我在hadoop流媒体中运行一个简单的python代码时遇到了一个问题。我尝试了所有的建议，在以前的职位与类似的错误，仍然有问题。
添加了usr/bin/env python
chmoda+xMap器和python代码
在python mapper.py-n 1-r 0.4中为-mapper放入“”
我已经在外面运行了代码，效果很好。
更新：我使用以下代码在hadoop流之外运行代码：

cat file |python mapper.py -n 5 -r 0.4 |sort|python reducer.py -f 3618

这很管用。。但是现在我需要运行它到hadoop流媒体

hadoop jar /usr/lib/hadoop-mapreduce/hadoop-streaming.jar \
-D mapreduce.job.reduces=5  \
-files lr \
-mapper "python lr/mapper.py -n 5 -r 0.4"  \
-reducer "python lr/reducer.py -f 3618"  \
-input training \
-output models

hadoop流媒体是失败的。我看了看日志，上面没有任何东西告诉我为什么会这样？
我有以下mapper.py：

# !/usr/bin/env python

import sys
import random

from optparse import OptionParser

parser = OptionParser()
parser.add_option("-n", "--model-num", action="store", dest="n_model",
                  help="number of models to train", type="int")
parser.add_option("-r", "--sample-ratio", action="store", dest="ratio",
                  help="ratio to sample for each ensemble", type="float")

options, args = parser.parse_args(sys.argv)

random.seed(8803)
r = options.ratio
for line in sys.stdin:
    # TODO
    # Note: The following lines are only there to help 
    #       you get started (and to have a 'runnable' program). 
    #       You may need to change some or all of the lines below.
    #       Follow the pseudocode given in the PDF.
    key = random.randint(0, options.n_model-1)
    value = line.strip()
    for i in range(1, options.n_model+1):
        m = random.random()
        if m < r:
            print "%d\t%s" % (i, value)

还有我的减速机.py：

# !/usr/bin/env python

import sys
import pickle
from optparse import OptionParser
from lrsgd import LogisticRegressionSGD
from utils import parse_svm_light_line

parser = OptionParser()
parser.add_option("-e", "--eta", action="store", dest="eta",
                  default=0.01, help="step size", type="float")
parser.add_option("-c", "--Regularization-Constant", action="store", dest="C",
                  default=0.0, help="regularization strength", type="float")
parser.add_option("-f", "--feature-num", action="store", dest="n_feature",
                  help="number of features", type="int")
options, args = parser.parse_args(sys.argv)

classifier = LogisticRegressionSGD(options.eta, options.C, options.n_feature)

for line in sys.stdin:
    key, value = line.split("\t", 1)
    value = value.strip()
    X, y = parse_svm_light_line(value)
    classifier.fit(X, y)

pickle.dump(classifier, sys.stdout)

当我在代码外运行它时，它运行正常，但当我在hadoop流媒体中运行它时，它会给我错误：

17/02/07 07:44:34 INFO mapreduce.Job: Task Id : attempt_1486438814591_0038_m_000001_2, Status : FAILED
Error: java.lang.RuntimeException: PipeMapRed.waitOutputThreads(): subprocess failed with code 2
    at org.apache.hadoop.streaming.PipeMapRed.waitOutputThreads(PipeMapRed.java:322)
    at org.apache.hadoop.streaming.PipeMapRed.mapRedFinished(PipeMapRed.java:535)
    at org.apache.hadoop.streaming.PipeMapper.close(PipeMapper.java:130)