Github user sun-rui commented on the pull request:
https://github.com/apache/spark/pull/9099#issuecomment-148713960
@zero323, I have an alternative proposal. That is as simpler as:
data.frame(t(data))
It seems t() can handle factor types, so we don't need dropFactor. Could
you try this proposal, benchmark it and compare the result with that of your
version?
For the problem you observed regarding sdf, that is because previously
inferring schema of complex types was buggy. That was fixed by my PR for
SPARK-10049. The fix is currently on master, not in 1.5.x releases.
For the bug regarding sdf1, I will investigate it (maybe some problem in
handling nested array) and fix in another PR. You can go on with this PR.
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