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  • 熟悉常用的HBase操作,编写MapReduce作业

    1. 以下关系型数据库中的表和数据,要求将其转换为适合于HBase存储的表并插入数据:

    学生表(Student)(不包括最后一列)

    学号(S_No)

    姓名(S_Name)

    性别(S_Sex)

    年龄(S_Age)

    课程(course)

    2015001

    Zhangsan

    male

    23

     

    2015003

    Mary

    female

    22

     

    2015003

    Lisi

    male

    24

    数学(Math)85

      

    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'

    2. 用Hadoop提供的HBase Shell命令完成相同任务:

    • 列出HBase所有的表的相关信息;list
    • 在终端打印出学生表的所有记录数据;
    • 向学生表添加课程列族;
    • 向课程列族添加数学列并登记成绩为85;
    • 删除课程列;
    • 统计表的行数;count 's1'
    • 清空指定的表的所有记录数据;truncate 's1'
    scan 'Student'
    alter 'Student','NAME'=>'course'
    put 'Student','3','course:Math','85'
    dorp 'Student','course'
    count 's1'
    truncate 's1'

    3. 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. 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	%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('	',1)
            try:
            count = int(count)
            except ValueError:
            continue
        
            if current_word == word:
            current_count += count 
            else:
            if current_word:
                print '%s	%s' % (current_word, current_count)
            current_count = count
            current_word = word
        
        if current_word == word:
            print '%s	%s' % (current_word, current_count)
      3. 将其权限作出相应修改
      4. chmod a+x /home/hadoop/mapper.py
      5. 本机上测试运行代码
      6. 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
      7. 放到HDFS上运行
      8. 下载并上传文件到hdfs上
      9. 用Hadoop Streaming命令提交任务
      10. 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
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  • 原文地址:https://www.cnblogs.com/xuyizhu/p/9005414.html
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