Hard to tell. Can you give more insights on what you try to achieve and what the data is about? For example, depending on your use case sqoop can make sense or not.
> On 28 Jan 2017, at 02:14, 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 --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org
