingsphere.sharding.tables.store_info.actual-data-nodes = ds$->{0}.store_info
spring.shardingsphere.sharding.tables.store_info.table-strategy.inline.sharding-column = id
spring.shardingsphere.sharding.tables.store_info.table-strategy.inline.algorithm-expression = store_info

# product_info分表策略
#数据结点包括，ds1.product_info_1，ds1.product_info_2,ds2.product_info_1，ds2.product_info_2
spring.shardingsphere.sharding.tables.product_info.actual-data-nodes = ds$->{1..2}.product_info_$->{1..2}
spring.shardingsphere.sharding.tables.product_info.table-strategy.inline.sharding-column = product_info_id
spring.shardingsphere.sharding.tables.product_info.table-strategy.inline.algorithm-expression = product_info_$->{product_info_id%2+1}
spring.shardingsphere.sharding.tables.product_info.key-generator.column=product_info_id
spring.shardingsphere.sharding.tables.product_info.key-generator.type=SNOWFLAKE

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

# 设置product_info,product_descript为绑定表
spring.shardingsphere.sharding.binding-tables[0] = product_info,product_descript

# 设置region为广播表(公共表)，每次更新操作会发送至所有数据源
spring.shardingsphere.sharding.broadcast-tables=region

# 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

主要就是配置，别的类就直接省略了，也比较简单，直接就测试

 //添加商品
    @Test
    public void testCreateProduct(){
        for (int i=1;i<10;i++){
            ProductInfo productInfo = new ProductInfo();
            productInfo.setStoreInfoId(1L);//店铺id

            productInfo.setProductName("Java编程思想"+i);//商品名称
            productInfo.setSpec("大号");
            productInfo.setPrice(new BigDecimal(60));
            productInfo.setRegionCode("110100");
            productInfo.setDescript("Java编程思想不错！！！"+i);//商品描述
            productService.createProduct(productInfo);
        }

    }

 分库策略是根据store_info_id,当为奇数的时候，就在m2数据源

  分库策略是根据store_info_id,当为偶数的时候，就在m1数据源

测试查询

 //查询商品
    @Test
    public void testQueryProduct(){

        List<ProductInfo> productInfos = productService.queryProduct(2, 2);
        System.out.println(productInfos);
    }

 发现实在从库上的，而且把分库分表都查了。

测试统计商品

//统计商品总数
    @Test
    public void testSelectCount(){

        int i = productDao.selectCount();

        System.out.println(i);
    }

分组统计商品

 //分组统计商品
    @Test
    public void testSelectProductGroupList(){

        List<Map> maps = productDao.selectProductGroupList();

        System.out.println(maps);
    }

分组统计
分组统计也是业务中常见的场景，分组功能的实现由Sharding-jdbc分组归并完成。分组归并的情况最为复杂，它
分为流式分组归并和内存分组归并。 流式分组归并要求SQL的排序项与分组项的字段必须保持一致，否则只能通过
内存归并才能保证其数据的正确性。
举例说明，假设根据科目分片，表结构中包含考生的姓名（为了简单起见，不考虑重名的情况）和分数。通过SQL
获取每位考生的总分，可通过如下SQL：

SELECT name, SUM(score) FROM t_score GROUP BY name ORDER BY name;

在分组项与排序项完全一致的情况下，取得的数据是连续的，分组所需的数据全数存在于各个数据结果集的当前游
标所指向的数据值，因此可以采用流式归并。如下图所示。

 进行归并时，逻辑与排序归并类似。 下图展现了进行next调用的时候，流式分组归并是如何进行的。

通过图中我们可以看到，当进行第一次next调用时，排在队列首位的t_score_java将会被弹出队列，并且将分组值
同为“Jetty”的其他结果集中的数据一同弹出队列。 在获取了所有的姓名为“Jetty”的同学的分数之后，进行累加操
作，那么，在第一次next调用结束后，取出的结果集是“Jetty”的分数总和。 与此同时，所有的数据结果集中的游标
都将下移至数据值“Jetty”的下一个不同的数据值，并且根据数据结果集当前游标指向的值进行重排序。 因此，包含
名字顺着第二位的“John”的相关数据结果集则排在的队列的前列。