一、下载解压Hive

1.官网地址

https://dlcdn.apache.org/hive/

2.选择对应版本进行下载，这里我以3.1.3为例；

3.下载好后，进行解压，并重命名为hive-3.1.3，放到资源库目录下；

二、配置系统环境

1.打开~/.bash_profile文件

open -e ~/.bash_profile

2.添加Hadoop、Hive环境变量

export HADOOP_HOME=/Library/hadoop-3.4.0
export PATH=$PATH:$HADOOP_HOME/binexport HIVE_HOME=/Library/hive-3.1.3
export PATH=$HIVE_HOME/bin:$PATH

3.使得配置生效

source ~/.bash_profile

4.停止hadoop并重启

如果hadoop正在运行暂停hadoop

# 进入hadoop目录
cd /Library/hadoop-3.4.0
# 停止hadoop服务
./sbin/stop-all.sh
# 启动hadoop
./sbin/start-all.sh

5.查看hive版本

hive --version

如果出现mac权限问题，解决方法参考链接

hive --versionSLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/Library/hive-3.1.3/lib/log4j-slf4j-impl-2.18.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/Library/hadoop-3.4.0/libexec/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:/Library/hive-3.1.3/lib/log4j-slf4j-impl-2.18.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/Library/hadoop-3.4.0/libexec/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]
Hive 4.0.0
Git git://MacBook-Air.local/Users/xxx/projects/hive/fork/hive -r 183f8cb41d3dbed961ffd27999876468ff06690c
Compiled by xxx on Mon Mar 25 12:44:09 CET 2024
From source with checksum e3c64bec52632c61cf7214c8b545b564

三、修改Hive配置文件

1.重命名conf文件夹下的hive-default.xml.template

cd /Library/hive-3.1.3/confmv hive-default.xml.template hive-default.xml

2.新建hive-site.xml

vim hive-site.xmlopen -e hive-site.xml

在hive-site.xml文件中添加如下内容：

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration><property><name>javax.jdo.option.ConnectionURL</name><value>jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true&amp;useSSL=false&amp;allowPublicKeyRetrieval=true</value><description>JDBC connect string for a JDBC metastore</description></property><property><name>javax.jdo.option.ConnectionDriverName</name><value>com.mysql.jdbc.Driver</value><description>Driver class name for a JDBC metastore</description></property><property><name>javax.jdo.option.ConnectionUserName</name><value>hive</value><description>username to use against metastore database</description></property><property><name>javax.jdo.option.ConnectionPassword</name><value>hive</value><description>password to use against metastore database</description></property>
</configuration>

保存并关闭；

四、安装并配置mysql

1.下载Mysql驱动

MySQL 驱动下载网址

2.将下载的压缩包解压，找到mysql-connector-j-8.2.0.jar文件，将该文件拷贝到/Library/hive-3.1.3/lib目录下。

3.确保你的电脑安装过mysql

打开终端，执行如下命令：

mysql -u root -p

如果你确定装过mysql，但是执行上述命令后，发现不存在mysql命令，那说明你的系统环境没有配置。

# 查看 mysql 安装路径
which mysql

若出现路径，则存在mysql。

# 打开如下配置文件
open -e ~/.bash_profile

export PATH=${PATH}:/usr/local/mysql/bin/

配置好后保存，使配置文件生效。

source ~/.bash_profile

4.重新执行mysql 登录

mysql -u root -p

回车，输入密码。

五、创建hive数据库

1.创建hive数据库

create database hive; CREATE USER 'hive'@'localhost' IDENTIFIED BY 'hive';GRANT ALL ON *.* TO 'hive'@'localhost';#刷新mysql系统权限关系表
flush privileges;

2.使用Hive自带的schematool工具升级元数据

cd /Library/hive-3.1.3
./bin/schematool -initSchema -dbType mysql

出现一段空白，接着出现Initialization script completed。

六、修改Hadoop配置文件并重启

1.编辑Hadoop的core-site.xml配置文件

cd /Library/hadoop-3.4.0
open -e core-site.xml

在文件中补充如下内容：

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

保存并推出。

用户名通过如下命令查看

whoami

2.重启Hadoop集群

cd /Library/hadoop-3.4.0/sbin
./stop-all.sh
./satrt-all.sh

七、启动Hive并访问

1.启动hive

cd /Library/hive-3.1.3/bin
hive --service hiveserver2&

启动后，出现如下命令证明启动成功：

SLF4J: Found binding in [jar:file:/Library/hive-3.1.3/lib/log4j-slf4j-impl-2.18.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/Library/hadoop-3.4.0/libexec/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]
Hive Session ID = 7afcdcf2-3f5d-4912-99b9-4e57a7ef3a03
Hive Session ID = 51a21ecb-ae06-4ed3-a6b7-a62444b5836e

2.浏览器访问

再去浏览器里输入

http://localhost:10002

就可以见到hive的web界面了

3.客户端访问

在bin目录下，重启一个终端，输入如下命令：

beeline
!connect jdbc:hive2://localhost:10000

用户名hive，密码hive
成功登录出现
0: jdbc:hive2://localhost:10000>

show databases;

执行上面命令后，若有结果输出，则证明配置完成了。

关闭hiveServer2时，执行如下命令查看hive进程；

ps aux | grep hive 

进程大概是下面内容：

 52843   0.1  2.9 413527440 489776 s003  SN    8:58下午   0:17.23 /Library/Java/JavaVirtualMachines/jdk-1.8.jdk/Contents/Home/bin/java -Dproc_jar -Dproc_hiveserver2 -Dlog4j2.formatMsgNoLookups=true -Dlog4j.configurationFile=hive-log4j2.properties -Djava.util.logging.config.file=/Library/hive-3.1.3/conf/parquet-logging.properties -Djline.terminal=jline.Unsuppo

4.通过如下命令杀死该进程

kill -9 52843 

八、通过DBeaver连接Hive

主机：localhost认证：Database Native用户名：hive密码：hive

九、利用Python连接Hive库，并在库中插入数据

代码如下：

from pyhive import hivedef ConnectHive(addr, port, user, pwd, db, auth):try:# 1. Create connectionconn = hive.Connection(host=addr, port=port, username=user, password=pwd, database=db, auth=auth)print("Hive connection successful!")# 2. Use Hive SQL to create tablecreate_tab_sql = """CREATE TABLE users (id INT, name STRING, age INT, address STRING)"""# 3. Execute SQL with cursorwith conn.cursor() as cursor:cursor.execute(create_tab_sql)print("User table created successfully!")except Exception as e:print(f"An error occurred: {e}")finally:# 4. Close connectionif conn:conn.close()print("Hive connection closed.")if __name__ == '__main__':addr = '127.0.0.1'port = 10000user = 'hive'pwd = 'hive'db = 'default'auth = 'LDAP'ConnectHive(addr, port, user, pwd, db, auth)

在执行这段代码时，出现下面报错：

org.apache.hadoop.security.AccessControlException Permission denied: user=hive, access=WRITE, inode="/"

说明hive用户没有写HDFS根目录(/)的权限。

2.解决办法

# 列出hdfs根目录的内容并查看权限
hdfs dfs -ls /

hdfs dfs -chmod 755 /
hdfs dfs -chown hive:supergroup /

再执行如下命令：

hdfs dfs -ls /

3.重新运行你的Python代码就成功了。