stevomitric commented on code in PR #56612:
URL: https://github.com/apache/spark/pull/56612#discussion_r3448450890
##########
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/ExpressionTypeCheckingSuite.scala:
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@@ -408,6 +408,20 @@ class ExpressionTypeCheckingSuite extends SparkFunSuite
with SQLHelper with Quer
}
}
+ test("SPARK-57103: max_by/min_by accept a nanosecond ordering and preserve
the value type") {
+ // MaxBy/MinBy gate only on the ordering expression's orderability; a
nanosecond ordering is an
+ // orderable AtomicType (SPARK-57103). The value expression is
unrestricted, and the result type
+ // is the value's type, so a nanosecond value is returned with its
precision preserved.
+ Seq(TimestampNTZNanosType(9), TimestampLTZNanosType(7)).foreach { dt =>
+ val v = AttributeReference("v", dt)()
+ val ord = AttributeReference("ord", dt)()
+ assert(MaxBy(v, ord).checkInputDataTypes() ==
TypeCheckResult.TypeCheckSuccess)
+ assert(MinBy(v, ord).checkInputDataTypes() ==
TypeCheckResult.TypeCheckSuccess)
+ assert(MaxBy(v, ord).dataType == dt)
+ assert(MinBy(v, ord).dataType == dt)
+ }
Review Comment:
Done - all three now use the functions.max_by/min_by(Column, Column) API
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