理解MapReduce计算构架

Posted 2020-11-04 懒得、起昵称

用Python编写WordCount程序任务

程序	WordCount
输入	一个包含大量单词的文本文件
输出	文件中每个单词及其出现次数（频数），并按照单词字母顺序排序，每个单词和其频数占一行，单词和频数之间有间隔

1. 编写map函数，reduce函数
2. 将其权限作出相应修改
3. 本机上测试运行代码
4. 放到HDFS上运行
5. 下载并上传文件到hdfs上
6. 用Hadoop Streaming命令提交任务

   create ‘Student‘, ‘ S_No  ‘,‘S_Name‘, ‘S_Sex‘,‘S_Age‘
   
   put ‘Student‘,‘s001‘,‘S_No‘,‘2015001‘
   put ‘Student‘,‘s001‘,‘S_Name‘,‘Zhangsan‘
   put ‘Student‘,‘s001‘,‘S_Sex‘,‘male‘
   put ‘Student‘,‘s001‘,‘S_Age‘,‘23‘
   
   put ‘Student‘,‘s002‘,‘S_No‘,‘2015003‘
   put ‘Student‘,‘s002‘,‘S_Name‘,‘Mary‘
   put ‘Student‘,‘s002‘,‘S_Sex‘,‘female‘
   put ‘Student‘,‘s002‘,‘S_Age‘,‘22‘
   
   put ‘Student‘,‘s003‘,‘S_No‘,‘2015003‘
   put ‘Student‘,‘s003‘,‘S_Name‘,‘Lisi‘
   put ‘Student‘,‘s003‘,‘S_Sex‘,‘male‘
   put ‘Student‘,‘s003‘,‘S_Age‘,‘24‘
   

   　　

   scan ‘Student‘
   alter ‘Student‘,‘NAME‘=>‘course‘
   put ‘Student‘,‘3‘,‘course:Math‘,‘85‘
   dorp ‘Student‘,‘course‘
   count ‘s1‘
   truncate ‘s1‘
   

   　　

   cd /home/hadoop/wc
   sudo gedit mapper.py
   
   # map函数
   import sys
   for i in stdin:
       i = i.strip()
       words = i.split()
       for word in words:
       print ‘%s\t%s‘ % (word,1)
   
   #reduce函数
   from operator import itemgetter
   import sys
   
   current_word = None
   current_count = 0
   word = None
   
   for i in stdin:
       i = i.strip()
       word, count = i.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)
   

   　　

   chmod a+x /home/hadoop/mapper.py
   

   　　

   echo "foo foo quux labs foo bar quux" | /home/hadoop/wc/mapper.py
   
   echo "foo foo quux labs foo bar quux" | /home/hadoop/wc/mapper.py | sort -k1,1 | /home/hadoop/wc/reducer.p
   

   　　

   cd  /home/hadoop/wc
   wget http://www.gutenberg.org/files/5000/5000-8.txt
   wget http://www.gutenberg.org/cache/epub/20417/pg20417.txt
   
   
   cd /usr/hadoop/wc
   hdfs dfs -put /home/hadoop/hadoop/gutenberg/*.txt /user/hadoop/input