Github user sun-rui commented on the pull request:
https://github.com/apache/spark/pull/8984#issuecomment-152465285
Per the Scala API doc on cast() of Column, the supported types are: string,
boolean, byte, short, int, long, float, double, decimal, date, timestamp. That
is, complext types are not supported as a target type. So for coltypes<-(),
regardless of the input (NA or not), it should not cast the type of a column of
a complex type. If the corresponding input is NA, coltype<-() can silently skip
the column, while if not NA, then prompts a warning.
What I am concerned about is that coltypes<-() actually returns a new
DataFrame instead in-place changing of the schema of the DataFrame (which is
not supported by Spark Core). Is this a desired behavior?
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