Github user justinuang commented on the pull request:
https://github.com/apache/spark/pull/8662#issuecomment-141232211
I'm not sure there is a solution that satisfies all the requirements. I can
say that this approach addresses 1,2,4 by design.
Would you guys support a 1.6.0 UDF implementation that uses thrift for the
RPC and serialization? In general, I think the custom-rolled socket,
serialization, and cleanup approach as pretty scary. They're already solved
problems, and then we can support multiple language bindings at the DataFrame
level, where I think it's a lot easier to implement. We could even support
broadcast variables by allowing language bindings to store bytes in the UDF
that will be passed back to them. I don't think we need to support accumulators
right?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
