理解MapReduce计算构架

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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
    cd /home/hadoop
    mkdir wc
    cd /home/hadoop/wc
    touch mapper.py
    
    touch reducer.py
    

      

     编写两个函数

      mapper.py:

    #!/usr/bin/env python
    import sys
    for line in sys.stdin:
        line = line.strip()
        words = line.split()
        for word in words:
            print ‘%s\t%s‘ % (word,1)
    

      reducer.py:

    #!/usr/bin/env python
    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)
    

      

  2. 将其权限作出相应修改

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

        

  3. 本机上测试运行代码
    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.py
    

      

  4. 放到HDFS上运行
    cd  /home/hadoop/wc
    wget http://www.gutenberg.org/files/5000/5000-8.txt
    wget http://www.gutenberg.org/cache/epub/20417/pg20417.txt
    

      

  5. 下载并上传文件到hdfs上
    hdfs dfs -put /home/hadoop/hadoop/gutenberg/*.txt /user/hadoop/input
    

      

  6. 用Hadoop Streaming命令提交任务
    cd /usr/local/hadoop/share/hadoop/tools/lib/hadoop-streaming-2.7.1.jar
    

      

    gedit ~/.bashrc
    

      

    export STREAM=$HADOOP_HOME/share/hadoop/tools/lib/hadoop-streaming-*.jar
    

      

    source ~/.bashrc
    echo $STREAM
    

      

    gedit run.sh
    

      

    hadoop jar $STREAM
    -file /home/hadoop/wc/mapper.py -mapper /home/hadoop/wc/mapper.py -file /home/hadoop/wc/reducer.py -reducer /home/hadoop/wc/reducer.py -input /user/hadoop/input/*.txt -output /user/hadoop/wcoutput
    

      

    source run.sh
    

      

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