01-18-2023 07:16 AM
I am aware, I can load anything into a DataFrame using JDBC, that works well from Oracle sources. Is there an equivalent in Spark SQL, so I can combine datasets as well?
Basically something like so - you get the idea...
select
lt.field1,
rt.field2
from localTable lt
join remoteTable@serverLink rt
on rt.id = lt.id
Thanks
01-18-2023 08:00 AM
dblink does not exist. What you can do is create two table statements with jdbc sources and then do a join of the two tables. It will be a little more to write, but you'll get the correct table in the end.
In python you can maybe do it easier with something like:
spark.read.jdbc(config1).join(spark.read.jdbc(config2), "key", "type")
01-18-2023 08:00 AM
dblink does not exist. What you can do is create two table statements with jdbc sources and then do a join of the two tables. It will be a little more to write, but you'll get the correct table in the end.
In python you can maybe do it easier with something like:
spark.read.jdbc(config1).join(spark.read.jdbc(config2), "key", "type")
01-18-2023 11:36 PM
Here are the methods you can leverage to establish Databricks Connect to Oracle Database seamlessly:
Check this link:
https://hevodata.com/learn/databricks-connect-to-oracle-database/#7
01-19-2023 12:35 AM
Thanks everyone for helping.
01-24-2023 01:46 AM
Hi @Roger Bieri (Customer), I appreciate your attempt to choose the best answer for us. I'm glad you got your query resolved. @Joseph Kambourakis and @Adrian Łobacz, Thank you for giving excellent answers 😀.
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