coderfender commented on PR #20555: URL: https://github.com/apache/datafusion/pull/20555#issuecomment-4049531882
@paleolimbot , agreed. This is just an initial framework to start supporting spark compatible cast in DF . In an utopian sense, we would have a single cast(expr, datatype) which would wire the right cast op based on the semantic profile selected by user . Something like this : ```` SET df.semantics.profile=spark select cast(1 as timestamp) ; Result : 1 SET df.semantics.profile=default select cast(1 as timestamp) ; Result : 0.0000001 ``` We pretty much have all the cast support (barring some incompatible support bound by JVM vs Rust implementation) that I plan to port upstream to DF . Once there are enough cast ops (and other spark compatible expressions) supported, I can start work on semantics support functionality to wire in the right functions and I think that would be a good feature for the users to leverage DF against spark loads directly -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
