理解MapReduce计算构架

1.编写map函数，reduce函数

（1）建立mapper.py文件

cd /home/hadoop/wc 

gedit mapper.p

 

（2）mapper函数

 

#!/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)

（3）reducer.py文件建立

cd /home/hadoop/wc

gedit reducer.py

（4）reducer函数

#!/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.将其权限做出相应修改

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


3.本机上测试运行代码

放到HDFS上运行

下载并上传文件到hdfs上

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