realno commented on pull request #1881: URL: https://github.com/apache/arrow-datafusion/pull/1881#issuecomment-1057737445
> Yes, it is important and required for DF to support udf. But for those who use DF, it is not necessary to support the udf plugin to dynamically load udf. If I understand correctly, you meant, udf is need in DF, but the mechanism to register udf during runtime is only needed in Ballista, correct? If so then I fully agree. > I don’t know if my understanding is wrong. I always think that DF is just a computing library, which cannot be directly deployed in production. Currently DF does more than just a computing library, it has full support for SQL parsing, dataframe API and planners - it is a complete single node compute engine. Ballista still uses most of the fundamental implementation from DF. The current effort splitting it to separate creates is a step towards making it just a library, I am curious what the direction the community is thinking here @alamb . If this is where we are going I think we can think about merging the SQL, DataFrame, ExecutionContext and Planner logic between DF and Ballista. -- 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]
