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 :
>
> 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
>
>
>
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