Github user brkyvz commented on a diff in the pull request:
https://github.com/apache/spark/pull/6782#discussion_r33526888
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/functions.scala ---
@@ -946,6 +947,38 @@ object functions {
def cosh(columnName: String): Column = cosh(Column(columnName))
/**
+ * Adds a number of days to startDate, given values for startDate and
days
+ *
+ * @group datetime_funcs
+ * @since 1.5.0
+ */
+ def date_add(startDate: Column, days: Column): Column =
DateAdd(startDate.expr, days.expr)
+
+ /**
+ * Adds a number of days to startDate, given column names for startDate
and days
+ *
+ * @group datetime_funcs
+ * @since 1.5.0
+ */
+ def date_add(startDate: String, days: String): Column =
date_add(Column(startDate), Column(days))
--- End diff --
@davies In those, you have to accept any combination, because they are math
functions. I may want to take the power of 2 with the values in my DataFrame
column. I also should be able to take the power of my Column by 2. If we can
have a case where `f(a, b) == f(b, a)`, we wouldn't need all combinations, but
those functions (pow, atan2) don't necessarily have `f(a, b) == f(b, a)`
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