Python结合Shell/Hadoop实现MapReduce

基本流程为：

cat data | map | sort | reduce

cat devProbe | ./mapper.py | sort| ./reducer.py

echo "foo foo quux labs foo bar quux" | ./mapper.py | sort -k1,1 | ./reducer.py

# -k, -key=POS1[,POS2]     键以pos1开始，以pos2结束

如不执行下述命令，可以再py文件前加上python调用

chmod +x mapper.py
chmod +x reducer.py

对于分布式环境下，可以使用以下命令：

hadoop jar /[YOUR_PATH]/hadoop/tools/lib/hadoop-streaming-2.6.0-cdh5.4.4.jar \
 -file mapper.py -mapper mapper.py \
 -file reducer.py -reducer reducer.py \
 -input [IN_FILE]    -output [OUT_DIR]

mapper.py

#!/usr/bin/python
# -*- coding: UTF-8 -*-

__author__ = 'Manhua'

import sys
for line in sys.stdin:
    line = line.strip()
    item = line.split('`')
    print "%s\t%s" % (item[0]+'`'+item[1], 1)

reducer.py

#!/usr/bin/python
# -*- coding: UTF-8 -*-

__author__ = 'Manhua'

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:  #count如果不是数字的话，直接忽略掉
        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 word == current_word:  #不要忘记最后的输出
    print "%s\t%s" % (current_word, current_count)