os.environ ['mapreduce_map_input_file']不起作用

问题描述 投票：5回答：1

[我在Python中创建了一个简单的map reduce，只是为了测试os.environ['mapreduce_map_input_file']调用，如下所示：

map.py

#!/usr/bin/python
import sys

# input comes from STDIN (stream data that goes to the program)
for line in sys.stdin:

    l = line.strip().split()

    for word in l:

        # output goes to STDOUT (stream data that the program writes)
        print "%s\t%d" %( word, 1 )

reduce.py

#!/usr/bin/python
import sys
import os

current_word = None
current_sum = 0

# input comes from STDIN (stream data that goes to the program)
for line in sys.stdin:

    word, count = line.strip().split("\t", 1)

    try:
        count = int(count)
        except ValueError:
        continue

    if word == current_word:
        current_sum += count
    else:
            if current_word:
            # output goes to STDOUT (stream data that the program writes)
            print "%s\t%d" %( current_word, current_sum )
            print (os.environ['mapreduce_map_input_file'])
        current_word = word
        current_sum = count

错误消息：

Traceback (most recent call last):
  File "/Users/brunomacedo/Desktop/Big-Data/./reduce.py", line 25, in <module>
    print (os.environ['mapreduce_map_input_file'])
  File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/UserDict.py", line 23, in __getitem__
    raise KeyError(key)
KeyError: 'mapreduce_map_input_file'
15/03/06 17:50:26 INFO streaming.PipeMapRed: Records R/W=16127/1
15/03/06 17:50:26 INFO streaming.PipeMapRed: MRErrorThread done
15/03/06 17:50:26 WARN streaming.PipeMapRed: java.io.IOException: Stream closed
15/03/06 17:50:26 INFO streaming.PipeMapRed: PipeMapRed failed!
java.lang.RuntimeException: PipeMapRed.waitOutputThreads(): subprocess failed with code 1
    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.PipeReducer.reduce(PipeReducer.java:128)
    at org.apache.hadoop.mapred.ReduceTask.runOldReducer(ReduceTask.java:444)
    at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:392)
    at org.apache.hadoop.mapred.LocalJobRunner$Job$ReduceTaskRunnable.run(LocalJobRunner.java:319)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)
15/03/06 17:50:26 WARN streaming.PipeMapRed: java.io.IOException: Stream closed
15/03/06 17:50:26 INFO streaming.PipeMapRed: PipeMapRed failed!
java.lang.RuntimeException: PipeMapRed.waitOutputThreads(): subprocess failed with code 1
    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.PipeReducer.close(PipeReducer.java:134)
    at org.apache.hadoop.io.IOUtils.cleanup(IOUtils.java:237)
    at org.apache.hadoop.mapred.ReduceTask.runOldReducer(ReduceTask.java:459)
    at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:392)
    at org.apache.hadoop.mapred.LocalJobRunner$Job$ReduceTaskRunnable.run(LocalJobRunner.java:319)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)
15/03/06 17:50:26 INFO mapred.LocalJobRunner: reduce task executor complete.
15/03/06 17:50:26 WARN mapred.LocalJobRunner: job_local1265836882_0001
java.lang.Exception: java.lang.RuntimeException: PipeMapRed.waitOutputThreads(): subprocess failed with code 1
    at org.apache.hadoop.mapred.LocalJobRunner$Job.runTasks(LocalJobRunner.java:462)
    at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:529)
Caused by: java.lang.RuntimeException: PipeMapRed.waitOutputThreads(): subprocess failed with code 1
    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.PipeReducer.close(PipeReducer.java:134)
    at org.apache.hadoop.io.IOUtils.cleanup(IOUtils.java:237)
    at org.apache.hadoop.mapred.ReduceTask.runOldReducer(ReduceTask.java:459)
    at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:392)
    at org.apache.hadoop.mapred.LocalJobRunner$Job$ReduceTaskRunnable.run(LocalJobRunner.java:319)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)
15/03/06 17:50:27 INFO mapreduce.Job: Job job_local1265836882_0001 failed with state FAILED due to: NA
15/03/06 17:50:27 INFO mapreduce.Job: Counters: 35
    File System Counters
        FILE: Number of bytes read=181735210
        FILE: Number of bytes written=292351104
        FILE: Number of read operations=0
        FILE: Number of large read operations=0
        FILE: Number of write operations=0
        HDFS: Number of bytes read=0
        HDFS: Number of bytes written=0
        HDFS: Number of read operations=0
        HDFS: Number of large read operations=0
        HDFS: Number of write operations=0
    Map-Reduce Framework
        Map input records=100
        Map output records=334328
        Map output bytes=2758691
        Map output materialized bytes=3427947
        Input split bytes=14100
        Combine input records=0
        Combine output records=0
        Reduce input groups=0
        Reduce shuffle bytes=3427947
        Reduce input records=0
        Reduce output records=0
        Spilled Records=334328
        Shuffled Maps =100
        Failed Shuffles=0
        Merged Map outputs=100
        GC time elapsed (ms)=1224
        Total committed heap usage (bytes)=49956257792
    Shuffle Errors
        BAD_ID=0
        CONNECTION=0
        IO_ERROR=0
        WRONG_LENGTH=0
        WRONG_MAP=0
        WRONG_REDUCE=0
    File Input Format Counters
        Bytes Read=2090035
    File Output Format Counters
        Bytes Written=0
15/03/06 17:50:27 ERROR streaming.StreamJob: Job not successful!
Streaming Command Failed!

我用来运行它的命令：

hadoop jar /usr/local/Cellar/hadoop/2.6.0/libexec/share/hadoop/tools/lib/hadoop-streaming-2.6.0.jar \
-D mapreduce.job.reduces=1 \
-file map.py \
-mapper map.py \
-file reduce.py \
-reducer reduce.py \
-input file:///Users/brunomacedo/Desktop/Big-Data/articles \
-output file:///Users/brunomacedo/Desktop/Big-Data/output

如果我删除print (os.environ['mapreduce_map_input_file'])行，则效果很好。该行的目的是打印单词计数来自的输入文件的名称。无论如何，我这样做只是为了测试此命令，因为我需要在更复杂的项目中使用它。

有人可以帮我解决这个电话有什么问题吗？非常感谢你！

编辑：

我正在使用Hadoop 2.6.0

mapreduce hadoop-streaming
1个回答
6
投票

当我在os.environ['mapreduce_map_input_file']文件中调用os.environ['map_input_file']或reduce时，它不起作用。但是它可以在map文件中使用。这很有意义，因为reducer无法知道mapper输出来自哪个输入文件（除非您直接从mapper发送该信息）。

我无法直接运行os.environ['mapreduce_map_input_file']或os.environ['map_input_file']。因此，我在映射器中使用它来使其工作：

try:
    input_file = os.environ['mapreduce_map_input_file']
except KeyError:
    input_file = os.environ['map_input_file']
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