Created 07-11-2016 12:58 PM
Hello, I try to create a job with a command oozie Sqoop got this error: Intercepting System.exit(1) Failing Oozie Launcher, Main class [org.apache.oozie.action.hadoop.SqoopMain], exit code [1] this is my xml file : <workflow-app name="exemple_hive" xmlns="uri:oozie:workflow:0.5"> <global> <configuration> <property> <name>mapreduce.job.queuename</name> <value>DES</value> </property> </configuration> </global> <start to="sqoop-9fb3"/> <kill name="Kill"> <message>L'action a échoué, message d'erreur[${wf:errorMessage(wf:lastErrorNode())}]</message> </kill> <action name="sqoop-9fb3"> <sqoop xmlns="uri:oozie:sqoop-action:0.2"> <job-tracker>${jobTracker}</job-tracker> <name-node>${nameNode}</name-node> <command>sqoop import -Dmapred.job.queue.name=DES --connect "jdbc:jtds:sqlserver://xxxx.xxxx.xxxx.xxxx:xxxx;databaseName=xxxxxxxx;user=xxxxxxxx;password=xxxxxxxx;instance=MSPAREBTP02" --driver net.sourceforge.jtds.jdbc.Driver --username hdp-import --table qvol_ccy --hive-import --hive-table test.qvol_ccy -m 1</command> <file>/dev/datalake/app/des/dev/lib/jtds-1.3.1.jar#jtds-1.3.1.jar</file> <file>/dev/datalake/app/des/dev/script/hive-site.xml#hive-site.xml</file> </sqoop> <ok to="End"/> <error to="Kill"/> </action> <end name="End"/> </workflow-app>
Created 07-11-2016 03:45 PM
You need to look into the logs. Most likely yarn logs of the Map Task of your Oozie launcher. This contains the sqoop command execution and any errors you would normally see on the command line. You can get them from resourcemanager ( click on your oozie launcher job and go through to the map task or use yarn application -logs.
You can find any issues in the actual data transfer in the kicked off Mapreduce job which is a separate job
Created 07-11-2016 03:45 PM
You need to look into the logs. Most likely yarn logs of the Map Task of your Oozie launcher. This contains the sqoop command execution and any errors you would normally see on the command line. You can get them from resourcemanager ( click on your oozie launcher job and go through to the map task or use yarn application -logs.
You can find any issues in the actual data transfer in the kicked off Mapreduce job which is a separate job