我正在尝试使用 Cloudera 5.5.0 实现一个简单的 Hadoop map reduce 示例 应该使用 Python 2.6.6 实现 map 和 reduce 步骤
问题：
- 如果脚本在 unix 命令行上执行，它们工作得非常好并产生预期的输出。
cat join2*.txt | ./join3_mapper.py | 排序 | ./join3_reducer.py
- 但是将脚本作为 hadoop 任务执行非常失败：
hadoop jar /usr/lib/hadoop-mapreduce/hadoop-streaming.jar -input /user/cloudera/inputTV/join2_gen*.txt -output /user/cloudera/output_tv -mapper /home/cloudera/join3_mapper.py -reducer /主页/cloudera/join3_reducer.py -numReduceTasks 1
16/01/06 12:32:32 INFO mapreduce.Job: Task Id : attempt_1452069211060_0026_r_000000_0, Status : FAILED
Error: 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.PipeReducer.close(PipeReducer.java:134)
at org.apache.hadoop.io.IOUtils.cleanup(IOUtils.java:244)
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.YarnChild$2.run(YarnChild.java:163)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1671)
at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:158)
映射器工作，如果使用 -numReduceTasks 0 执行 hadoop 命令，则 hadoop 作业仅执行映射步骤，成功结束，输出目录包含映射步骤的结果文件。
我想reduce步骤一定有问题吗？
- Hue 中的 stderr 日志没有显示任何相关内容：
日志上传时间：2016 年 1 月 6 日星期三 12:33:10 -0800 日志长度：222 log4j:WARN 找不到记录器（org.apache.hadoop.ipc.Server）的附加程序。log4j:WARN 请正确初始化 log4j 系统。log4j:WARN 有关详细信息，请参阅http://logging.apache.org/log4j/1.2/faq.html#noconfig。
脚本代码：第一个文件：join3_mapper.py
#!/usr/bin/env python
import sys
for line in sys.stdin:
line = line.strip() #strip out carriage return
tuple2 = line.split(",") #split line, into key and value, returns a list
if len(tuple2) == 2:
key = tuple2[0]
value = tuple2[1]
if value == 'ABC':
print('%s\t%s' % (key, value) )
elif value.isdigit():
print('%s\t%s' % (key, value) )
第二个文件：join3_reducer.py
#!/usr/bin/env python
import sys
last_key = None #initialize these variables
running_total = 0
abcFound =False;
this_key = None
# -----------------------------------
# Loop the file
# --------------------------------
for input_line in sys.stdin:
input_line = input_line.strip()
# --------------------------------
# Get Next Key value pair, splitting at tab
# --------------------------------
tuple2 = input_line.split("\t")
this_key = tuple2[0]
value = tuple2[1]
if value.isdigit():
value = int(value)
# ---------------------------------
# Key Check part
# if this current key is same
# as the last one Consolidate
# otherwise Emit
# ---------------------------------
if last_key == this_key:
if value == 'ABC': # filter for only ABC in TV shows
abcFound=True;
else:
if isinstance(value, (int,long) ):
running_total += value
else:
if last_key: #if this key is different from last key, and the previous
# (ie last) key is not empy,
# then output
# the previous <key running-count>
if abcFound:
print('%s\t%s' % (last_key, running_total) )
abcFound=False;
running_total = value #reset values
last_key = this_key
if last_key == this_key:
print('%s\t%s' % (last_key, running_total) )
我尝试了各种不同的方式将输入文件声明为 hadoop 命令，没有区别，没有成功。
我究竟做错了什么 ？提示，想法非常感谢谢谢