Hadoop 之 Hive 搭建与使用
- 一.Hive 简介
- 二.Hive 搭建
- 1.下载
- 2.安装
- 1.解压并配置 HIVE
- 2.修改 hive-site.xml
- 3.修改 hadoop 的 core-site.xml
- 4.启动
- 三.Hive 测试
- 1.基础测试
- 2.建库建表
- 3.Java 连接测试
- 1.Pom依赖
- 2.Yarm 配置文件
- 3.启动类
- 4.配置类
- 5.测试类
一.Hive 简介
Hive 是基于 Hadoop 的数据仓库工具,可以提供类 SQL 查询能力
二.Hive 搭建
1.下载
Hive 官网
Hive 下载地址(自选版本)
MySQL Java 驱动下载
2.安装
1.解压并配置 HIVE
## 1.创建安装目录
mkdir -p /usr/local/hive
## 2.将压缩包拷贝到服务器并解压
tar zxvf apache-hive-4.0.0-alpha-2-bin.tar.gz -C /usr/local/hive/
## 3.添加环境变量并刷新
echo 'export HIVE_HOME=/usr/local/hive/apache-hive-4.0.0-alpha-2-bin' >> /etc/profile
echo 'export PATH=${HIVE_HOME}/bin:${PATH}' >> /etc/profile
source /etc/profile
## 4.进入安装目录
cd $HIVE_HOME/conf
## 5.复制 hive-env.sh.template 并修改配置
cp hive-env.sh.template hive-env.sh
echo 'export JAVA_HOME=/usr/local/java/jdk-11.0.19' >> hive-env.sh
echo 'export HADOOP_HOME=/usr/local/hadoop/hadoop-3.3.6' >> hive-env.sh
echo 'export HADOOP_CONF_DIR=${HADOOP_HOME}/etc/hadoop' >> hive-env.sh
echo 'export HIVE_HOME=/usr/local/hive/apache-hive-4.0.0-alpha-2-bin' >> hive-env.sh
echo 'export HIVE_CONF_DIR=${HIVE_HOME}/conf' >> hive-env.sh
echo 'export HIVE_AUX_JARS_PATH=${HIVE_HOME}/lib' >> hive-env.sh
## 6.复制 mysql-connector-j-8.0.33.jar 到 ${HIVE_HOME}/lib
tar zxvf mysql-connector-j-8.0.33.tar.gz
cp mysql-connector-j-8.0.33/mysql-connector-j-8.0.33.jar ${HIVE_HOME}/lib/
## 7.复制 cp hive-default.xml.template 并修改配置
cp hive-default.xml.template hive-site.xml
2.修改 hive-site.xml
使用 MobaXterm 连接虚拟机,并用文本编辑工具打开 hive-site.xml 修改:
注释掉同名的默认配置,或参考下面信息,直接修改默认配置值
同时全局替换下面两个变量值,避免 hiveserver2 启动报错
1.${system:java.io.tmpdir} => /tmp (Linux 系统默认的临时目录)
2.${system:user.name} => root (本系统当前操作用户名)
3.hive.server2.thrift.client.user 配置用户 root , 同时需要修改 hadoop 的 core-site.xml 为 root 配置代理信息
4.hadoop 集群搭建参考前面文章
<!--配置 Hive Metastore 此处使用 mysql & 转义 &-->
<property>
<name>javax.jdo.option.ConnectionURL</name>
<value>jdbc:mysql://192.168.1.201:3306/hive?characterEncoding=UTF8&createDatabaseIfNotExist=true&serverTimezone=GMT%2B8&useSSL=false&allowPublicKeyRetrieval=true</value>
</property>
<property>
<name>javax.jdo.option.ConnectionDriverName</name>
<value>com.mysql.cj.jdbc.Driver</value>
</property>
<property>
<name>javax.jdo.option.ConnectionUserName</name>
<value>admin</value>
</property>
<property>
<name>javax.jdo.option.ConnectionPassword</name>
<value>12345678</value>
</property>
<property>
<name>datanucleus.schema.autoCreateAll</name>
<value>true</value>
</property>
<!-- nn 配置主机地址/用户/密码 -->
<property>
<name>hive.server2.thrift.bind.host</name>
<value>nn</value>
</property>
<property>
<name>hive.server2.thrift.client.user</name>
<value>root</value>
<description>Username to use against thrift client. default is 'anonymous'</description>
</property>
<property>
<name>hive.server2.thrift.client.password</name>
<value>123456</value>
<description>Password to use against thrift client. default is 'anonymous'</description>
</property>
<property>
<name>hive.metastore.event.db.notification.api.auth</name>
<value>false</value>
</property>
<property>
<name>hive.server2.active.passive.ha.enable</name>
<value>true</value>
</property>
<property>
<name>hive.metastore.warehouse.dir</name>
<value>hdfs://nn:9000/user/hive/warehouse</value>
<description>hdfs 地址</description>
</property>
<property>
<name>hive.metastore.schema.verification</name>
<value>true</value>
</property>
<property>
<name>hive.metastore.uris</name>
<value>thrift://nn:9083</value>
</property>
初始化元数据
查看库 Hive
3.修改 hadoop 的 core-site.xml
## 1.进入配置目录
cd $HADOOP_HOME//etc/hadoop
## 2.修改 core-site.xml
vim core-site.xml
## 3.增加以下内容
<property>
<name>hadoop.proxyuser.root.hosts</name>
<value>*</value>
</property>
<property>
<name>hadoop.proxyuser.root.groups</name>
<value>*</value>
</property>
4.启动
## 1.初始化
schematool -initSchema -dbType mysql
## 2.启动 hadoop 集群
cd $HADOOP_HOME/sbin && start-all.sh
## 3.启动 hive
mkdir -p /var/log/hive
cd ${HIVE_HOME}/bin
nohup hive --service metastore 2>&1 >> /var/log/hive/metastore.log &
nohup hive --service hiveserver2 2>&1 >> /var/log/hive/hiveserver2.log &
## 4.杀死 hive 进程
kill -9 `ps aux | grep hiveserver2 | grep -v grep | awk '{print $2}'`
kill -9 `ps aux | grep metastore | grep -v grep | awk '{print $2}'`
查看 Java 进程:jps
查看端口占用:lsof -i -P -n | grep LISTEN
查看默认日志:tail -200f /tmp/root/hive.log
日志发现一个报错:java.sql.SQLException: Referencing column 'ACTIVE_EXECUTION_ID' and referenced column 'SCHEDULED_EXECUTION_ID' in foreign key constraint 'SCHEDULED_EXECUTIONS_SCHQ_ACTIVE' are incompatible.
因为 MySQL 版本为 8.0.33,可能导致了主外键字段类型不一致时的异常
对应初始化后的表和字段分别为:
SCHEDULED_EXECUTIONS - SCHEDULED_EXECUTION_ID
SCHEDULED_QUERIES - ACTIVE_EXECUTION_ID
原来这两个字段一个为 int ,一个为 bigint 统一为 bigint 后就不报错了
三.Hive 测试
1.基础测试
## 1.控制台连接
hive
## 2.连接并输入用户名、密码
!connect jdbc:hive2://nn:10000
## 3.查看库
show databases;
## 4.退出
!quit
UI 访问:http://192.168.1.6:10002/
hdfs 查看: http://192.168.1.6:9870/explorer.html#/tmp/hive/root
2.建库建表
## 1.建库并设置存储位置
create database if not exists animal_db
comment "This is animal database"
location '/hive_database/animal_db';
## 2.查看库
show databases;
## 3.切换库
use animal_db;
## 4.创建表
create table if not exists dog_tb(name string,breed string,area string,feature string)
row format delimited fields terminated by ';';
## 5.从本地文件加载数据
load data local inpath '/home/dog_tb.txt' into table dog_tb;
## 6.查看数据
select * from dog_tb;
## 7.删除表
drop table dog_tb;
## 7.强制删库
drop database animal_db cascade ;
dog_tb.txt
bomei;small;germany;white,small
bianmu;big;scotland;clever
tugou;all;china;clever,loyalty
3.Java 连接测试
1.Pom依赖
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>org.example</groupId>
<artifactId>hive-demo</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<maven.compiler.source>11</maven.compiler.source>
<maven.compiler.target>11</maven.compiler.target>
<spring.version>2.7.8</spring.version>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
</properties>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
<version>${spring.version}</version>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<version>1.18.28</version>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>fastjson</artifactId>
<version>2.0.32</version>
</dependency>
<dependency>
<groupId>org.apache.hive</groupId>
<artifactId>hive-jdbc</artifactId>
<version>4.0.0-alpha-2</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>3.3.6</version>
</dependency>
</dependencies>
</project>
2.Yarm 配置文件
config:
hivedriverClassName: org.apache.hive.jdbc.HiveDriver
hiveurl: jdbc:hive2://192.168.1.6:10000/animal_db
hiveusername: root
hivepassword: 123456
3.启动类
package org.example;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
/**
* @author Administrator
*/
@SpringBootApplication
public class HiveApp {
public static void main(String[] args) {
//启动触发
SpringApplication.run(HiveApp.class,args);
}
}
4.配置类
package org.example.config;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.context.annotation.Bean;
import org.springframework.stereotype.Component;
import java.sql.Connection;
import java.sql.DriverManager;
import java.util.Properties;
/**
* @author Administrator
* @Description
* @create 2023-08-02 21:42
*/
@Component
public class HiveConfig {
@Bean("hiveProperties")
@ConfigurationProperties(prefix = "config")
public Properties getConfig(){
return new Properties();
}
@Bean
public Connection start(@Qualifier("hiveProperties") Properties properties){
try {
String url = (String) properties.get("hiveurl");
String user = (String) properties.get("hiveusername");
String password = (String) properties.get("hivepassword");
Connection conn = DriverManager.getConnection(url,user,password);
conn.setAutoCommit(true);
return conn;
} catch (Exception e) {
System.out.println(e);
}
return null;
}
}
5.测试类
package org.example.controller;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.lang.StringUtils;
import org.apache.hive.jdbc.HivePreparedStatement;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;
import java.sql.Connection;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
/**
* @author Administrator
* @Description
* @create 2023-08-02 21:42
*/
@Slf4j
@RestController
@RequestMapping("/hive")
public class HiveController {
/**
* 注入连接类
*/
@Autowired
Connection conn;
/**
* 列
*/
List<String> columns = Arrays.asList("name","breed","area","feature");
/**
* 插入
* @throws SQLException
*/
@GetMapping("/insert")
public void insert() throws SQLException {
String sql = "insert into dog_tb values (?,?,?,?)";
HivePreparedStatement pStSm= (HivePreparedStatement) conn.prepareStatement(sql);
pStSm.setString(1, "keji");
pStSm.setString(2, "small");
pStSm.setString(3, "welsh");
pStSm.setString(4, "friendly");
pStSm.executeUpdate();
}
/**
* 查询
* @return
* @throws SQLException
*/
@GetMapping("/query")
public List<String> query(int index,String value) throws SQLException {
List<String> list = new ArrayList<>();
String sql = "select * from dog_tb";
if (index > 0 && StringUtils.isNotEmpty(value)){
sql = "select * from dog_tb where name = ?";
}
HivePreparedStatement pStSm= (HivePreparedStatement) conn.prepareStatement(sql);
if (index >= 0 && StringUtils.isNotEmpty(value)){
pStSm.setString(index, value);
}
ResultSet resultSet = pStSm.executeQuery();
StringBuilder builder = new StringBuilder();
while (resultSet.next()){
builder.setLength(0);
for (String col:columns){
builder.append(resultSet.getString(col)).append(";");
}
String result = builder.substring(0,builder.length()-1);
list.add(result);
log.info("row: {}",result);
}
return list;
}
}
如果插入或查询报错可通过如下位置查询报错信息