Github user shivaram commented on the pull request:
https://github.com/apache/spark/pull/7280#issuecomment-120990179
Ok I see the problem -- I guess there are two solutions.
1. In `createDataFrame` we throw an error if somebody has `float` in their
schema and ask them to use `double` instead.
2. We auto-convert `double` to `float` based on the schema on the Scala
side.
I don't mind either of them (the first might be simpler / cheaper to
implement) as I don't think using `float` from a local data frame is a major
use case.
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