rich7420 commented on code in PR #7457:
URL: https://github.com/apache/datafusion-comet/pull/7457#discussion_r4485316487
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spark/src/main/scala/org/apache/comet/expressions/CometCast.scala:
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@@ -572,6 +572,32 @@ object CometCast
private[comet] def canProduceNullMapKey(cast: Cast): Boolean =
evalMode(cast) == CometEvalMode.TRY && mayNullMapKey(cast.child.dataType,
cast.dataType)
+ /**
+ * Whether `cast` cannot raise an error for any value. A TRY cast returns
NULL for a value it
+ * cannot convert, and so does a LEGACY cast between the atomic types listed
here. An ANSI cast
+ * cannot fail only where the conversion is always exact, such as a widening
one or a string to
+ * its bytes. A cast to or from a timestamp is excluded in every mode: the
native kernels go
+ * through chrono, which rejects years Spark accepts, and raise even for TRY.
+ */
+ private[comet] def cannotFail(cast: Cast): Boolean = {
+ val from = cast.child.dataType
+ val to = cast.dataType
+ def isTimestamp(t: DataType) = t == TimestampType || t == TimestampNTZType
+ !isTimestamp(from) && !isTimestamp(to) && (evalMode(cast) match {
+ case CometEvalMode.TRY => true
Review Comment:
`try_cast(ts_array AS STRING)` bypasses this timestamp check. With
`Long.MaxValue` microseconds, the native cast errors while Spark formats it.
Check nested timestamp types too, with a TopK regression.
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