创建可视化网页四 : 虚拟机中Hive的安装与配置 , 并测试其是否安装成功

这里写目录标题

• 引入 : hive-2.1.0的安装包
• 一.安装配置hive
• • 1.启动相关进程 , 进行解压安装
  • 2.相关配置
• 二.测试是否成功安装Hiv
• • 1.导入数据
  • 2.在hive中执行数据操作

引入 : hive-2.1.0的安装包

hive-2.1.0的安装包

一.安装配置hive

1.启动相关进程 , 进行解压安装

//打开虚拟机时 , 先启动所有进程
[root@hadoop ~]# jps
10111 Jps
[root@hadoop ~]# start-all.sh
[root@hadoop ~]# jps
10544 SecondaryNameNode
10723 ResourceManager
10249 NameNode
10825 NodeManager
11212 Jps
10351 DataNode

//启动mysql
[root@hadoop ~]# service mysql start
Starting MySQL SUCCESS!
[root@hadoop ~]# 2024-05-19T10:35:28.535241Z mysqld_safe A mysq
mysql -uroot -p
Enter password:
mysql> exit;
Bye

[root@hadoop ~]# systemctl stop firewalld //关闭防火墙
[root@hadoop ~]# start-yarn.sh //启动mapreduce
[root@hadoop ~]# cd /usr/soft

//解压hive的安装包
[root@hadoop soft]# tar -zxvf apache-hive-2.1.0-bin.tar.gz //解压
[root@hadoop soft]# ls
apache-hive-2.1.0-bin hadoop mysql5.7
apache-hive-2.1.0-bin.tar.gz jdk
[root@hadoop soft]# rm -rf apache-hive-2.1.0-bin.tar.gz //删除压缩包
[root@hadoop soft]# ls
apache-hive-2.1.0-bin hadoop jdk mysql5.7
[root@hadoop soft]# mv apache-hive-2.1.0-bin/ hive //改名为hive
[root@hadoop soft]# ls
hadoop hive jdk mysql5.7

2.相关配置

//配置环境变量
[root@hadoop soft]# vim /etc/profile.d/hive.sh
[root@hadoop profile.d]# cat hive.sh
HIVE_HOME=/usr/soft/hive
PATH=$PATH:$HIVE_HOME/bin
CLASSPATH=$CLASSPATH:$HIVE_HOME/lib
export HIVE_HOME PATH CLASSPATH

//source一下,让环境变量的配置生效
[root@hadoop profile.d]# source /etc/profile.d/hive.sh

//修改hive-site.xml 文件
[root@hadoop profile.d]# cd /usr/soft/hive/conf

[root@hadoop conf]# cat hive-site.xml

- hive-site.xml 文件

	<?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?useUnicode=true&amp;characterEncoding=utf8&amp;useSSL=false&amp;createDatabaseIfNotExist=true</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>1234</value> 	 </property> 	 </<configuration>> 

//在xftp中将mysql的驱动包传到 /usr/soft/hive/lib目录下

• mysql驱动包下载到 /usr/soft/hive/lib目录下
  

//然后初始化元数据
[root@hadoop lib]# schematool -dbType mysql -initSchema

//这时数据库就会有些变动(更新了) , 我们可以查看一下

[root@hadoop lib]# mysql -uroot -p

mysql> show databases;
//…
5 rows in set (0.01 sec)
mysql> use hive;
mysql> show tables;
//…
57 rows in set (0.00 sec)

• 查看mysql
  

二.测试是否成功安装Hiv

1.导入数据

//先创建一个文件 , 存放点数据
[root@hadoop ~]# cd /usr/
[root@hadoop usr]# mkdir data
[root@hadoop usr]# cd data
[root@hadoop data]# vim student.txt
[root@hadoop data]# cat student.txt

95002,刘晨,女,19,IS 95017,王风娟,女,18,IS 95018,王一,女,19,IS 95013,冯伟,男,21,CS 95014,王小丽,女,19,CS 95019,邢小丽,女,19,IS 95020,赵钱,男,21,IS 95003,王敏,女,22,MA 95004,张立,男,19,IS 95012,孙花,女,20,CS 95010,孔小涛,男,19,CS 95005,刘刚,男,18,MA 95006,孙庆,男,23,CS 95007,易思玲,女,19,MA 95008,李娜,女,18,CS 95021,周二,男,17,MA 95022,郑明,男,20,MA 95001,李勇,男,20,CS 95011,包小柏,男,18,MA 95009,梦圆圆,女,18,MA 95015,王君,男,18,MA 

//将文件 上传到hdfs中
[root@hadoop data]# hdfs dfs -put student.txt /

[root@hadoop data]# hdfs dfs -ls /
Found 2 items
-rw-r–r-- 1 root supergroup 504 2024-05-27 09:56 /student.txt
drwx-wx-wx - root supergroup 0 2024-05-19 21:18 /tmp

2.在hive中执行数据操作

//打开hive
[root@hadoop ~]# hive

hive> show databases;
OK
default
Time taken: 1.361 seconds, Fetched: 1 row(s)

//创建一个数据库
hive> create database myhive;
OK
Time taken: 0.583 seconds

hive> show databases;
OK
default
myhive
Time taken: 0.022 seconds, Fetched: 2 row(s)
hive> use myhive;
OK
Time taken: 0.047 seconds

//创建一个student的表
hive> create table student(id int, name string, sex string, age int, department string) row format delimited fields terminated by ",";
OK
Time taken: 0.158 seconds

//执行数据加载
hive> load data inpath "/student.txt" into table student;
Loading data to table myhive.student
OK
Time taken: 0.964 seconds

//此时,数据导入到表中 , 可以使用hive进行表操作了
hive> select * from student;

OK 95002	刘晨	女	19	IS 95017	王风娟	女	18	IS 95018	王一	女	19	IS 95013	冯伟	男	21	CS 95014	王小丽	女	19	CS 95019	邢小丽	女	19	IS 95020	赵钱	男	21	IS 95003	王敏	女	22	MA 95004	张立	男	19	IS 95012	孙花	女	20	CS 95010	孔小涛	男	19	CS 95005	刘刚	男	18	MA 95006	孙庆	男	23	CS 95007	易思玲	女	19	MA 95008	李娜	女	18	CS 95021	周二	男	17	MA 95022	郑明	男	20	MA 95001	李勇	男	20	CS 95011	包小柏	男	18	MA 95009	梦圆圆	女	18	MA 95015	王君	男	18	MA Time taken: 1.905 seconds, Fetched: 21 row(s) 

//计算平均年龄 ----> hive去调用了mapreduce
hive> select avg(age) from student;

WARNING: Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases. Query ID = root_20240527102934_25490751-a0bb-48aa-9f5e-79f3426a66d8 Total jobs = 1 Launching Job 1 out of 1 Number of reduce tasks determined at compile time: 1 In order to change the average load for a reducer (in bytes):   set hive.exec.reducers.bytes.per.reducer=<number> In order to limit the maximum number of reducers:   set hive.exec.reducers.max=<number> In order to set a constant number of reducers:   set mapreduce.job.reduces=<number> Starting Job = job_1716114831307_0001, Tracking URL = http://hadoop:8088/proxy/application_1716114831307_0001/ Kill Command = /usr/soft/hadoop/bin/hadoop job  -kill job_1716114831307_0001 Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1 2024-05-27 10:30:07,243 Stage-1 map = 0%,  reduce = 0% 2024-05-27 10:30:21,672 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 3.16 sec 2024-05-27 10:30:31,669 Stage-1 map = 100%,  reduce = 100%, Cumulative CPU 5.24 sec MapReduce Total cumulative CPU time: 5 seconds 240 msec Ended Job = job_1716114831307_0001 MapReduce Jobs Launched:  Stage-Stage-1: Map: 1  Reduce: 1   Cumulative CPU: 5.24 sec   HDFS Read: 9204 HDFS Write: 118 SUCCESS Total MapReduce CPU Time Spent: 5 seconds 240 msec OK 19.285714285714285 Time taken: 59.164 seconds, Fetched: 1 row(s)