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_Name','S_Sex','S_Age'
put 'Student','2015001','S_Name','Zhangshan'
put 'Student','2015001','S_Sex','male'

put 'Student','2015001','S_Age','23'

put 'Student','2015002','S_Name','Mary'

put 'Student','2015002','S_Sex','female'

put 'Student','2015002','S_Age','22'

put 'Student','2015003','S_name','Lisi'

put 'Student','2015003','S_Sex','male'

put 'Student','2015003','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'

 

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
    1. #!/usr/bin/env python
      import sys
      for i in stdin:
          i = i.strip()
          words = i.split()
          for word in words:
          print '%s\t%s' % (word,1)
    2. #!/usr/bin/env python
      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)
  2. 将其权限作出相应修改
    1. chmod a+x /home/hadoop/mapper.py
  3. 本机上测试运行代码
    1. 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
  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
  7. 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

     

posted @ 2018-05-08 21:25  150颜杰文  阅读(98)  评论(0编辑  收藏  举报