1.clickhouse应用场景,copy:
应用场景:
1.绝大多数请求都是用于读访问的
2.数据需要以大批次(大于1000行)进行更新,而不是单行更新;或者根本没有更新操作
3.数据只是添加到数据库,没有必要修改
4.读取数据时,会从数据库中提取出大量的行,但只用到一小部分列
5.表很“宽”,即表中包含大量的列
6.查询频率相对较低(通常每台服务器每秒查询数百次或更少)
7.对于简单查询,允许大约50毫秒的延迟
8.列的值是比较小的数值和短字符串(例如,每个URL只有60个字节)
9.在处理单个查询时需要高吞吐量(每台服务器每秒高达数十亿行)
10.不需要事务
11.数据一致性要求较低
12.每次查询中只会查询一个大表。除了一个大表,其余都是小表
13.查询结果显著小于数据源。即数据有过滤或聚合。返回结果不超过单个服务器内存大小
2.整合springboot
依赖(mybatis plus做持久层,druid做数据源):
ru.yandex.clickhouse
clickhouse-jdbc
0.2.4
com.alibaba
druid
1.2.4
com.baomidou
mybatis-plus-boot-starter
3.2.0
配置文件yml:
spring:
datasource:
type: com.alibaba.druid.pool.DruidDataSource
click:
driverClassName: ru.yandex.clickhouse.ClickHouseDriver
url: jdbc:clickhouse://xx.xx.xx.xx:8123/default
username: default
password: 123456
initialSize: 10
maxActive: 100
minIdle: 10
maxWait: 6000
mybatis-plus:
mapper-locations: classpath*:mapper/*.xml
configuration:
log-impl: org.apache.ibatis.logging.stdout.StdOutImpl
map-underscore-to-camel-case: true
cache-enabled: true
lazy-loading-enabled: true
multiple-result-sets-enabled: true
use-generated-keys: true
default-statement-timeout: 60
default-fetch-size: 100
type-aliases-package: com.xrj.clickhouse.pojo
clickhouse与Druid配置类:
package com.xrj.clickhouse.config;
import com.alibaba.druid.pool.DruidDataSource;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import javax.annotation.Resource;
import javax.sql.DataSource;
@Configuration
public class DruidConfig {
@Resource
private JdbcParamConfig jdbcParamConfig ;
@Bean
public DataSource dataSource() {
DruidDataSource datasource = new DruidDataSource();
datasource.setUrl(jdbcParamConfig.getUrl());
datasource.setDriverClassName(jdbcParamConfig.getDriverClassName());
datasource.setInitialSize(jdbcParamConfig.getInitialSize());
datasource.setMinIdle(jdbcParamConfig.getMinIdle());
datasource.setMaxActive(jdbcParamConfig.getMaxActive());
datasource.setMaxWait(jdbcParamConfig.getMaxWait());
datasource.setUsername(jdbcParamConfig.getUsername());
datasource.setPassword(jdbcParamConfig.getPassword());
return datasource;
}
}
package com.xrj.clickhouse.config;
import lombok.Data;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.stereotype.Component;
@Data
@Component
@ConfigurationProperties(prefix = "spring.datasource.click")
public class JdbcParamConfig {
private String driverClassName ;
private String url ;
private String username ;
private String password ;
private Integer initialSize ;
private Integer maxActive ;
private Integer minIdle ;
private Integer maxWait ;
}
接下来配置实体类,mapper,service,controlle以及mapper.xml。与mybatisplus操作mysql一样的思路。
@Data
public class UserInfo implements Serializable {
private static final long serialVersionUID = 1L;
private int id;
private String userName;
private String passWord;
private String phone;
private String email;
private String createDay;
}
@Repository
public interface UserInfoMapper extends BaseMapper {
// 写入数据
void saveData (UserInfo userInfo) ;
// ID 查询
UserInfo selectById (@Param("id") Integer id) ;
// 查询全部
List selectList () ;
}
public interface UserInfoService extends IService {
// 写入数据
void saveData (UserInfo userInfo) ;
// ID 查询
UserInfo selectById (@Param("id") Integer id) ;
// 查询全部
List selectList () ;
}
@Service
public class UserInfoServiceImpl extends ServiceImpl implements UserInfoService {
@Autowired
UserInfoMapper userInfoMapper;
@Override
public void saveData(UserInfo userInfo) {
userInfoMapper.saveData(userInfo);
}
@Override
public UserInfo selectById(Integer id) {
return userInfoMapper.selectById(id);
}
@Override
public List selectList() {
return userInfoMapper.selectList();
}
}
@RestController
public class UserInfoController {
@Autowired
UserInfoService userInfoService;
@GetMapping("/selectById/{id}")
public UserInfo selectById(@PathVariable("id") Integer id){
return userInfoService.selectById(id);
}
@PostMapping("/saveData")
public void saveData(@RequestBody UserInfo userInfo){
userInfoService.saveData(userInfo);
}
@GetMapping("/selectList")
public List selectList(){
return userInfoService.selectList();
}
}
id,user_name,pass_word,phone,email,create_day
INSERT INTO cs_user_info
(id,user_name,pass_word,phone,email)
VALUES
(#{id,jdbcType=INTEGER},#{userName,jdbcType=VARCHAR},#{passWord,jdbcType=VARCHAR},
#{phone,jdbcType=VARCHAR},#{email,jdbcType=VARCHAR})
后面接着更新docker安装clickhouse的流程