Hive中使用Python实现Transform时遇到Broken pipe错误排查

Hive中有一表,列分隔符为冒号(:),有一列utime是Timestamp格式,需要转成Weekday存到新表。

利用Python写一个Pipeline的Transform,weekday.py的代码也很简单:
import sys
import datetime
for line in sys.stdin:
 line=line.strip()
 uid,mid,rating,utime=line.split(':')
 weekday=datetime.datetime.fromtimestamp(float(utime)).isoweekday()
 print '\t'.join([uid,mid,rating,str(weekday)])
 
HQL的查询也很简单:
select 
transform(uid,mid,rating,utime) 
using 'python weekday.py' as (uid,mid,rating,weekday) 
from rating
 
Stage-1结束后就报错!
 
排查过程:
1. Hive给出的日志,没有什么意义。Hive日志:
 INFO exec.Task: 2015-07-07 16:34:57,938 Stage-1 map = 0%,  reduce = 0%
INFO exec.Task: 2015-07-07 16:35:30,262 Stage-1 map = 100%,  reduce = 0%
ERROR exec.Task: Ended Job = job_1431587697935_0210 with errors
ERROR operation.Operation: Error running hive query:
org.apache.hive.service.cli.HiveSQLException: Error while processing statement: FAILED: Execution Error, return code 20001 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask. An error occurred while reading or writing to your custom script. It may have crashed with an error. 
 at org.apache.hive.service.cli.operation.Operation.toSQLException(Operation.java:315)
 at org.apache.hive.service.cli.operation.SQLOperation.runQuery(SQLOperation.java:156)
 at org.apache.hive.service.cli.operation.SQLOperation.access$100(SQLOperation.java:71)
 at org.apache.hive.service.cli.operation.SQLOperation$1$1.run(SQLOperation.java:206)
 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:1628)
 at org.apache.hive.service.cli.operation.SQLOperation$1.run(SQLOperation.java:218)
 at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
 at java.util.concurrent.FutureTask.run(FutureTask.java:262)
 at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
 at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
 at java.lang.Thread.run(Thread.java:745)
 
 2. 不死心呀!开启Hive日志的Debug,再看看日志。
   因为我一直使用的是Beeline连接Hive,得到的日志跟1.一样,没有收获。后来我想想,要不用Hive CLI看一下,会不会有收获。终于得到点有意义的日志了:
Task with the most failures(4): 
-----
Task ID:
  task_1431587697935_0210_m_000000
-----
Diagnostic Messages for this Task:
Error: java.lang.RuntimeException: org.apache.hadoop.hive.ql.metadata.HiveException: Hive Runtime Error while processing row {"uid":11,"mid":2791,"rating":4,"utime":"978903186"}
at org.apache.hadoop.hive.ql.exec.mr.ExecMapper.map(ExecMapper.java:172)
at org.apache.hadoop.mapred.MapRunner.run(MapRunner.java:54)
at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:450)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:343)
at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:163)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1628)
at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:158)
Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: Hive Runtime Error while processing row {"uid":11,"mid":2791,"rating":4,"utime":"978903186"}
at org.apache.hadoop.hive.ql.exec.MapOperator.process(MapOperator.java:518)
at org.apache.hadoop.hive.ql.exec.mr.ExecMapper.map(ExecMapper.java:163)
... 8 more
Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: [Error 20001]: An error occurred while reading or writing to your custom script. It may have crashed with an error.
at org.apache.hadoop.hive.ql.exec.ScriptOperator.process(ScriptOperator.java:456)
at org.apache.hadoop.hive.ql.exec.Operator.forward(Operator.java:837)
at org.apache.hadoop.hive.ql.exec.SelectOperator.process(SelectOperator.java:88)
at org.apache.hadoop.hive.ql.exec.Operator.forward(Operator.java:837)
at org.apache.hadoop.hive.ql.exec.TableScanOperator.process(TableScanOperator.java:97)
at org.apache.hadoop.hive.ql.exec.MapOperator$MapOpCtx.forward(MapOperator.java:162)
at org.apache.hadoop.hive.ql.exec.MapOperator.process(MapOperator.java:508)

Caused by: java.io.IOException: Broken pipe
at java.io.FileOutputStream.writeBytes(Native Method)
at java.io.FileOutputStream.write(FileOutputStream.java:345)
at java.io.BufferedOutputStream.write(BufferedOutputStream.java:122)
at java.io.BufferedOutputStream.flushBuffer(BufferedOutputStream.java:82)
at java.io.BufferedOutputStream.write(BufferedOutputStream.java:126)
at java.io.DataOutputStream.write(DataOutputStream.java:107)
at org.apache.hadoop.hive.ql.exec.TextRecordWriter.write(TextRecordWriter.java:53)
at org.apache.hadoop.hive.ql.exec.ScriptOperator.process(ScriptOperator.java:425)

3. 根据上步提示的那行可疑的数据,我怀疑有Bad Data,处理时出错。我单独将报错的行放到另一个表中去处理,又完全没有问题。好吧,继续。
 
4. 断续之前我需要搞清楚: java.io.IOException: Broken pipe是什么?
    写入端出现的时候,另一端却休息或退出了,因此造成没有及时取走管道中的数据,从而系统异常退出。在这里就是:当Streaming正在获取input数据,好给weekday.py处理的过程中,weekday.py异常终止了。等Streaming准备好数据回来后,却找不到weekday.py来接收数据,于是Broken pipe了。
 
5. 搞明白Broken pipe并给前面的错误信息,断定问题应该出在weekday.py上。接下来,既然是MapReduce出错,那就需要去看Yarn的Stderr.
     通过ResouceManager查看对应Application的Logs中的stderr,发现:
     Traceback (most recent call last):
     File "weekday_mapper.py", line 5, in <module>
    uid,mid,rating,utime=line.split(':')
    ValueError: need more than 1 value to unpack
 
6. 从Python的错误来看,推测有数据行的分隔符(:)有异常,导致split之后不能返回4个值(uid,mid,rating,utime)。用各种方法检查数据格式,一切正常。只好,处理脚本加上异常处理。
加上异常处理之后不报错了,但是Select输出0行数据
import sys
import datetime
for line in sys.stdin:
 try:
  line=line.strip()
  uid,mid,rating,utime=line.split(':')
  weekday=datetime.datetime.fromtimestamp(float(utime)).isoweekday()
  print '\t'.join([uid,mid,rating,str(weekday)])
 except Exception, ex:
  pass
 
7. 问题锁定到:脚本处理数据有问题。尝试直接从HDFS上直接抓取表的数据文件,再用脚本处理,是正常的。
hdfs dfs -cat /user/hive/warehouse/test.db/t/000000_0|python /tmp/weekday_mapper.py
最后,怀疑transform的输出格式是不是与定义表的格式不一样,查阅官方说明:

By default, columns will be transformed to STRING and delimited by TAB before feeding to the user script。

于是,将脚本中的 uid,mid,rating,utime=line.split(':')改成 uid,mid,rating,utime=line.split('\t')。再试一次,成功!

 

总结

  1. 基础知识很重要,要在自己内心成体系,才能够用信手拈来。路漫漫兮!

  2. 有时凭借经验的“猜”,会很有帮助,有时却会“聪明反被聪明误"。所以要重视日志,并以之为操作重现的依据。

posted @ 2015-07-13 17:30  Joe.TJ  阅读(12320)  评论(1编辑  收藏  举报