目的：将python实现mapreduce(1)中的python脚本部署到hadoop上，实现mapreduce。

1. 修改脚本执行权限

[tianyc@TeletekHbase ~]$ which python

/usr/bin/python

#将 #!/usr/bin/python 加到map.py和red.py的第一行，并设置执行权限。

[tianyc@TeletekHbase python]$ chmod 744 *.py

[tianyc@TeletekHbase python]$ ll

总用量 20

-rwxr--r--. 1 tianyc NEU 132 2月 19 00:40 map.py

-rwxr--r--. 1 tianyc NEU 324 2月 19 00:56 red.py

-rw-r--r--. 1 tianyc NEU 314 2月 18 22:34 test.dat

[tianyc@TeletekHbase python]$ scp ~/study/mapred/python/*.py s1:~/study/mapred/python

map.py 100% 132 0.1KB/s 00:00

red.py 100% 324 0.3KB/s 00:00

[tianyc@TeletekHbase python]$ scp ~/study/mapred/python/*.py s2:~/study/mapred/python

map.py 100% 132 0.1KB/s 00:00

red.py 100% 324 0.3KB/s 00:00

#在s1和s2上分别修改这2个脚本的权限为744

2. 将测试文件放到hdfs上

[tianyc@TeletekHbase python]$ ~/hadoop/bin/hadoop dfs -copyFromLocal test.dat test.dat

[tianyc@TeletekHbase python]$ ~/hadoop/bin/hadoop dfs -ls

Found 1 items

-rw-r--r-- 2 tianyc supergroup 314 2013-02-19 03:14 /user/tianyc/test.dat

3. 执行mapreduce

[tianyc@TeletekHbase hadoop]$ ~/hadoop/bin/hadoop jar ~/hadoop/contrib/streaming/hadoop-streaming-1.0.4.jar -mapper ~/study/mapred/python/map.py -reducer ~/study/mapred/python/red.py -input test.dat -output test-output

packageJobJar: [/tmp/hadoop-tianyc/hadoop-unjar5892434231150397369/] [] /tmp/streamjob7683487212899164160.jar tmpDir=null

13/02/20 16:45:23 INFO util.NativeCodeLoader: Loaded the native-hadoop library

13/02/20 16:45:23 WARN snappy.LoadSnappy: Snappy native library not loaded

13/02/20 16:45:23 INFO mapred.FileInputFormat: Total input paths to process : 1

13/02/20 16:45:23 INFO streaming.StreamJob: getLocalDirs(): [/tmp/hadoop-tianyc/mapred/local]

13/02/20 16:45:23 INFO streaming.StreamJob: Running job: job_201302201459_0010

13/02/20 16:45:23 INFO streaming.StreamJob: To kill this job, run:

13/02/20 16:45:23 INFO streaming.StreamJob: /home/tianyc/hadoop-1.0.4/libexec/../bin/hadoop job -Dmapred.job.tracker=http://TeletekHbase:9001 -kill job_201302201459_0010

13/02/20 16:45:23 INFO streaming.StreamJob: Tracking URL: http://TeletekHbase:50030/jobdetails.jsp?jobid=job_201302201459_0010

13/02/20 16:45:24 INFO streaming.StreamJob: map 0% reduce 0%

13/02/20 16:45:37 INFO streaming.StreamJob: map 50% reduce 0%

13/02/20 16:45:38 INFO streaming.StreamJob: map 100% reduce 0%

13/02/20 16:45:49 INFO streaming.StreamJob: map 100% reduce 100%

13/02/20 16:45:55 INFO streaming.StreamJob: Job complete: job_201302201459_0010

13/02/20 16:45:55 INFO streaming.StreamJob: Output: test-output

4. 查看执行结果

[tianyc@TeletekHbase hadoop]$ hadoop dfs -ls

Found 7 items

drwxr-xr-x - tianyc supergroup 0 2013-02-20 16:45 /user/tianyc/test-output

-rw-r--r-- 2 tianyc supergroup 314 2013-02-19 03:14 /user/tianyc/test.dat

[tianyc@TeletekHbase hadoop]$ hadoop dfs -ls test-output

Found 3 items

-rw-r--r-- 2 tianyc supergroup 0 2013-02-20 16:45 /user/tianyc/test-output/_SUCCESS

drwxr-xr-x - tianyc supergroup 0 2013-02-20 16:45 /user/tianyc/test-output/_logs

-rw-r--r-- 2 tianyc supergroup 17 2013-02-20 16:45 /user/tianyc/test-output/part-00000

[tianyc@TeletekHbase hadoop]$ hadoop dfs -cat test-output/part-00000

1949 111

1950 22

[tianyc@TeletekHbase hadoop]$

其他：

1. 执行过程可能会比较长，可以通过命令查看作业的执行情况

[tianyc@TeletekHbase ~]$ hadoop job -list

1 jobs currently running

JobId State StartTime UserName Priority SchedulingInfo

job_201302180014_0006 1 1361216791160 tianyc NORMAL NA

[tianyc@TeletekHbase ~]$ hadoop job -status job_201302180014_0006

Job: job_201302180014_0006

file: hdfs://master:9000/tmp/hadoop-tianyc/mapred/staging/tianyc/.staging/job_201302180014_0006/job.xml

tracking URL: http://master:50030/jobdetails.jsp?jobid=job_201302180014_0006

map() completion: 1.0

reduce() completion: 0.16666667

Counters: 25

Job Counters

Launched reduce tasks=3

SLOTS_MILLIS_MAPS=13255

Launched map tasks=2

Data-local map tasks=2

SLOTS_MILLIS_REDUCES=8739

File Input Format Counters

Bytes Read=472

FileSystemCounters

HDFS_BYTES_READ=656

FILE_BYTES_WRITTEN=68722

Map-Reduce Framework

Map output materialized bytes=77

Map input records=5

Reduce shuffle bytes=32

Spilled Records=5

Map output bytes=55

Total committed heap usage (bytes)=337780736

CPU time spent (ms)=2790

Map input bytes=314

SPLIT_RAW_BYTES=184

Combine input records=0

Reduce input records=0

Reduce input groups=0

Combine output records=0

Physical memory (bytes) snapshot=334417920

Reduce output records=0

Virtual memory (bytes) snapshot=1138679808

Map output records=5

2. 若mr执行失败，可以通过浏览器登录jobtracker的web控制台查看具体的故障堆栈。一般在jobtracker的50030端口(http://jobmaster:50030)。

我的错误提示为：Shuffle Error: Exceeded MAX_FAILED_UNIQUE_FETCHES; bailing-out 解决办法可以参考这个帖子。因为我最初是参考这个帖子部署的hadoop，设置了master，s1和s2，这与/etc/sysconfig/network中的HOSTNAME不一致了。

3. 将/etc/hosts与/etc/sysconfig/network设置一致后，仍然出现了问题。详细描述参考这里。