Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/6782#discussion_r33331507
--- 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 --
Good point, we have many functions which take two or more parameters, all
the parameters could Column or Literal, we usually take only a few combination
of them as DataFrame function. It's hard to have a rule to follow, but we
usually take the first one as Column, and others as Literal.
There are a few cases that we have all the combinations (for example,
atan2, pow), that's bad, we should revisit them, cc @rxin @brkyvz
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