关于hadoop运行python写的单词计数的脚本报错

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这是我参考的文章，按着这个文章来跑的程序https://blog.csdn.net/wangato...
如图，总是报第一句话的错误，我百度了原因，但是都没能解决。
1.在文章中python没有报错，按照文章中也都可以统计单词次数，但是用hadoop就报

java.lang.RuntimeException: PipeMapRed.waitOutputThreads(): subprocess failed with code 1
at org.apache.hadoop.streaming.PipeMapRed.waitOutputThreads(PipeMapRed.java:325)
    at org.apache.hadoop.streaming.PipeMapRed.mapRedFinished(PipeMapRed.java:538)
    at org.apache.hadoop.streaming.PipeMapper.close(PipeMapper.java:130)
    at org.apache.hadoop.mapred.MapRunner.run(MapRunner.java:61)
    at org.apache.hadoop.streaming.PipeMapRunner.run(PipeMapRunner.java:34)
    at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:453)
    at org.apache.hadoop.mapred.MapTask.run(MapTask.java:343)
    at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:175)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:422)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1840)
    at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:169)

新手，而且实在没找到原因。这是我的python程序
1.mapper.py

#!/usr/bin/env python3
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))

2.reduce.py

#!/usr/bin/env python3
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))

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