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)

巴特西

Python结合Shell/Hadoop实现MapReduce

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