You can use the map datatype on the Hive table for the columns that are uncertain: https://cwiki.apache.org/confluence/display/Hive/LanguageManual+Types#LanguageManualTypes-ComplexTypes
However, maybe you can share more concrete details, because there could be also other solutions. > Am 07.08.2019 um 20:40 schrieb anbutech <anbutec...@outlook.com>: > > Hi All, > > I have a scenario in (Spark scala/Hive): > > Day 1: > > i have a file with 5 columns which needs to be processed and loaded into > hive tables. > day2: > > Next day the same feeds(file) has 8 columns(additional fields) which needs > to be processed and loaded into hive tables > > How do we approach this problem without changing the target table schema.Is > there any way we can achieve this. > > Thanks > Anbu > > > > -- > Sent from: http://apache-spark-user-list.1001560.n3.nabble.com/ > > --------------------------------------------------------------------- > To unsubscribe e-mail: user-unsubscr...@spark.apache.org >
