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理解MapReduce计算构架

时间:2018-05-12 02:28:50      阅读:218      评论:0      收藏:0      [点我收藏+]

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
    

      

理解MapReduce计算构架

原文:https://www.cnblogs.com/Runka/p/9026668.html

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