Apache Hive在使用Python UDF时收到错误

时间:2015-08-16 05:33:43

标签: python hadoop hive apache-hive

我在Apache配置单元中使用Python用户定义的函数将字符从小写字符更改为大写字母。关闭运算符时,我收到错误" Hive运行时错误"。

以下是我尝试的查询:

describe table1;     
OK
item    string  
count   int 
city    string  

select * from table1;
aaa 1   tokyo
aaa 2   london
bbb 3   washington
ccc 4   moscow
ddd 5   bejing

从上表中,项目和城市字段应从小写更改为大写,计数应增加10。

使用的Python脚本:

cat caseconvert.py
import sys
import string

for line in sys.stdin:
    line = line.strip()
    item,count,city=line.split('\t')

    ITEM1=item.upper()
    COUNT1=count+10
    CITY1=city.upper()
    print '\t'.join([ITEM1,str(COUNT1),FRUIT1])

将table1数据插入table2

create table table2(ITEM1 string, COUNT1 int, CITY1 string) row format delimited fields terminated by ',';

add FILE caseconvert.py 

insert overwrite table table2 select TRANSFORM(item,count,city) using 'python caseconvert.py' as (ITEM1,COUNT1,CITY1) from table1;

如果我执行,我收到以下错误。我无法追查这个问题。我可以知道它出错吗?

Total MapReduce jobs = 3
Launching Job 1 out of 3
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_201508151858_0014, Tracking URL = http://0.0.0.0:50030/jobdetails.jsp?jobid=job_201508151858_0014
Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_201508151858_0014
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0
2015-08-15 22:24:06,212 Stage-1 map = 0%,  reduce = 0%
2015-08-15 22:25:01,559 Stage-1 map = 100%,  reduce = 100%
Ended Job = job_201508151858_0014 with errors
Error during job, obtaining debugging information...
Job Tracking URL: http://0.0.0.0:50030/jobdetails.jsp?jobid=job_201508151858_0014
Examining task ID: task_201508151858_0014_m_000002 (and more) from job job_201508151858_0014

Task with the most failures(4): 
-----
Task ID:
  task_201508151858_0014_m_000000

URL:
  http://localhost.localdomain:50030/taskdetails.jsp?jobid=job_201508151858_0014&tipid=task_201508151858_0014_m_000000
-----
Diagnostic Messages for this Task:
java.lang.RuntimeException: Hive Runtime Error while closing operators
    at org.apache.hadoop.hive.ql.exec.ExecMapper.close(ExecMapper.java:224)
    at org.apache.hadoop.mapred.MapRunner.run(MapRunner.java:57)
    at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:417)
    at org.apache.hadoop.mapred.MapTask.run(MapTask.java:332)
    at org.apache.hadoop.mapred.Child$4.run(Child.java:268)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:396)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1438)
    at org.apache.hadoop.mapred.Child.main(Child.java:262)
Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: [Error 20003]: An error occurred when trying to close the Operator running your custom script.
    at org.apache.hadoop.hive.ql.exec.ScriptOperator.close(ScriptOperator.java:488)
    at org.apache.hadoop.hive.ql.exec.Operator.close(Operator.java:570)
    at org.apache.hadoop.hive.ql.exec.Operator.close(Operator.java:5

FAILED: Execution Error, return code 20003 from org.apache.hadoop.hive.ql.exec.MapRedTask. An error occurred when trying to close the Operator running your custom script.
MapReduce Jobs Launched: 
Job 0: Map: 1   HDFS Read: 0 HDFS Write: 0 FAIL
Total MapReduce CPU Time Spent: 0 msec

1 个答案:

答案 0 :(得分:0)

在Python脚本的最后一行,您将输出打印到STDOUT,在没有定义它的情况下调用FRUIT1。这应该是CITY1。您还导入了字符串但未使用它。我写的脚本有点不同:

import sys
import string

while True:
    line = sys.stdin.readline()
    if not line:
        break

    line = string.strip(line, '\n ')
    item,count,city=string.split(line, '\t')

    ITEM1=item.upper()
    COUNT1=count+10
    CITY1=city.upper()
    print '\t'.join([ITEM1,str(COUNT1),CITY1])

然后,我使用CREATE TABLE AS SELECT查询(假设TABLE1和你的python脚本都存在于HDFS中):

create table TABLE2
as select transform(item, count, city)
using 'hdfs:///user/username/caseconvert.py' 
as (item1 string, count1 string, city1 string)
FROM TABLE1;

这对我有用。但是,使用Hive内置函数可以更轻松地进行所需的转换:

upper(字符串A)>>>返回将A的所有字符转换为大写字符所产生的字符串。例如,上层(' fOoBaR')会导致' FOOBAR'。

当然对于城市来说,你可以做到:(城市+10)AS city1。

因此,可以按如下方式创建TABLE2:

CREATE TABLE2
AS SELECT
UPPER(ITEM) AS ITEM1,
COUNT + 10 AS COUNT1,
UPPER CITY AS CITY1
FROM TABLE1;

比编写自定义UDF麻烦少得多。