hadoop maper reducer python

Hadoop MapReduce是一个分布式计算框架，可以用于处理大规模数据集。Mapper和Reducer是MapReduce的两个主要组件。Python是一种流行的编程语言，也可以用于编写Hadoop MapReduce作业。

在Python中编写MapReduce作业，您可以使用Hadoop Streaming API。该API允许您使用任何可执行文件作为Mapper和Reducer。以下是一个使用Python编写Mapper和Reducer的示例：

Mapper:

#!/usr/bin/env python

import sys

# input comes from STDIN (standard input)
for line in sys.stdin:
    # remove leading and trailing whitespace
    line = line.strip()
    # split the line into words
    words = line.split()
    # increase counters
    for word in words:
        # write the results to STDOUT (standard output);
        # what we output here will be the input for the
        # Reduce step, i.e. the input for reducer.py
        #
        # tab-delimited; the trivial word count is 1
        print '%s\t%s' % (word, 1)

Reducer:

#!/usr/bin/env python

from operator import itemgetter
import sys

current_word = None
current_count = 0
word = None

# input comes from STDIN
for line in sys.stdin:
    # remove leading and trailing whitespace
    line = line.strip()

    # parse the input we got from mapper.py
    word, count = line.split('\t', 1)

    # convert count (currently a string) to int
    try:
        count = int(count)
    except ValueError:
        # count was not a number, so silently
        # ignore/discard this line
        continue

    # this IF-switch only works because Hadoop sorts map output
    # by key (here: word) before it is passed to the reducer
    if current_word == word:
        current_count += count
    else:
        if current_word:
            # write result to STDOUT
            print '%s\t%s' % (current_word, current_count)
        current_count = count
        current_word = word

# do not forget to output the last word if needed!
if current_word == word:
    print '%s\t%s' % (current_word, current_count)

这些脚本可以使用Hadoop Streaming API提交为MapReduce作业，如下所示：

$HADOOP_HOME/bin/hadoop jar $HADOOP_HOME/share/hadoop/tools/lib/hadoop-streaming-2.7.3.jar \
-input input_file \
-output output_directory \
-mapper mapper.py \
-reducer reducer.py \
-file mapper.py \
-file reducer.py

其中，input_file是输入文件的路径，output_directory是输出目录的路径，mapper.py和reducer.py是上述Python脚本的文件名。