1、SpringBoot基础配置
框架搭建：SpringBoot + HikariCP/Druid + Mybatis + Mysql+sharding-jdbc
1、POM依赖：
<dependency>
<groupId>org.apache.shardingsphere</groupId>
<artifactId>sharding-jdbc-spring-boot-starter</artifactId>
<version>4.1.1</version>
</dependency>
2、配置允许数据源覆盖
properties文件加入以下配置
# 允许数据源覆盖
spring.main.allow-bean-definition-overriding=true
3、数据源配置
数据源类型通常选择DruidDataSource或者HikariDataSource两者在配置上有所不同。
- DruidDataSource
<!-- 不能使用druid-spring-boot-starter，会导致：Property 'sqlSessionFactory' or 'sqlSessionTemplate' are required -->
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>druid</artifactId>
<version>version</version>
</dependency>
com.alibaba.druid.pool.DruidDataSource
DruidDataSource需要引入druid的Jar包，使用：url
spring.shardingsphere.datasource.m1.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m1.url=
- HikariDataSource
com.zaxxer.hikari.HikariDataSource
HikariDataSource要使用：jdbc-url
spring.shardingsphere.datasource.m1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.m1.jdbc-url=
2、创建表
将用户(user)表，进行水平分表，分为：user_202201,user_202202.... user_202212
//创建数据表
CREATE TABLE user_1/user_2/..../user_6 (
id BIGINT(20) NOT NULL COMMENT 'Id',
name VARCHAR(20) NOT NULL COMMENT '名称',
phone VARCHAR(20) NOT NULL COMMENT '电话',
email VARCHAR(20) NOT NULL COMMENT '邮箱',
create_time TIMESTAMP NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '操作时间',
PRIMARY KEY (id)
)
3、完整properties配置
server.port=9090
server.servlet.context-path=/demo
spring.application.name=sharding-jdbc-simple-demo
# 允许数据源覆盖
spring.main.allow-bean-definition-overriding=true
# MyBatis配置
# 搜索指定包别名
mybatis.typeAliasesPackage=com.lhz.sharding.model.entity
# 配置mapper的扫描，找到所有的mapper.xml映射文件
mybatis.mapperLocations=classpath*:mybatis/**/*.xml
#数据库类型
mybatis.configuration.database-id=mysql
#自动驼峰转换
mybatis.configuration.map-underscore-to-camel-case=true
#pagehelper 分页插件
pagehelper.helper-dialect=mysql
pagehelper.reasonable=false
pagehelper.support-methods-arguments=true
pagehelper.params=count=countSql
# 数据源名称，多数据源逗号隔开
spring.shardingsphere.datasource.names=m1
spring.shardingsphere.datasource.m1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.m1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.m1.jdbc-url=jdbc:mysql://127.0.0.1:3307/shardingjdbc?useUnicode=true&useSSL=false&zeroDateTimeBehavior=convertToNull&characterEncoding=UTF-8&allowMultiQueries=true&serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.m1.username=root
spring.shardingsphere.datasource.m1.password=lhzlx
# 水平分表：user_202201、user_202202、user_202203..，多个表进行分表时，依次在tables标签后写逻辑
# user_202201、user_202202、user_202203... 为数据库中的事实表
# user为xml编码中操作的逻辑表，sharding-jdbc会自动根据策略操作事实表
# 配置节点分布情况，表示可以容纳user_202201到user_203212 张表，根据时间情况定
spring.shardingsphere.sharding.tables.user.actual-data-nodes=m1.user_$->{2022..2032}$->{(1..12).collect{t ->t.toString().padLeft(2,'0')}}
# 指定user表的主键生成策略为SNOWFLAKE
spring.shardingsphere.sharding.tables.user.key-generator.column=id
spring.shardingsphere.sharding.tables.user.key-generator.type=SNOWFLAKE
# 指定user表的分片策略，分片策略包括分片键和分片算法
# 配置表的分片策略
spring.shardingsphere.sharding.tables.user.table-strategy.standard.sharding-column=create_time
# 精确分片算法类名称，用于 = 和 IN。该类需实现 PreciseShardingAlgorithm 接口并提供无参数的构造器
spring.shardingsphere.sharding.tables.user.table-strategy.standard.precise-algorithm-class-name=\
com.lhz.sharding.algorithm.DatePreciseShardingAlgorithm
# 范围分片算法类名称，用于 范围查询 可选。该类需实现 RangeShardingAlgorithm 接口并提供无参数的构造器
spring.shardingsphere.sharding.tables.user.table-strategy.standard.range-algorithm-class-name=\
com.lhz.sharding.algorithm.DateRangeShardingAlgorithm
# 打开sql输出日志
spring.shardingsphere.props.sql.show=true
4、分片算法
4.1、精确分片算法
DatePreciseShardingAlgorithm：
public class DatePreciseShardingAlgorithm implements PreciseShardingAlgorithm<Date> {
/**
* 精确匹配查询
*
* @param tbNames 数据库中所有的事实表
* @param shardingValue 分片相关信息
* @return 返回匹配的数据源
*/
@Override
public String doSharding(Collection<String> tbNames, PreciseShardingValue<Date> shardingValue) {
String logicTableName = shardingValue.getLogicTableName();
// 匹配满足当前分片规则的表名称
Date date = shardingValue.getValue();
Calendar cal = Calendar.getInstance();
cal.setTime(date);
int year = cal.get(Calendar.YEAR);
int month = cal.get(Calendar.MONTH) + 1;
String monthStr = month >= 10 ? month + "" : "0" + month;
String value = year + monthStr;
return logicTableName + "_" + value;
}
}
4.2、范围分片算法
DateRangeShardingAlgorithm：
public class DateRangeShardingAlgorithm implements RangeShardingAlgorithm<Date> {
@Override
public Collection<String> doSharding(Collection<String> tbNames, RangeShardingValue<Date> rangeShardingValue) {
// 获取逻辑表名称
String logicTableName = rangeShardingValue.getLogicTableName();
// between and 的起始值，需要处理只有最大值或者只有最小值的情况
boolean hasLowerBound = rangeShardingValue.getValueRange().hasLowerBound();
boolean hasUpperBound = rangeShardingValue.getValueRange().hasUpperBound();
long max = 0;
long min = 0;
// 只有最小值，比如：id > x
if (hasLowerBound && !hasUpperBound) {
Date lower = rangeShardingValue.getValueRange().lowerEndpoint();
// 直接大于最小值的表
String suffix = getSuffix(lower);
min = Long.parseLong(suffix);
// 获取最大的日期表
ArrayList<String> arrayList = new ArrayList<>(tbNames);
String maxSuffix = arrayList.get(tbNames.size() - 1).split("_")[1];
max = Long.parseLong(maxSuffix);
} else if (!hasLowerBound && hasUpperBound) {
// 只有最大值，比如：id < x
Date upper = rangeShardingValue.getValueRange().upperEndpoint();
String suffix = getSuffix(upper);
max = Long.parseLong(suffix);
// 获取最小的日期表
ArrayList<String> arrayList = new ArrayList<>(tbNames);
String maxSuffix = arrayList.get(0).split("_")[1];
min = Long.parseLong(maxSuffix);
} else {
// 区间值情况
Date lower = rangeShardingValue.getValueRange().lowerEndpoint();
Date upper = rangeShardingValue.getValueRange().upperEndpoint();
String lowerSuffix = getSuffix(lower);
String upperSuffix = getSuffix(upper);
min = Long.parseLong(lowerSuffix);
max = Long.parseLong(upperSuffix);
}
// 拼接事实表名称
return matchMinAndMax(min, max, logicTableName);
}
private List<String> matchMinAndMax(long lower, long upper, String logicTableName) {
List<String> tableNameList = new ArrayList<>();
for (long index = lower; index <= upper; index++) {
String tableName = logicTableName + "_" + index;
tableNameList.add(tableName);
}
return tableNameList;
}
/**
* 获取逻辑表后缀
*
* @param date
* @return
*/
private String getSuffix(Date date) {
Calendar cal = Calendar.getInstance();
cal.setTime(date);
int year = cal.get(Calendar.YEAR);
int month = cal.get(Calendar.MONTH) + 1;
String monthStr = month >= 10 ? month + "" : "0" + month;
return year + monthStr;
}
}
5、实体类
User ：
@Data
public class User implements Serializable {
private Long id;
private String name;
private String phone;
private String email;
private Date createTime;
}
6、Mapper类
DateMapper：
@Mapper
public interface DateMapper {
/**
* 新增数据
*
* @param minTime
* @param minTime
* @return
*/
List<User> listByRange(@Param("minTime") Date minTime, @Param("maxTime") Date maxTime);
/**
* @param user
* @return
*/
int insert(User user);
/**
* @param list
* @return
*/
int insertBatch(List<User> list);
}
DateMapper.xml ：
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN" "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
<mapper namespace="com.lhz.sharding.mapper.DateMapper">
<select id="listByRange"
resultType="com.lhz.sharding.model.entity.User">
select a.*
from user a
where a.create_time >={minTime}
and a.create_time <={maxTime}
</select>
<insert id="insert" parameterType="com.lhz.sharding.model.entity.User">
insert into user(id, name, phone, email, create_time)
values (#{id},{name},{phone},{email},{createTime})
</insert>
<insert id="insertBatch" parameterType="com.lhz.sharding.model.entity.User">
insert into user(id, name, phone, email,create_time)
values
<foreach collection="list" item="item" separator=",">
(#{item.id},{item.name},{item.phone},{item.email},{item.createTime})
</foreach>
</insert>
</mapper>
7、Service类
DateService:
@Service
public class DateService {
@Resource
private DateMapper dateMapper;
/**
* 范围查询
*
* @param minTime
* @param maxTime
* @return
*/
public List<User> listByRange(Date minTime, Date maxTime) {
return dateMapper.listByRange(minTime, maxTime);
}
/**
* 新增数据
*
* @return
*/
@ApiOperation(value = "新增数据", notes = "新增数据")
@ApiOperationSupport(order = 25)
@GetMapping("/insert")
public int insert() {
// 模拟数据
List<User> list = new ArrayList<>();
for (long a = 1; a <= 10; a++) {
User user = new User();
long id = new Random().nextInt(99999999);
user.setId(id);
user.setName("测试名称-" + a);
user.setPhone("176-" + a);
user.setEmail("123@com-" + a);
user.setEmail("123@com-" + a);
// 时间戳，从2022-01-01随机到2022-04-30
long time = (16409664 + new Random().nextInt(102816)) * 100000L;
user.setCreateTime(new Date(time));
list.add(user);
}
// 批量新增
dateMapper.insertBatch(list);
// 单个新增
User user = new User();
long id = new Random().nextInt(99999999);
user.setId(id);
user.setName("测试名称-" + 999);
user.setPhone("176-" + 999);
user.setEmail("123@com-" + 999);
// 时间戳，从2022-01-01随机到2022-04-30
long time = (16409664 + new Random().nextInt(102816)) * 100000L;
user.setCreateTime(new Date(time));
return dateMapper.insert(user);
}
}
8、Controller类
DateController：
@RestController
@RequestMapping("date")
public class DateController {
@Resource
private DateService dateService;
/**
* 范围查询
*
* @return
*/
@GetMapping("/listByRange")
public List<User> listByRange() {
// 模拟时间区间时间戳
long minTime = 1644331100000L;
long maxTime = 1651248000000L;
return dateService.listByRange(new Date(minTime), new Date(maxTime));
}
/**
* 新增数据
*
* @return
*/
@GetMapping("/insert")
public int insert() {
return dateService.insert();
}
}
9、测试
1、查询：
查询的时间范围从2022-02-08 22:38:20 到2022-04-30 00:00:00
所以设置的表分别为：user_202202,user_202203,user_202204 共三张
2、新增：
新增时的日期为2022-01-08 03:06:40，所以操作表user_202201
