关于hadoop运行python写的单词计数的脚本报错
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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