我正在运行一个配置单元脚本，在一个由5452689行和7gb数据大小组成的表中执行一些操作。然而，我的map reduce卡在大约70%的位置，并给出了一个没有空格的错误
误差如下：

Hadoop job information for Stage-4: number of mappers: 27; number of reducers: 1
2015-06-23 01:47:43,748 Stage-4 map = 0%,  reduce = 0%
2015-06-23 01:48:04,550 Stage-4 map = 1%,  reduce = 0%, Cumulative CPU 258.06 sec
2015-06-23 01:48:06,661 Stage-4 map = 2%,  reduce = 0%, Cumulative CPU 331.98 sec
2015-06-23 01:48:07,796 Stage-4 map = 3%,  reduce = 0%, Cumulative CPU 370.35 sec
2015-06-23 01:48:09,931 Stage-4 map = 4%,  reduce = 0%, Cumulative CPU 406.65 sec
2015-06-23 01:48:28,778 Stage-4 map = 7%,  reduce = 0%, Cumulative CPU 973.33 sec
2015-06-23 01:48:30,987 Stage-4 map = 8%,  reduce = 0%, Cumulative CPU 1034.17 sec
2015-06-23 01:48:34,251 Stage-4 map = 11%,  reduce = 0%, Cumulative CPU 1121.22 sec
2015-06-23 01:48:35,419 Stage-4 map = 13%,  reduce = 0%, Cumulative CPU 1173.4 sec
2015-06-23 01:48:36,458 Stage-4 map = 18%,  reduce = 0%, Cumulative CPU 1191.29 sec
2015-06-23 01:48:37,499 Stage-4 map = 22%,  reduce = 0%, Cumulative CPU 1215.44 sec
2015-06-23 01:48:38,607 Stage-4 map = 29%,  reduce = 0%, Cumulative CPU 1267.07 sec
2015-06-23 01:48:39,671 Stage-4 map = 32%,  reduce = 0%, Cumulative CPU 1289.57 sec
2015-06-23 01:48:40,883 Stage-4 map = 34%,  reduce = 0%, Cumulative CPU 1309.96 sec
2015-06-23 01:48:41,922 Stage-4 map = 36%,  reduce = 0%, Cumulative CPU 1366.31 sec
2015-06-23 01:48:48,693 Stage-4 map = 39%,  reduce = 0%, Cumulative CPU 1554.9 sec
2015-06-23 01:48:54,121 Stage-4 map = 40%,  reduce = 0%, Cumulative CPU 1709.04 sec
2015-06-23 01:49:00,973 Stage-4 map = 43%,  reduce = 0%, Cumulative CPU 1895.86 sec
2015-06-23 01:49:03,099 Stage-4 map = 46%,  reduce = 0%, Cumulative CPU 1976.89 sec
2015-06-23 01:49:05,180 Stage-4 map = 49%,  reduce = 0%, Cumulative CPU 2003.08 sec
2015-06-23 01:49:06,225 Stage-4 map = 58%,  reduce = 0%, Cumulative CPU 2062.33 sec
2015-06-23 01:49:07,353 Stage-4 map = 60%,  reduce = 0%, Cumulative CPU 2067.9 sec
2015-06-23 01:49:08,388 Stage-4 map = 66%,  reduce = 0%, Cumulative CPU 2087.55 sec
2015-06-23 01:49:09,551 Stage-4 map = 74%,  reduce = 2%, Cumulative CPU 2112.96 sec
2015-06-23 01:49:10,607 Stage-4 map = 75%,  reduce = 2%, Cumulative CPU 2118.14 sec
2015-06-23 01:49:11,669 Stage-4 map = 19%,  reduce = 0%, Cumulative CPU 433.75 sec
2015-06-23 01:49:12,699 Stage-4 map = 16%,  reduce = 0%, Cumulative CPU 350.93 sec
2015-06-23 01:49:14,760 Stage-4 map = 15%,  reduce = 0%, Cumulative CPU 263.95 sec
2015-06-23 01:49:26,177 Stage-4 map = 16%,  reduce = 0%, Cumulative CPU 341.29 sec
2015-06-23 01:49:31,365 Stage-4 map = 15%,  reduce = 0%, Cumulative CPU 334.86 sec
2015-06-23 01:49:39,713 Stage-4 map = 23%,  reduce = 0%, Cumulative CPU 300.53 sec
2015-06-23 01:49:40,758 Stage-4 map = 15%,  reduce = 0%, Cumulative CPU 300.53 sec
2015-06-23 01:49:43,868 Stage-4 map = 100%,  reduce = 100%, Cumulative CPU 263.95 sec
MapReduce Total cumulative CPU time: 4 minutes 23 seconds 950 msec
Ended Job = job_1434953415026_0374 with errors
Error during job, obtaining debugging information...
Examining task ID: task_1434953415026_0374_m_000025 (and more) from job job_1434953415026_0374
Examining task ID: task_1434953415026_0374_m_000004 (and more) from job job_1434953415026_0374
Examining task ID: task_1434953415026_0374_m_000019 (and more) from job job_1434953415026_0374
Examining task ID: task_1434953415026_0374_m_000003 (and more) from job job_1434953415026_0374
Examining task ID: task_1434953415026_0374_m_000022 (and more) from job job_1434953415026_0374
Examining task ID: task_1434953415026_0374_m_000002 (and more) from job job_1434953415026_0374
Examining task ID: task_1434953415026_0374_m_000005 (and more) from job job_1434953415026_0374

Task with the most failures(4): 
-----
Task ID:
  task_1434953415026_0374_m_000000

URL:
  http://pfaquaap1u:8088/taskdetails.jsp?jobid=job_1434953415026_0374&tipid=task_1434953415026_0374_m_000000
-----
Diagnostic Messages for this Task:
FSError: java.io.IOException: No space left on device

但是，运行 df 显示我在本地系统上有超过80 gb的可用空间。 df -i 同时也表明没有任何inode被过度使用。如果使用较小的数据输入，脚本运行良好。有人能告诉我在这里该做什么吗？提前谢谢。