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?
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