MaxGekk commented on a change in pull request #28998:
URL: https://github.com/apache/spark/pull/28998#discussion_r451121973
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/datetimeExpressions.scala
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@@ -1176,41 +1176,15 @@ case class DateAddInterval(
copy(timeZoneId = Option(timeZoneId))
}
-/**
- * This is a common function for databases supporting TIMESTAMP WITHOUT
TIMEZONE. This function
- * takes a timestamp which is timezone-agnostic, and interprets it as a
timestamp in UTC, and
- * renders that timestamp as a timestamp in the given time zone.
- *
- * However, timestamp in Spark represents number of microseconds from the Unix
epoch, which is not
- * timezone-agnostic. So in Spark this function just shift the timestamp value
from UTC timezone to
- * the given timezone.
- *
- * This function may return confusing result if the input is a string with
timezone, e.g.
- * '2018-03-13T06:18:23+00:00'. The reason is that, Spark firstly cast the
string to timestamp
- * according to the timezone in the string, and finally display the result by
converting the
- * timestamp to string according to the session local timezone.
- */
-// scalastyle:off line.size.limit
-@ExpressionDescription(
- usage = "_FUNC_(timestamp, timezone) - Given a timestamp like '2017-07-14
02:40:00.0', interprets it as a time in UTC, and renders that time as a
timestamp in the given time zone. For example, 'GMT+1' would yield '2017-07-14
03:40:00.0'.",
- examples = """
- Examples:
- > SELECT _FUNC_('2016-08-31', 'Asia/Seoul');
- 2016-08-31 09:00:00
- """,
- group = "datetime_funcs",
- since = "1.5.0")
-// scalastyle:on line.size.limit
-case class FromUTCTimestamp(left: Expression, right: Expression)
- extends BinaryExpression with ImplicitCastInputTypes with NullIntolerant {
+trait UTCTimestamp extends BinaryExpression with ImplicitCastInputTypes with
NullIntolerant {
Review comment:
Sure, I added `sealed` and matching by both implementations.
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