标签：one AC 上传 red tput org tin 文本文件 文本
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
首先在/home/hadoop路径下建立wc文件夹，在wc文件夹下创建文件mapper.py和reducer.py
cd /home/hadoop mkdir wc cd /home/hadoop/wc touch mapper.py touch reducer.py
编写两个函数mapper:
import sys
for line in sys.stdin:
line = line.strip()
words = line.split()
for word in words:
print ‘%s\t%s‘ % (word,1)
reduces.py:
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:
寻找你的streaming的jar文件存放地址：
cd /usr/local/hadoop/share/hadoop/tools/lib/hadoop-streaming-2.7.1.jar
打开环境变量配置文件:
gedit ~/.bashrc
在里面写入streaming路径:
export STREAM=$HADOOP_HOME/share/hadoop/tools/lib/hadoop-streaming-*.jar
让环境变量生效:
source ~/.bashrc echo $STREAM
建立一个shell名称为run.sh来运行：
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
标签：one AC 上传 red tput org tin 文本文件 文本
原文地址：https://www.cnblogs.com/229zyx/p/9026628.html
