[ https://issues.apache.org/jira/browse/SPARK-19983?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Rajkumar updated SPARK-19983: ----------------------------- Description: Hi, I am creating a DataFrame and registering that DataFrame as temp table using df.createOrReplaceTempView('mytable'). After that I try to write the content from 'mytable' into Hive table(It has partition) using the following query insert overwrite table myhivedb.myhivetable partition(testdate) // ( 1) : Note here : I have a partition named 'testdate' select Field1, Field2, ... TestDate //(2) : Note here : I have a field named 'TestDate' ; Both (1) & (2) have the same name from mytable when I execute this query, I am getting the following error Exception in thread "main" org.apache.hadoop.hive.ql.metadata.Table$ValidationFailureSemanticException: Partition spec {testdate=, TestDate=2013-01-01} Looks like I am getting this error because of the same field names ; ie testdate(the partition in Hive) & TestDate (The field in temp table 'mytable') Whereas if my partition name testdate is different from the fieldname(ie TestDate), the query executes successuflly. Example... insert overwrite table myhivedb.myhivetable partition(my_partition) //Note here the partition name is not 'testdate' select Field1, Field2, ... TestDate from mytable was: Hi, I am creating a DataFrame and registering that DataFrame as temp table using df.createOrReplaceTempView('mytable'). After that I try to write the content from 'mytable' into Hive table(It has partition) using the following query insert overwrite table myhivedb.myhivetable partition(testdate) // ( 1) : Note here : I have a partition named 'testdate' select Field1, Field2, ... TestDate //(2) : Note here : I have a field named 'TestDate' ; Both (1) & (2) have the same name from mytable when I execute this query, I am getting the following error Exception in thread "main" org.apache.hadoop.hive.ql.metadata.Table$ValidationFailureSemanticException: Partition spec {testdate=, TestDate=2013-01-01} Looks like I am getting this error because of the same field names ; ie testdate(the partition in Hive) & TestDate (The field in temp table 'mytable') Whereas if my fieldname 'TestDate' is different, the query executes successuflly. Example... insert overwrite table myhivedb.myhivetable partition(testdate) select Field1, Field2, ... myDate //Note here : The field name is 'myDate' & not 'TestDate' from mytable > Getting ValidationFailureSemanticException on 'INSERT OVEWRITE' > --------------------------------------------------------------- > > Key: SPARK-19983 > URL: https://issues.apache.org/jira/browse/SPARK-19983 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 2.1.0 > Reporter: Rajkumar > Priority: Blocker > Labels: sparkSQL > > Hi, I am creating a DataFrame and registering that DataFrame as temp table > using df.createOrReplaceTempView('mytable'). After that I try to write the > content from 'mytable' into Hive table(It has partition) using the following > query > insert overwrite table > myhivedb.myhivetable > partition(testdate) // ( 1) : Note here : I have a partition named 'testdate' > select > Field1, > Field2, > ... > TestDate //(2) : Note here : I have a field named 'TestDate' ; Both (1) & > (2) have the same name > from > mytable > when I execute this query, I am getting the following error > Exception in thread "main" > org.apache.hadoop.hive.ql.metadata.Table$ValidationFailureSemanticException: > Partition spec {testdate=, TestDate=2013-01-01} > Looks like I am getting this error because of the same field names ; ie > testdate(the partition in Hive) & TestDate (The field in temp table 'mytable') > Whereas if my partition name testdate is different from the fieldname(ie > TestDate), the query executes successuflly. Example... > insert overwrite table > myhivedb.myhivetable > partition(my_partition) //Note here the partition name is not 'testdate' > select > Field1, > Field2, > ... > TestDate > from > mytable -- This message was sent by Atlassian JIRA (v6.3.15#6346) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org