python如何链接hadoop,并且使用hadoop的资源,这篇文章介绍了一个简单的案例!
一、python的map/reduce代码
首先认为大家已经对haoop已经有了很多的了解,那么需要建立mapper和reducer,分别代码如下:
1、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 %s' %(word, 1)
2、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: words = line.strip() word, count = words.split(' ') 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)
建立了两个代码之后,测试一下:
[qiu.li@l-tdata5.tkt.cn6 /export/python]$ echo "I like python hadoop , hadoop very good" | ./mapper.py | sort -k 1,1 | ./reducer.py , 1 good 1 hadoop 2 I 1 like 1 python 1 very 1
二、上传文件
发现没啥问题,那么成功一半了,下面上传几个文件到hadoop做进一步测试。我在线上找了几个文件,命令如下:
wget http://www.gutenberg.org/ebooks/20417.txt.utf-8 wget http://www.gutenberg.org/files/5000/5000-8.txt wget http://www.gutenberg.org/ebooks/4300.txt.utf-8
查看下载的文件:
[qiu.li@l-tdata5.tkt.cn6 /export/python]$ ls 20417.txt.utf-8 4300.txt.utf-8 5000-8.txt mapper.py reducer.py run.sh
上传文件到hadoop上面,命令如下:hadoop dfs -put ./*.txt /user/ticketdev/tmp (hadoop是配置好的,目录也是建立好的)
建立run.sh
hadoop jar $STREAM -files ./mapper.py,./reducer.py -mapper ./mapper.py -reducer ./reducer.py -input /user/ticketdev/tmp/*.txt -output /user/ticketdev/tmp/output
查看结果:
[qiu.li@l-tdata5.tkt.cn6 /export/python]$ hadoop dfs -cat /user/ticketdev/tmp/output/part-00000 | sort -nk 2 | tail DEPRECATED: Use of this script to execute hdfs command is deprecated. Instead use the hdfs command for it. it 2387 which 2387 that 2668 a 3797 is 4097 to 5079 in 5226 and 7611 of 10388 the 20583
三、参考文献:
http://www.cnblogs.com/wing1995/p/hadoop.html?utm_source=tuicool&utm_medium=referral