hadoop流式传输作业在python中失败

时间:2011-04-22 19:53:04

标签: python hadoop

我试图在hadoop中实现一个算法。 我试图在hadoop中执行部分代码但是流式传输作业失败

$ /home/hadoop/hadoop/bin/hadoop jar contrib/streaming/hadoop-*-streaming.jar -file /home/hadoop/hadoop/PR/mapper.py -mapper mapper.py -file /home/hadoop/hadoop/PR/reducer.py -reducer reducer.py -input pagerank/* -output PRoutput6

packageJobJar: [/home/hadoop/hadoop/PR/mapper.py, /home/hadoop/hadoop/PR/reducer.py, /home/hadoop/hadoop/tmp/dir/hadoop-hadoop/hadoop-unjar7101759175212283428/] [] /tmp/streamjob6286075675343269479.jar tmpDir=null

11/04/23 01:03:24 INFO mapred.FileInputFormat: Total input paths to process : 1

11/04/23 01:03:24 INFO streaming.StreamJob: getLocalDirs(): [/home/hadoop/hadoop/tmp/dir/hadoop-hadoop/mapred/local]

11/04/23 01:03:24 INFO streaming.StreamJob: Running job: job_201104222325_0021

11/04/23 01:03:24 INFO streaming.StreamJob: To kill this job, run:

11/04/23 01:03:24 INFO streaming.StreamJob: /home/hadoop/hadoop/bin/../bin/hadoop job  -Dmapred.job.tracker=localhost:54311 -kill job_201104222325_0021

11/04/23 01:03:24 INFO streaming.StreamJob: Tracking URL: http://localhost:50030/jobdetails.jsp?jobid=job_201104222325_0021

11/04/23 01:03:25 INFO streaming.StreamJob:  map 0%  reduce 0%

11/04/23 01:03:31 INFO streaming.StreamJob:  map 50%  reduce 0%

11/04/23 01:03:41 INFO streaming.StreamJob:  map 50%  reduce 17%

11/04/23 01:03:56 INFO streaming.StreamJob:  map 100%  reduce 100%

11/04/23 01:03:56 INFO streaming.StreamJob: To kill this job, run:

11/04/23 01:03:56 INFO streaming.StreamJob: /home/hadoop/hadoop/bin/../bin/hadoop job  -Dmapred.job.tracker=localhost:54311 -kill job_201104222325_0021

11/04/23 01:03:56 INFO streaming.StreamJob: Tracking URL: http://localhost:50030/jobdetails.jsp?jobid=job_201104222325_0021

11/04/23 01:03:56 ERROR streaming.StreamJob: Job not Successful!

11/04/23 01:03:56 INFO streaming.StreamJob: killJob...

Streaming Job Failed!

mapper.py

#!/usr/bin/env python
import sys
import itertools

def ipsum(input_key,input_value_list):
   return sum(input_value_list)

n= 20 # works up to about 1000000 pages
i = {}
for j in xrange(n): i[j] = [1.0/n,0,[]]
j=0
u=0
for line in sys.stdin:
  if j<n:
    i[j][1]=int(line)
  j=j+1

  if j > n: 
    if line != "-1\n":
      i[u][2] = line.split(',')
    else: 
      i[u][2]=[]
    u=u+1
for j in xrange(n):
  if i[j][1] != 0:
    i[j][2] = map(int,i[j][2])    

intermediate=[]
for (input_key,input_value) in i.items():
  if input_value[1] == 0: intermediate.extend([(1,input_value[0])])
  else: intermediate.extend([])
grp = {}
for key, group in itertools.groupby(sorted(intermediate),lambda x: x[0]):
  grp[key] = list([y for x, y in group])
iplist = [ipsum(intermediate_key,grp[intermediate_key]) for intermediate_key in grp]
inter=[]
for (input_key,input_value) in i.items():
  if input_value[1] == 0: inter.extend([(input_key,0.0)]+[(outlink,input_value[0]/input_value[1]) for outlink in input_value[2]])
  else: inter.extend([])

for value in inter:
  value1 = value[0]
  value2 = value[1]
  print '%s %s' % (value1,value2)

reducer.py

#!/usr/bin/env python
import sys
import itertools
for line in sys.stdin:
  input_key, input_value=line.split(' ',1)
  input_key = input_key.strip()
  input_value = input_value.strip()
  input_key = int(input_key)
  input_value = float(input_value)
  print str(input_key)+' '+str(input_value)

我不知道错误是在我的代码还是hadoop配置中...因为我能够使用执行代码, $ cat /home/hadoop/hadoop/PR/pagerank/input.txt | python /home/hadoop/hadoop/PR/mapper.py |排序| python /home/hadoop/hadoop/PR/reducer.py

非常感谢任何帮助, 谢谢。

2 个答案:

答案 0 :(得分:0)

我的猜测是你的数据可能是关键。从字符串或类似问题中转换浮点数可能会使您的实际数据中出现一个不会出现在本地测试数据中的麻烦。也许您可以通过异常处理或断言进行处理。

答案 1 :(得分:0)

从输出中查看作业信息页面网址。在你的情况下,     本地主机:50030 / jobdetails.jsp作业ID = job_201104222325_0021

点击“失败的映射器”列中的数字和“最后8KB”(或其他)日志链接,您将看到您正在击中的(最有可能的)python异常。

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