1.安装mysql数据库

这里采用docker部署mysql,如果没有安装docker

#安装yum工具
yum install -y yum-utils device-mapper-persistent-data lvm2 --skip-broken
#设置docker镜像源
yum-config-manager     --add-repo     https://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo
sed -i 's/download.docker.com/mirrors.aliyun.com\/docker-ce/g' /etc/yum.repos.d/docker-ce.repo
yum makecache fast
#安装docker
yum install -y docker-ce
#查看docker的版本
docker --verison
#启动docker
systemctl start docker
#开机启动
systemctl enable docker
#配置镜像加速器
vi /etc/docker/daemon.json{"registry-mirrors":["https://aa25jngu.mirror.aliyuncs.com"]
}#重启docker
systemctl daemon-reload
systemctl restart docker

安装mysql

#创建mysql数据目录
mkdir -p /docker/mysql/data
#启动mysql容器
docker run -d --name mysql -p 3306:3306 -v /docker/mysql/data:/var/lib/mysql -e MYSQL_ROOT_PASSWORD=123456 mysql:5.7.44

2.配置hadoop

core-site.xml,新增配置

        <property><name>hadoop.proxyuser.hadoop.groups</name><value>*</value></property><property><name>hadoop.proxyuser.hadoop.hosts</name><value>*</value></property>

3.下载hive

29 March 2024: release 4.0.0 available

• This release works with Hadoop 3.3.6, Tez 0.10.3

https://dlcdn.apache.org/hive/hive-4.0.0/apache-hive-4.0.0-bin.tar.gz

mysql jdbc jar

https://repo1.maven.org/maven2/mysql/mysql-connector-java/5.1.49/mysql-connector-java-5.1.49.jar

[root@hadoop1 hadoop]# tar -zxvf apache-hive-4.0.0-bin.tar.gz -C /export/server/
[root@hadoop1 server]# ln -s /export/server/apache-hive-4.0.0-bin/ /export/server/hive
[root@hadoop1 export]# mv mysql-connector-java-5.1.49.jar /export/server/hive/lib/
[root@hadoop1 export]# chown -R hadoop:hadoop /export

4.配置hive

hive-env.sh

[root@hadoop1 export]# vi /export/server/hive/conf/hive-env.sh
export HADOOP_HOME=/export/server/hadoop
export HIVE_CONF_DIR=/export/server/hive/conf
export HIVE_AUX_JARS_PATH=/export/server/hive/lib

hive-site.xml

[root@hadoop1 conf]# vi /export/server/hive/conf/hive-site.xml
<configuration><property><name>javax.jdo.option.ConnectionURL</name><value>jdbc:mysql://hadoop1:3306/hive?createDatabaseIfNotExist=true&amp;useSSL=false&amp;useUnicode=true&amp;characterEncoding=UTF-8</value></property><property><name>javax.jdo.option.ConnectionDriverName</name><value>com.mysql.jdbc.Driver</value></property><property><name>javax.jdo.option.ConnectionUserName</name><value>root</value></property><property><name>javax.jdo.option.ConnectionPassword</name><value>123456</value></property><property><name>hive.server2.thrift.bind.host</name><value>hadoop1</value></property><property><name>hive.metastore.uris</name><value>thrift://hadoop1:9083</value></property><property><name>hive.metastore.event.db.notification.api.auth</name><value>false</value></property>
</configuration>

create database hive charset utf8;

[root@hadoop1 bin]# /export/server/hive/bin/schematool -initSchema -dbType mysql -verbos
[hadoop@hadoop1 data]$ mkdir -p hive/logs
[hadoop@hadoop1 bin]$ cd /export/server/hive/bin
[hadoop@hadoop1 data]$ nohup ./hive --service metastore >> /data/hive/logs/metastore.log 2>&1 &
[hadoop@hadoop1 bin]$ nohup ./hive --service hiveserver2 >> /data/hive/logs/hiveserver2.log 2>&1 &

5.使用内置客户端beeline,或第三方dbeaver

[hadoop@hadoop1 bin]$ beeline 
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/export/server/apache-hive-4.0.0-bin/lib/log4j-slf4j-impl-2.18.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/export/server/hadoop-3.3.6/share/hadoop/common/lib/slf4j-reload4j-1.7.36.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/export/server/apache-hive-4.0.0-bin/lib/log4j-slf4j-impl-2.18.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/export/server/hadoop-3.3.6/share/hadoop/common/lib/slf4j-reload4j-1.7.36.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
Beeline version 4.0.0 by Apache Hive
beeline> !connect jdbc:hive2://hadoop1:10000
Connecting to jdbc:hive2://hadoop1:10000
Enter username for jdbc:hive2://hadoop1:10000: hadoop
Enter password for jdbc:hive2://hadoop1:10000: 
Connected to: Apache Hive (version 4.0.0)
Driver: Hive JDBC (version 4.0.0)
Transaction isolation: TRANSACTION_REPEATABLE_READ
0: jdbc:hive2://hadoop1:10000> show databases;
INFO  : Compiling command(queryId=hadoop_20240604004120_6c11b3b6-ce13-4c04-a1d2-6bc799a040a0): show databases
INFO  : Semantic Analysis Completed (retrial = false)
INFO  : Created Hive schema: Schema(fieldSchemas:[FieldSchema(name:database_name, type:string, comment:from deserializer)], properties:null)
INFO  : Completed compiling command(queryId=hadoop_20240604004120_6c11b3b6-ce13-4c04-a1d2-6bc799a040a0); Time taken: 0.014 seconds
INFO  : Concurrency mode is disabled, not creating a lock manager
INFO  : Executing command(queryId=hadoop_20240604004120_6c11b3b6-ce13-4c04-a1d2-6bc799a040a0): show databases
INFO  : Starting task [Stage-0:DDL] in serial mode
INFO  : Completed executing command(queryId=hadoop_20240604004120_6c11b3b6-ce13-4c04-a1d2-6bc799a040a0); Time taken: 0.009 seconds
+----------------+
| database_name  |
+----------------+
| default        |
+----------------+
1 row selected (0.201 seconds)
0: jdbc:hive2://hadoop1:10000>