嗨，我用python编写了两个脚本，作为hadoop流的Map器和还原器。我运行代码，它成功地完成了Map和缩减，都是100%。但它只是挂在那里的过程结束。
输出如下所示：

...
13/10/07 17:25:16 INFO streaming.StreamJob:  map 99%  reduce 30%
13/10/07 17:26:18 INFO streaming.StreamJob:  map 99%  reduce 31%
13/10/07 17:26:55 INFO streaming.StreamJob:  map 99%  reduce 32%
13/10/07 17:28:16 INFO streaming.StreamJob:  map 100%  reduce 32%
13/10/07 17:29:08 INFO streaming.StreamJob:  map 100%  reduce 33%
13/10/07 17:30:55 INFO streaming.StreamJob:  map 100%  reduce 39%
13/10/07 17:30:56 INFO streaming.StreamJob:  map 100%  reduce 46%
13/10/07 17:30:57 INFO streaming.StreamJob:  map 100%  reduce 52%
13/10/07 17:30:58 INFO streaming.StreamJob:  map 100%  reduce 72%
13/10/07 17:31:00 INFO streaming.StreamJob:  map 100%  reduce 74%
13/10/07 17:31:01 INFO streaming.StreamJob:  map 100%  reduce 89%
13/10/07 17:31:02 INFO streaming.StreamJob:  map 100%  reduce 98%
13/10/07 17:31:03 INFO streaming.StreamJob:  map 100%  reduce 99%
13/10/07 17:31:57 INFO streaming.StreamJob:  map 100%  reduce 100%
13/10/07 17:32:00 INFO streaming.StreamJob: Job complete: job_201309301959_0100
13/10/07 17:32:00 INFO streaming.StreamJob: Output: /tmp/binwang_31

我们的集群是由ganglia监控的，我可以清楚地看到所有节点都恢复了正常，没有进行繁重的计算。同时，我去了hdfs，可以在那里找到我的输出(不确定是否完成）。在我看来，整个MapReduce似乎已经成功完成，但终端挂在最后一步超过10分钟。。。
我想知道怎么会发生这种情况，我应该按ctrl+z停止它，还是再给几分钟。有人知道output:... 这一步要花那么长时间？如果不是，原因可能是什么？

下面是我打开另一个会话并运行命令时的响应

$ /usr/bin/hadoop job -status job_201309301959_0100
DEPRECATED: Use of this script to execute mapred command is deprecated.
Instead use the mapred command for it.

Job: job_201309301959_0100
file: hdfs://url1:8020/user/user1/.staging/job_201309301959_0100/job.xml
tracking URL: http://url1:50030/jobdetails.jsp?jobid=job_201309301959_0100
map() completion: 1.0
reduce() completion: 1.0
Counters: 34
    File System Counters
            FILE: Number of bytes read=232427562
            FILE: Number of bytes written=835363817
            FILE: Number of read operations=0
            FILE: Number of large read operations=0
            FILE: Number of write operations=0
            HDFS: Number of bytes read=107873895369
            HDFS: Number of bytes written=51760077
            HDFS: Number of read operations=1722
            HDFS: Number of large read operations=0
            HDFS: Number of write operations=144
    Job Counters
            Launched map tasks=803
            Launched reduce tasks=72
            Data-local map tasks=731
            Rack-local map tasks=72
            Total time spent by all maps in occupied slots (ms)=521490905
            Total time spent by all reduces in occupied slots (ms)=47701745
            Total time spent by all maps waiting after reserving slots (ms)=0
            Total time spent by all reduces waiting after reserving slots (ms)=0
    Map-Reduce Framework
            Map input records=425093
            Map output records=10311822
            Map output bytes=906412336
            Input split bytes=111617
            Combine input records=0
            Combine output records=0
            Reduce input groups=550636
            Reduce shuffle bytes=452246236
            Reduce input records=10311822
            Reduce output records=550636
            Spilled Records=20623644
            CPU time spent (ms)=479770510
            Physical memory (bytes) snapshot=533152505856
            Virtual memory (bytes) snapshot=1439405166592
            Total committed heap usage (bytes)=844896337920
    org.apache.hadoop.mapreduce.lib.input.FileInputFormatCounter
            BYTES_READ=107742318536

提前谢谢。