Github user frreiss commented on the issue:
https://github.com/apache/spark/pull/17640
Overall, this looks like a sensible approach to a messy problem.
You might want to think about adding some overflow handling to the SQL-->R
translation. That is, if a Dataframe contains a `bigint` value that cannot be
expressed as a `Double`, it would be safer to convert that value to NaN instead
of stripping the lower-order bits off the `bigint`. The `bigint` column in the
source Dataframe could hold a unique identifier or a hash value.
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