viirya commented on code in PR #56334:
URL: https://github.com/apache/spark/pull/56334#discussion_r3554429297
##########
sql/api/src/main/scala/org/apache/spark/sql/util/ArrowUtils.scala:
##########
@@ -38,6 +38,50 @@ private[sql] object ArrowUtils {
// todo: support more types.
+ /**
+ * Check if a Spark DataType is supported by Arrow. This recursively checks
complex types
+ * (Array, Struct, Map).
+ *
+ * Note: This checks compatibility with toArrowField(), not toArrowType().
Types like
+ * GeometryType, GeographyType, and VariantType are not supported by
toArrowType() (which only
+ * handles primitive Arrow types), but ARE supported by toArrowField() which
converts them to
+ * Arrow Struct representations with metadata. Since Arrow cache uses
toArrowField() via
+ * toArrowSchema() to create the schema, these types are supported.
+ */
+ def isSupportedByArrow(dt: DataType): Boolean = {
+ dt match {
+ // Primitive types
+ case BooleanType | ByteType | ShortType | IntegerType | LongType |
FloatType | DoubleType |
+ _: StringType | BinaryType | NullType =>
+ true
+
+ // Decimal
+ case _: DecimalType => true
+
+ // Temporal types
+ case DateType | TimestampType | TimestampNTZType | _: TimeType => true
+
+ // Interval types
+ case _: YearMonthIntervalType | _: DayTimeIntervalType |
CalendarIntervalType => true
Review Comment:
Done. With SPARK-57975 and SPARK-58005 merged, this PR now opts the cache
into the lossless encodings (`losslessInternalTypes = true` at the
schema-construction sites) and deletes `withIntervalOverflowTranslation`
entirely -- on the cache path there is no longer a nanosecond conversion that
can overflow, so the mis-attribution you found is gone along with the wrapper:
your ANSI `DIVIDE_BY_ZERO` repro surfaces `DIVIDE_BY_ZERO` regardless of
interval columns. The overflow diagnostic test is replaced by a full-domain
round-trip test (`microseconds = Long.MaxValue` etc., top-level and nested),
and the docs now state the cache matches the default serializer's full value
domain for this type.
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