zhengruifeng commented on code in PR #58385:
URL: https://github.com/apache/spark/pull/58385#discussion_r3892941920
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sql/api/src/main/scala/org/apache/spark/sql/functions.scala:
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@@ -16567,6 +17106,12 @@ object functions {
* @since 4.1.0
* @return
* Returns a column that evaluates to a timestamp.
+ *
+ * @note
+ * Affected by these public SQL configurations:
+ * - `spark.sql.ansi.enabled`
Review Comment:
Good catch. I traced each arity through the timestamp expression builders
and updated the Scala notes per overload in f2ffca7bf8e. Explicit-timezone
forms no longer list the session time zone; the date/time constructors no
longer list ANSI or timestamp type; `make_timestamp_ntz(date, time)` and
no-argument `unix_timestamp()` no longer have config notes. I applied the same
corrections to the analogous `try_make_timestamp*` overloads. Python exposes
one docstring for all typing overloads, so it retains the union of configs that
can affect at least one supported call form.
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sql/api/src/main/scala/org/apache/spark/sql/functions.scala:
##########
@@ -13124,6 +13403,10 @@ object functions {
* @since 3.5.0
* @return
* Returns a column that evaluates to a timestamp.
+ *
+ * @note
+ * Affected by these public SQL configurations:
+ * - `spark.sql.session.timeZone`
Review Comment:
Confirmed. Both LTZ and NTZ builders construct `ParseToTimestamp`, whose
default `failOnError` is `SQLConf.get.ansiEnabled`. In f2ffca7bf8e I added
`spark.sql.ansi.enabled` to both Scala overloads of `to_timestamp_ltz` and
`to_timestamp_ntz`, and to both Python docstrings. I also clarified that
invalid input returns null only with ANSI disabled and raises an error
otherwise.
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sql/api/src/main/scala/org/apache/spark/sql/functions.scala:
##########
@@ -1724,6 +1736,10 @@ object functions {
* @since 1.3.0
* @return
* Returns a column that evaluates to a numeric or interval.
+ *
+ * @note
+ * Affected by these public SQL configurations:
+ * - `spark.sql.ansi.enabled`
Review Comment:
Confirmed all of these paths: `mean` resolves to `Average`; `sum_distinct`
and `sumDistinct` resolve to `Sum`; `negative` and `negate` resolve to
`UnaryMinus`; and `pmod` uses `NumericEvalContext`, all of which read ANSI
mode. `TryReflect` wraps `CallMethodViaReflection`, whose analysis still
enforces `spark.sql.reflect.allowList`. I added the Scala and Python notes in
f2ffca7bf8e; the Python `negate` alias shares `negative`'s docstring.
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