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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2021/11/29 15:26:12 UTC
[GitHub] [spark] MaxGekk commented on a change in pull request #34716: [SPARK-37468][SQL] Support ANSI intervals and TimestampNTZ for UnionEstimation
MaxGekk commented on a change in pull request #34716:
URL: https://github.com/apache/spark/pull/34716#discussion_r758469434
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/statsEstimation/UnionEstimation.scala
##########
@@ -50,13 +50,23 @@ object UnionEstimation {
case TimestampType => (a: Any, b: Any) =>
TimestampType.ordering.lt(a.asInstanceOf[TimestampType.InternalType],
b.asInstanceOf[TimestampType.InternalType])
+ case TimestampNTZType => (a: Any, b: Any) =>
+ TimestampNTZType.ordering.lt(a.asInstanceOf[TimestampNTZType.InternalType],
+ b.asInstanceOf[TimestampNTZType.InternalType])
+ case y: YearMonthIntervalType => (a: Any, b: Any) =>
+ y.ordering.lt(a.asInstanceOf[y.InternalType],
+ b.asInstanceOf[y.InternalType])
+ case d: DayTimeIntervalType => (a: Any, b: Any) =>
+ d.ordering.lt(a.asInstanceOf[d.InternalType],
+ b.asInstanceOf[d.InternalType])
case _ =>
throw new IllegalStateException(s"Unsupported data type: ${dt.catalogString}")
}
private def isTypeSupported(dt: DataType): Boolean = dt match {
case ByteType | IntegerType | ShortType | FloatType | LongType |
- DoubleType | DateType | _: DecimalType | TimestampType => true
+ DoubleType | DateType | _: DecimalType | TimestampType | TimestampNTZType |
+ _: YearMonthIntervalType | _: DayTimeIntervalType => true
Review comment:
```suggestion
_: AnsiIntervalType => true
```
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/statsEstimation/UnionEstimation.scala
##########
@@ -50,13 +50,23 @@ object UnionEstimation {
case TimestampType => (a: Any, b: Any) =>
TimestampType.ordering.lt(a.asInstanceOf[TimestampType.InternalType],
b.asInstanceOf[TimestampType.InternalType])
+ case TimestampNTZType => (a: Any, b: Any) =>
+ TimestampNTZType.ordering.lt(a.asInstanceOf[TimestampNTZType.InternalType],
+ b.asInstanceOf[TimestampNTZType.InternalType])
+ case y: YearMonthIntervalType => (a: Any, b: Any) =>
+ y.ordering.lt(a.asInstanceOf[y.InternalType],
+ b.asInstanceOf[y.InternalType])
+ case d: DayTimeIntervalType => (a: Any, b: Any) =>
+ d.ordering.lt(a.asInstanceOf[d.InternalType],
+ b.asInstanceOf[d.InternalType])
Review comment:
```suggestion
case i: AnsiIntervalType => (a: Any, b: Any) =>
i.ordering.lt(a.asInstanceOf[i.InternalType], b.asInstanceOf[i.InternalType])
```
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