Hadoop3.0基础平台搭建(三节点),以及案例运行并使用python生成词云

ゞ浴缸里的玫瑰 2023-07-13 10:44 10阅读 0赞

# 一、设备配置列表，软件包 #

# 二、主机名映射 #

# 三、生成密钥 #

# 四、将密钥发送到各个节点 #

# 五、注意事项及验证 #

# 六、关闭防火墙和SeLinux安全模块(所有主机均需操作 #

# 七、解压JDK、hadoop包，设置Java和hadoop环境 #

# 八、配置Hadoop相关配置文件 #

# 九、将已经修改好的文件使用scp命令复制到各个节点 #

# 十、node1 、 node2使环境生效，并验证 #

# 十一、启动hadoop系统并验证 #

# 十二、在本地编写并测试mapreduce程序，运行WordCount案例 #

# 十三、在hadoop中运行运行WordCount案例 #

# 十四、利用生成文件结合python生成词云 #

## 一、假设有如下设备 ##

<table> 
 <thead> 
  <tr> 
   <th>设备编号</th> 
   <th>主机名</th> 
   <th>系统</th> 
   <th>IP地址</th> 
   <th>准备文件</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>1</td> 
   <td>master</td> 
   <td>centos7.2</td> 
   <td>10.0.0.10</td> 
   <td>----------------hadoop3.0.0.tar.gz -------------------------jdk-8u161-linux-x64.tar.gz</td> 
  </tr> 
  <tr> 
   <td>2</td> 
   <td>node1</td> 
   <td>centos7.2</td> 
   <td>10.0.0.11</td> 
   <td></td> 
  </tr> 
  <tr> 
   <td>3</td> 
   <td>node2</td> 
   <td>centos7.2</td> 
   <td>10.0.0.12</td> 
   <td></td> 
  </tr> 
 </tbody> 
</table>

**软件包下载地址**：  
链接: [https://pan.baidu.com/s/1dvf4o8i9J02fmUu3SMRyDw][https_pan.baidu.com_s_1dvf4o8i9J02fmUu3SMRyDw] 提取码: 3dk3

## 二、首先，需要在各个节点上设置主机名映射(千万不要忘了改主机名)，以master为例 ##

[root@master ~]# vi /etc/hosts
    添加如下内容
    10.0.0.10 master
    10.0.0.11 node1
    10.0.0.12 node2

![在这里插入图片描述][20200308001905864.png]

## 三、使用命令生成密钥(以master节点为例) ##

ssh-keygen

[root@master ~]# ssh-keygen

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70]

## 四、然后使用命令复制SSH密钥到目标主机，开启无密码SSH登录(以master节点为例)，这里对另外两台都需要将密钥复制过去 ##

[root@master ~]# ssh-copy-id master
    [root@master ~]# ssh-copy-id node1
    [root@master ~]# ssh-copy-id node2

## 五、第一次会让你输入yes 这样master节点就可以免密登陆其他节点，同样其他节点也需要进行以上操作，就可以免密登陆其他节点 ##

验证

[root@master ~]# ssh master
    [root@master ~]# ssh node1
    [root@master ~]# ssh node2

## 六、关闭防火墙和SeLinux安全模块(所有主机均需操作 ##

#systemctl stop firewalld;systemctl disable firewalld;setenforce 0

###### 这里是关闭防火墙并关闭其开机自启，并将selinux设置为允许模式，个人认为这里较为重要，若不设置，可能防火墙会拦截主机间的通信流量 ######

## 七、解压JDK、hadoop包，设置Java和hadoop环境 ##

##### 将tar.gz文件传输到master节点，进行如下操作 #####

#### 这里暂时只做master节点，到第九步才是将配置好的所有东西复制到其他节点，可以点击传送门查看 ####

# 第九节传送门 #

##### 1、每个节点创建文件夹 #####

mkdir /opt/bigdata

##### 2、将文件传输到bigdata目录中 #####

[root@master ~]# mkdir /opt/bigdata
    [root@master ~]# mv hadoop-3.0.0.tar.gz jdk-8u161-linux-x64.tar.gz /opt/bigdata/
    [root@master ~]#

##### 3、解压压缩包文件 #####

[root@master bigdata]# tar -zxf hadoop-3.0.0.tar.gz -C /opt/bigdata/
    [root@master bigdata]# tar -zxf jdk-8u161-linux-x64.tar.gz -C /opt/bigdata/
    [root@master bigdata]# ll
    total 484528
    drwxr-xr-x 9 centos centos       139 Dec  8  2017 hadoop-3.0.0
    -rw-r--r-- 1 root   root   306392917 Mar 11 08:50 hadoop-3.0.0.tar.gz
    drwxr-xr-x 8     10    143      4096 Dec 20  2017 jdk1.8.0_161
    -rw-r--r-- 1 root   root   189756259 Mar 11 08:50 jdk-8u161-linux-x64.tar.gz

##### 4、添加环境变量 #####

#vi /etc/profile添加如下内容

export JAVA_HOME=/opt/bigdata/jdk1.8.0_161
    export PATH=$JAVA_HOME/bin:$PATH
    export HADOOP_HOME=/opt/bigdata/hadoop-3.0.0
    export PATH=$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH

![在这里插入图片描述][20200311165307711.png]

##### 5、使环境变量生效 #####

source /etc/profile

##### 6、验证 #####

# hadoop version
    # java -version

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 1]

## 八、配置Hadoop相关配置文件 ##

hadoop目录是hadoop平台的配置目录，我们需要对hadoop-env.sh、core-site.xml、hdfs-site.xml、mapred-site.xml、yarn-site.xml进行配置

##### 1、首先进入hadoop系统目录/opt/bigdata/hadoop-3.0.0/etc/hadoop #####

[root@master ~]# cd /opt/bigdata/hadoop-3.0.0/etc/hadoop
    [root@master hadoop]# pwd
    /opt/bigdata/hadoop-3.0.0/etc/hadoop
    [root@master hadoop]# ls

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 2]

##### 2、编辑hadoop-env.sh,添加java环境 #####

[root@master hadoop]# vi hadoop-env.sh

移动到第54行，删除前面的 '#' 和空格，并修改成如下内容
    export JAVA_HOME=/opt/bigdata/jdk1.8.0_161

![在这里插入图片描述][20200311165748332.png]

##### 3、编辑core-site.xml文件 #####

**\[root@master hadoop\]\# vi core-site.xml**

<property>
        <name>fs.default.name</name>
        <value>hdfs://master:9000</value>
      </property>
      <property>
        <name>hadoop.temp.dir</name>
        <value>/opt/bigdata/hadoop-3.0.0/tmp</value>
      </property>

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 3]

##### 4、编辑hdfs-site.xml文件 #####

**\[root@master hadoop\]\# vi hdfs-site.xml**

<property>
        <name>dfs.replication</name>
        <value>2</value>
      </property>
      <property>
        <name>dfs.namenode.name.dir</name>
        <value>/opt/bigdata/hadoop-3.0.0/hdfs/name</value>
      </property>
      <property>
        <name>dfs.datanode.data.dir</name>
        <value>/opt/bigdata/hadoop-3.0.0/hdfs/data</value>
      </property>
      <property>
        <name>dfs.namenode.secondary.http-address</name>
        <value>node1:9001</value>
      </property>
      <property>
        <name>dfs.http.address</name>
        <value>0.0.0.0:50070</value>
      </property>

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 4]

##### 5、编辑mapred-site.xml文件 #####

**\[root@master hadoop\]\# vi mapred-site.xml**

<property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
      </property>
      <property>
        <name>mapred.job.tracker.http.address</name>
        <value>0.0.0.0:50030</value>
      </property>
      <property>
        <name>mapred.task.tracker.http.address</name>
        <value>0.0.0.0:50060</value>
      </property>
      <property>
        <name>mapreduce.applicaton.classpath</name>
        <value>
          /opt/bigdata/hadoop-3.0.0/etc/hadoop,
          /opt/bigdata/hadoop-3.0.0/share/hadoop/common/*,
          /opt/bigdata/hadoop-3.0.0/share/hadoop/common/lib/*,
          /opt/bigdata/hadoop-3.0.0/share/hadoop/hdfs/*,
          /opt/bigdata/hadoop-3.0.0/share/hadoop/hdfs/lib/*
          /opt/bigdata/hadoop-3.0.0/share/hadoop/mapreduce/*,
          /opt/bigdata/hadoop-3.0.0/share/hadoop/yarn/*,
          /opt/bigdata/hadoop-3.0.0/share/hadoop/yarn/lib/*
        </value>
      </property>

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 5]

##### 6、编辑yarn-site.xml文件 #####

**\[root@master hadoop\]\# vi yarn-site.xml**

<property>
        <name>yarn.resourcemanager.hostname</name>
        <value>master</value>
      </property>
      <property>
        <name>yarn.resourcemanager.webapp.address</name>
        <value>master:8099</value>
      </property>
      <property>
        <name>yarn.application.classpath</name>
        <value>/opt/bigdata/hadoop-3.0.0/etc/hadoop:/opt/bigdata/hadoop-3.0.0/share/hadoop/common/lib/*:/opt/bigdata/hadoop-3.0.0/share/hadoop/common/*:/opt/bigdata/hadoop-3.0.0/share/hadoop/hdfs:/opt/bigdata/hadoop-3.0.0/share/hadoop/hdfs/lib/*:/opt/bigdata/hadoop-3.0.0/share/hadoop/hdfs/*:/opt/bigdata/hadoop-3.0.0/share/hadoop/mapreduce/*:/opt/bigdata/hadoop-3.0.0/share/hadoop/yarn:/opt/bigdata/hadoop-3.0.0/share/hadoop/yarn/lib/*:/opt/bigdata/hadoop-3.0.0/share/hadoop/yarn/*
     </value>
      </property>
    <property>
         <name>yarn.nodemanager.vmem-check-enabled</name>
         <value>false</value>
    </property>
    <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>
    <property>
        <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
        <value>org.apache.hadoop.mapred.ShuffleHandler</value>
    </property>

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 6]

##### 7、编辑workers文件，指定节点 #####

**\[root@master hadoop\]\# vi workers**  
添加node1 node2

![在这里插入图片描述][2020031117050182.png]

### 如果不想master中也有datanode，就把localhost删掉，只保留node1 node2 ###

##### 8、编辑启动配置文件，都添加如下内容 #####

**\[root@master ~\]\# vi /opt/bigdata/hadoop-3.0.0/sbin/start-dfs.sh  
\[root@master ~\]\# vi /opt/bigdata/hadoop-3.0.0/sbin/stop-dfs.sh**

HDFS_DATANODE_USER=root
    HADOOP_SECURE_DN_USER=hdfs
    HDFS_NAMENODE_USER=root
    HDFS_SECONDARYNAMENODE_USER=root

![在这里插入图片描述][20200311172858662.png]  
编辑配置文件，都添加如下内容  
**\[root@master ~\]\# vi /opt/bigdata/hadoop-3.0.0/sbin/start-yarn.sh  
\[root@master ~\]\# vi /opt/bigdata/hadoop-3.0.0/sbin/stop-yarn.sh**

YARN_RESOURCEMANAGER_USER=root
    HADOOP_SECURE_DN_USER=yarn
    YARN_NODEMANAGER_USER=root

![在这里插入图片描述][20200311172815324.png]

## 九、将已经修改好的文件使用scp命令复制到各个节点 ##

##### 1、首先要在各个节点创建/opt/bigdata目录 #####

[root@node1 ~]# mkdir /opt/bigdata
    [root@node2 ~]# mkdir /opt/bigdata

##### 2、master节点复制hadoop文件夹 和jdk文件夹，以及环境配置文件 #####

[root@master ~]# scp -r /opt/bigdata/hadoop-3.0.0 node1:/opt/bigdata
    [root@master ~]# scp -r /opt/bigdata/hadoop-3.0.0 node2:/opt/bigdata
    [root@master ~]# scp -r /opt/bigdata/jdk1.8.0_161/ node1:/opt/bigdata/
    [root@master ~]# scp -r /opt/bigdata/jdk1.8.0_161/ node2:/opt/bigdata/
    [root@master ~]# scp /etc/profile node1:/etc/
    [root@master ~]# scp /etc/profile node2:/etc/

## 十、node1 、 node2使环境生效，并验证 ##

\#\#\#\#\# 1、node1验证 \`\`\`powershell \[root@node1 ~\]\# source /etc/profile \[root@node1 ~\]\# java -version \[root@node1 ~\]\# hadoop version \`\`\`

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 7]

##### 2、node2验证 #####

[root@node2 ~]# source /etc/profile
    [root@node2 ~]# java -version
    [root@node2 ~]# hadoop version

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 8]

## 十一、启动hadoop系统并验证 ##

##### 1、第一次启动，格式化namenode #####

[root@master ~]# hadoop namenode -format

##### 2、启动hadoop系统，并验证 #####

\[root@master ~\]\# start-all.sh  
\[root@master ~\]\# jps  
\[root@node1 ~\]\# jps  
\[root@node2 ~\]\# jps  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 9]  
![在这里插入图片描述][20200311173253238.png]  
![在这里插入图片描述][20200311173301155.png]

网页端访问master节点ip地址  
http://Master\_IP:50072  
例:  
http://10.0.0.10:50070  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 10]  
网页端查看HDFS文件系统  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 11]

## 十二、在本地编写并测试mapreduce程序，运行WordCount案例 ##

#### 编写MapReduce程序,请注意，此处使用python2代码。因为CentOS7.2已经安装了python2 ####

##### 1、首先编写mapper.py程序 #####

**\[root@master ~\]\# vi mapper.py**

#!/usr/bin/env python
    # -*- coding:UTF-8 -*-
    
    import sys
    for line in sys.stdin:
        line = line.strip()
        words = line.split()
        for word in words:
            print '%s\t%s' % (word, 1)

##### 2、编写Reducer程序 #####

**\[root@master ~\]\# vi reducer.py**

#!/usr/bin/env python
    # -*- coding:UTF-8 -*-
    
    #from operator import itemgetter
    import sys
    
    current_word = None
    current_count = 0
    word = None
    
    for line in sys.stdin:
        line = line.strip()
    
        word, count = line.split('\t', 1)
        
        try:
            count = int(count)
        except ValueError:
            continue
    
        if current_word  == word:
            current_count += count
        else:
            if current_word:
                print '%s\t%s' % (current_word, current_count)
            current_count = count
            current_word = word
            
    if current_word == word:
        print '%s\t%s' % (current_word, current_count)

##### 3、给刚刚编写的程序添加执行权限 #####

[root@master ~]# chmod a+x mapper.py  
    [root@master ~]# chmod a+x reducer.py

![在这里插入图片描述][20200313041509423.png]

##### 4、使用echo加sort对程序进行测试 #####

[root@master ~]# echo “hello world hell hi word” | python mapper.py |sort|python reducer.py

![在这里插入图片描述][20200313041608524.png]

## 十三、在hadoop中运行WordCount案例 ##

# 一定要检查一下yarn-site.xml，之前的配置文件我已经重新修改了，请回到第八步第六小点再看看，yarn-site.xml有没有添加上 #

<property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>
    <property>
        <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
        <value>org.apache.hadoop.mapred.ShuffleHandler</value>
    </property>

##### 1、首先编写MapReduce脚本mapreduce.sh #####

\[root@master ~\]\# vi mapreduce.sh

hadoop jar /opt/bigdata/hadoop-3.0.0/share/hadoop/tools/lib/hadoop-*streaming*.jar -mapper "python mapper.py" -reducer "python reducer.py" -input /user_test/
    data.txt -output /output_dir -file /opt/bigdata/mapreduce/mapper.py -file /opt/bigdata/mapreduce/reducer.py

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 12]

#streaming可以执行任意语言写的mapper，reducer程序
    -mapper "python mapper.py"  #执行mapper程序
    -reducer "python reducer.py"   #执行reducer程序
    -input /user_test/data.txt -output /output_dir  #导入文件及导出文件地址
    -file /opt/bigdata/mapreduce/mapper.py  #mapper程序路径
    -file /opt/bigdata/mapreduce/reducer.py  #reducer程序路径

##### 2、在本地，首先创建文件夹，将mapper.py和reducer.py移动到相应位置，也可在相应位置创建好 #####

**\[root@master ~\]\# mkdir /opt/bigdata/mapreduce  
\[root@master ~\]\# mv mapper.py reducer.py /opt/bigdata/mapreduce/  
\[root@master ~\]\# ls /opt/bigdata/mapreduce/**  
![在这里插入图片描述][20200313042822330.png]

##### 3、在本地创建data.txt文件，并输入相应数据 #####

**\[root@master ~\]\# vi data.txt**

java
    java
    python
    ruby
    ruby
    mongo
    ruby
    java
    python
    java
    python
    python
    java
    python
    python
    java
    python
    python
    java
    java

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 13]

##### 4、在 HDFS 文件系统中创建相应目录以及将data.txt文件上传 #####

**\[root@master ~\]\# hdfs dfs -mkdir /user\_test  
\[root@master ~\]\# hdfs dfs -chmod -R 777 /user\_test \#\#给目录添加权限  
\[root@master ~\]\# hdfs dfs -put /root/data.txt /user\_test  
\[root@master ~\]\# hdfs dfs -ls /user\_test**  
![在这里插入图片描述][20200313043346843.png]

##### 5、查看是否存在 输出目录 (一定不能存在，如果存在就需要删除) #####

\[root@master ~\]\# hdfs dfs -ls /  
![在这里插入图片描述][20200313043505658.png]

##### 6、运行mapreduce.sh脚本，测试运行 #####

**\[root@master ~\]\# source mapreduce.sh**  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 14]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 15]

###### 7、查看结果 ######

**\[root@master ~\]\# hdfs dfs -ls /output\_dir  
\[root@master ~\]\# hdfs dfs -cat /output\_dir/part-00000**  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 16]  
也可以在Web端查看  
http://Master\_I:50070  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 17]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 18]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 19]  
点击下载会提示网页无法访问，请将node1或者node2替换成相应的IP地址即可  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 20]

## 十四、利用生成文件结合python生成词云 ##

#### 这里我使用python3进行实验 ####

##### 1、将上述的文件下载到Windows #####

![在这里插入图片描述][20200313052901101.png]

##### 2、在windows下，下载/安装pip #####

pip install wordcloud（执行下载woedcloud）
    pip install matplotlib（执行下载matplotlib）

##### 3、此时我将part-00000文件存放于E盘下 #####

##### 4、编写输出词云的python程序 #####

# -*-coding:UTF-8 -*-
    # 导入相关的库
    import matplotlib #导入matplotlib
    matplotlib.use('Agg')
    from os import path
    import matplotlib.pyplot as plt
    from wordcloud import WordCloud #从wordcloud导入WordCloud
    
    # 获取当前文件路径
    # __file__ 为当前文件, 在ide中运行此行会报错,可改为
    # d = path.dirname('.')
    d = path.dirname('.') ##选择文件路径
    
    # 读取整个文件
    text = open(path.join(d, 'E:\part-00000')).read() #打开文件并赋值给变量text
    #wordcloud = WordCloud().generate(text)
    wc = WordCloud().generate(text)
    wc.to_file('Word Cloud.png') #命名生成的图片
    # 绘图
    plt.imshow(wc)
    plt.axis("off")

##### 6、运行程序得到词云图片 #####

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 21]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 22]

#### 本次教程到此结束，如果您觉得不错，可以打赏，请您到B站观看更多技术视频，欢迎点赞投币打赏！ ####

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTE1NzQ_size_16_color_FFFFFF_t_70 23]

# [B站传送门][B] #

[https_pan.baidu.com_s_1dvf4o8i9J02fmUu3SMRyDw]: https://pan.baidu.com/s/1dvf4o8i9J02fmUu3SMRyDw
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[B]: https://space.bilibili.com/384089037/video