Josh Morris
2014-06-27 18:19:10 UTC
I get an error (see below) while trying to insert data into a hive table
that is connected to a Mongodb table. I'm able to create, drop and query
the table just fine e.g. if I insert data into the Mongo collection first
and perform a select from the Hive cli I see the Mongo data.
FAILED: Execution Error, return code 2 from
org.apache.hadoop.hive.ql.exec.mr.MapRedTask
I'm using HDP 2.1 set up across 3 ec2 instances, Mongodb 2.6 on another ec2
instance.
So far I haven't been able to find more details about the error. Any help
would be appreciated.
*Details*
hive> CREATE TABLE individuals
OK
Time taken: 0.294 seconds
hive> select * from individuals;
OK
Time taken: 0.351 seconds
hive> insert into table individuals select 1, 'name column', 5 from
some_table limit 1;
Query ID = hdfs_20140627134040_5a3db212-e6e1-42cf-a6cc-0a0078ef3bb3
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks determined at compile time: 1
In order to change the average load for a reducer (in bytes):
set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
set mapreduce.job.reduces=<number>
Starting Job = job_1403731258511_0038, Tracking URL =
http://192.168.2.40:8088/proxy/application_1403731258511_0038/
Kill Command = /usr/lib/hadoop/bin/hadoop job -kill job_1403731258511_0038
Hadoop job information for Stage-0: number of mappers: 0; number of
reducers: 0
2014-06-27 13:40:16,335 Stage-0 map = 0%, reduce = 0%
Ended Job = job_1403731258511_0038 with errors
*Error during job, obtaining debugging information...*
*FAILED: Execution Error, return code 2 from
org.apache.hadoop.hive.ql.exec.mr.MapRedTask*
MapReduce Jobs Launched:
Job 0: HDFS Read: 0 HDFS Write: 0 FAIL
Total MapReduce CPU Time Spent: 0 msec
hive>
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that is connected to a Mongodb table. I'm able to create, drop and query
the table just fine e.g. if I insert data into the Mongo collection first
and perform a select from the Hive cli I see the Mongo data.
FAILED: Execution Error, return code 2 from
org.apache.hadoop.hive.ql.exec.mr.MapRedTask
I'm using HDP 2.1 set up across 3 ec2 instances, Mongodb 2.6 on another ec2
instance.
So far I haven't been able to find more details about the error. Any help
would be appreciated.
*Details*
hive> CREATE TABLE individuals
(
id INT,
name STRING,
age INT
)
STORED BY 'com.mongodb.hadoop.hive.MongoStorageHandler'
TBLPROPERTIES('mongo.uri'='mongodb://testuser:test-***@public.gmane.org:27017/test.persons2');id INT,
name STRING,
age INT
)
STORED BY 'com.mongodb.hadoop.hive.MongoStorageHandler'
OK
Time taken: 0.294 seconds
hive> select * from individuals;
OK
Time taken: 0.351 seconds
hive> insert into table individuals select 1, 'name column', 5 from
some_table limit 1;
Query ID = hdfs_20140627134040_5a3db212-e6e1-42cf-a6cc-0a0078ef3bb3
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks determined at compile time: 1
In order to change the average load for a reducer (in bytes):
set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
set mapreduce.job.reduces=<number>
Starting Job = job_1403731258511_0038, Tracking URL =
http://192.168.2.40:8088/proxy/application_1403731258511_0038/
Kill Command = /usr/lib/hadoop/bin/hadoop job -kill job_1403731258511_0038
Hadoop job information for Stage-0: number of mappers: 0; number of
reducers: 0
2014-06-27 13:40:16,335 Stage-0 map = 0%, reduce = 0%
Ended Job = job_1403731258511_0038 with errors
*Error during job, obtaining debugging information...*
*FAILED: Execution Error, return code 2 from
org.apache.hadoop.hive.ql.exec.mr.MapRedTask*
MapReduce Jobs Launched:
Job 0: HDFS Read: 0 HDFS Write: 0 FAIL
Total MapReduce CPU Time Spent: 0 msec
hive>
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To view this discussion on the web visit https://groups.google.com/d/msgid/mongodb-user/5e188766-e0a1-4cd1-a776-428f7ec3d20c%40googlegroups.com.
For more options, visit https://groups.google.com/d/optout.