Question

我正在尝试解决Hadoop流中的倒排单词列表问题（对于每个单词，输出是包含该单词的文件名列表）。输入是包含文本文件的目录的名称。我已经用python编写了mapper和reducer，在尝试使用unix管道时它们可以正常工作。但是，使用Hadoop流命令执行时，代码会运行，但最终作业会失败。我怀疑这是Mapper代码中的内容，但似乎无法确切知道问题所在。

我是初学者（因此，如果我做的不好，请原谅），并在VMware Fusion上使用Cloudera培训。我的Mapper和Reducer .py可执行文件放在本地系统以及hdfs的主目录中。我在hdfs上有目录“莎士比亚”。下面的unix pipe命令可以正常工作。

回音莎士比亚| ./InvertedMapper.py |排序./InvertedReducer.py

但是，haddop流没有。

hadoop jar /usr/lib/hadoop-0.20-mapreduce/contrib/streaming/hadoop-streaming*.jar-输入莎士比亚-输出InvertedList -mapper InvertedMapper.py -reducer InvertedReducer.py -file InvertedMapper.py -file InvertedReducer .py

#MAPPER CODE

#!/usr/bin/env python

import sys
import os

class Mapper(object):

        def __init__(self, stream, sep='\t'):
                self.stream=stream
                self.sep=sep

        def __iter__(self):
                os.chdir(self.stream.read().strip())
                files = [os.path.abspath(f) for f in os.listdir(".")]
                for file in files:
                        yield file

        def emit(self, key, value):
                sys.stdout.write("{0}{1}{2}\n".format(key,self.sep,value))

        def map(self):
                for file in self:
                        with open(file) as infile:
                                name = file.split("/")[-1].split(".")[0]
                                words = infile.read().strip().split()
                                for word in words:
                                        self.emit(word,name)

 if __name__ == "__main__":
        cwd = os.getcwd()
        mapper = Mapper(sys.stdin)
        mapper.map()
        os.chdir(cwd)


#REDUCER CODE

#!/usr/bin/env python

import sys
from itertools import groupby
from operator import itemgetter

class Reducer(object):
        def __init__(self, stream, sep="\t"):
                self.stream = stream
                self.sep = sep

        def __iter__(self):
                for line in self.stream:
                        try:
                                parts = line.strip().split(self.sep)
                                yield parts[0], parts[1]
                        except:
                                continue

        def emit(self, key, value):
                sys.stdout.write("{0}{1}{2}\n".format(key, self.sep, value))

        def reduce(self):
                for key, group in groupby(self, itemgetter(0)):
                        values = []
                        for item in group:
                                values.append(item[1])
                        values = set(values)
                        values = list(values)
                        self.emit(key, values)
if __name__ == "__main__":
    reducer = Reducer(sys.stdin)
    reducer.reduce()

运行Hadoop命令的输出如下。

packageJobJar: [InvertedMapper1.py, /tmp/hadoop-training/hadoop-unjar281431668511629942/] [] /tmp/streamjob679048425003800890.jar tmpDir=null
19/02/17 00:22:19 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
19/02/17 00:22:19 INFO mapred.FileInputFormat: Total input paths to process : 5
19/02/17 00:22:20 INFO streaming.StreamJob: getLocalDirs(): [/var/lib/hadoop-hdfs/cache/training/mapred/local]
19/02/17 00:22:20 INFO streaming.StreamJob: Running job: job_201902041621_0051
19/02/17 00:22:20 INFO streaming.StreamJob: To kill this job, run:
19/02/17 00:22:20 INFO streaming.StreamJob: UNDEF/bin/hadoop job  -Dmapred.job.tracker=0.0.0.0:8021 -kill job_201902041621_0051
19/02/17 00:22:20 INFO streaming.StreamJob: Tracking URL: http://0.0.0.0:50030/jobdetails.jsp?jobid=job_201902041621_0051
19/02/17 00:22:21 INFO streaming.StreamJob:  map 0%  reduce 0%
19/02/17 00:22:34 INFO streaming.StreamJob:  map 40%  reduce 0%
19/02/17 00:22:39 INFO streaming.StreamJob:  map 0%  reduce 0%
19/02/17 00:22:50 INFO streaming.StreamJob:  map 40%  reduce 0%
19/02/17 00:22:53 INFO streaming.StreamJob:  map 0%  reduce 0%
19/02/17 00:23:03 INFO streaming.StreamJob:  map 40%  reduce 0%
19/02/17 00:23:06 INFO streaming.StreamJob:  map 20%  reduce 0%
19/02/17 00:23:07 INFO streaming.StreamJob:  map 0%  reduce 0%
19/02/17 00:23:16 INFO streaming.StreamJob:  map 20%  reduce 0%
19/02/17 00:23:17 INFO streaming.StreamJob:  map 40%  reduce 0%
19/02/17 00:23:19 INFO streaming.StreamJob:  map 20%  reduce 0%
19/02/17 00:23:21 INFO streaming.StreamJob:  map 100%  reduce 100%
19/02/17 00:23:21 INFO streaming.StreamJob: To kill this job, run:
19/02/17 00:23:21 INFO streaming.StreamJob: UNDEF/bin/hadoop job  -Dmapred.job.tracker=0.0.0.0:8021 -kill job_201902041621_0051
19/02/17 00:23:21 INFO streaming.StreamJob: Tracking URL: http://0.0.0.0:50030/jobdetails.jsp?jobid=job_201902041621_0051
19/02/17 00:23:21 ERROR streaming.StreamJob: Job not successful. Error: NA
19/02/17 00:23:21 INFO streaming.StreamJob: killJob...
Streaming Command Failed!

Answer 1

我不知道这是否是您的代码失败的原因，但常见问题解答指出不应在 Hadoop Streaming 中使用 unix 管道。

https://hadoop.apache.org/docs/current/hadoop-streaming/HadoopStreaming.html#Frequently_Asked_Questions

映射器代码与unix管道一起运行，但不能与hadoop流一起运行。错误NA。流命令失败

1 个答案: