On Sat, Jan 28, 2017 at 6:44 AM, Sirisha Cheruvu <siri8...@gmail.com> wrote:
> Hi Team, > > RIght now our existing flow is > > Oracle-->Sqoop --> Hive--> Hive Queries on Spark-sql (Hive > Context)-->Destination Hive table -->sqoop export to Oracle > > Half of the Hive UDFS required is developed in Java UDF.. > > SO Now I want to know if I run the native scala UDF's than runninng hive > java udfs in spark-sql will there be any performance difference > > > Can we skip the Sqoop Import and export part and > > Instead directly load data from oracle to spark and code Scala UDF's for > transformations and export output data back to oracle? > > RIght now the architecture we are using is > > oracle-->Sqoop (Import)-->Hive Tables--> Hive Queries --> Spark-SQL--> > Hive --> Oracle > what would be optimal architecture to process data from oracle using spark > ?? can i anyway better this process ? > > > > > Regards, > Sirisha >
