Hi The is not with spark in this case, it is with Oracle. If you do not know which columns to apply date-related conversion rule, then you have a problem.
You should try either a) Define some config file where you can define table name, date column name and date-format @ source so that you can apply appropriate conversion dynamically b) Write data into Oracle DB with String data type but have a view which will translate the date c) Define Hive tables with date data type so that you can apply appropriate conversion On Mon, Mar 19, 2018 at 1:36 PM, Deepak Sharma <deepakmc...@gmail.com> wrote: > The other approach would to write to temp table and then merge the data. > But this may be expensive solution. > > Thanks > Deepak > > On Mon, Mar 19, 2018, 08:04 Gurusamy Thirupathy <thirug...@gmail.com> > wrote: > >> Hi, >> >> I am trying to read data from Hive as DataFrame, then trying to write the >> DF into the Oracle data base. In this case, the date field/column in hive >> is with Type Varchar(20) >> but the corresponding column type in Oracle is Date. While reading from >> hive , the hive table names are dynamically decided(read from another >> table) based on some job condition(ex. Job1). There are multiple tables >> like this, so column and the table names are decided only run time. So I >> can't do type conversion explicitly when read from Hive. >> >> So is there any utility/api available in Spark to achieve this conversion >> issue? >> >> >> Thanks, >> Guru >> > -- Best Regards, Ayan Guha
