Hive error: java.lang.Throwable: Child Error - hadoop

Question

I am using CDH 5.9, while executing following hive query it is throwing error. Any idea about the issue?
For normal select query its working but for complex query it results failure.
hive> select * from table where dt='22-01-2017' and field like '%xyz%' limit 10;
Query ID = hdfs_20170123200303_44a9c423-4bb3-4f80-ade4-b1312971eb63
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_201701131637_0067, Tracking URL = http://cdhum03.temp-dsc-updates.bms.bz:50030/jobdetails.jsp?jobid=job_201701131637_0067
Kill Command = /usr/lib/hadoop/bin/hadoop job -kill job_201701131637_0067
Hadoop job information for Stage-1: number of mappers: 6; number of reducers: 0
2017-01-23 20:05:46,563 Stage-1 map = 100%, reduce = 100%
Ended Job = job_201701131637_0067 with errors
Error during job, obtaining debugging information...
Job Tracking URL: http://cdhum03.temp-dsc-updates.bms.bz:50030/jobdetails.jsp?jobid=job_201701131637_0067
Examining task ID: task_201701131637_0067_m_000007 (and more) from job job_201701131637_0067
Examining task ID: task_201701131637_0067_r_000000 (and more) from job job_201701131637_0067
Task with the most failures(4):
-----
Task ID:
task_201701131637_0067_m_000006
URL:
http://cdhum03.temp-dsc-updates.bms.bz:50030/taskdetails.jsp?jobid=job_201701131637_0067&tipid=task_201701131637_0067_m_000006
-----
Diagnostic Messages for this Task:
java.lang.Throwable: Child Error
at org.apache.hadoop.mapred.TaskRunner.run(TaskRunner.java:250)
Caused by: java.io.IOException: Task process exit with nonzero status of 126.
at org.apache.hadoop.mapred.TaskRunner.run(TaskRunner.java:237)
FAILED: Execution Error, return code 2 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask
MapReduce Jobs Launched:
Stage-Stage-1: Map: 6 HDFS Read: 0 HDFS Write: 0 FAIL
Total MapReduce CPU Time Spent: 0 msec
Thanks.

Answer 1

Please check your data size as your job needs more space for logs but the jvm are less please scale your cluster or use specific query as you are using -
select * from table where dt='22-01-2017' and field like '%xyz%' limit 10
, as '%xyz%' will check whole data better to use specific requirement.
Else drop your table and create a new partitioned table with date as a partition column.