HuwCampbell commented on code in PR #36441:
URL: https://github.com/apache/spark/pull/36441#discussion_r973814236
##########
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/HigherOrderFunctionsSuite.scala:
##########
@@ -839,6 +841,52 @@ class HigherOrderFunctionsSuite extends SparkFunSuite with
ExpressionEvalHelper
Seq(1d, 2d, Double.NaN, null))
}
+ test("SPARK-39081: compatibility of combo of HigherOrderFunctions" +
+ " with other Expression subclasses") {
+ // Dummy example given in JIRA, this is to test a compile time issue only,
has no real usage
+ case class MyExploder(
+ arrays: Expression, // Array[AnyDataType]
+ asOfDate: Expression, //
LambdaFunction[AnyDataType -> TimestampType]
+ extractor: Expression) // TimestampType
+ extends HigherOrderFunction with Generator with TimeZoneAwareExpression {
+
+ override def children: Seq[Expression] = Seq[Expression](arrays,
asOfDate)
+
+ override def withNewChildrenInternal(newChildren:
IndexedSeq[Expression]): Expression = null
+
+ override def eval(input: InternalRow): TraversableOnce[InternalRow] =
null
+
+ override def nodePatternsInternal(): Seq[TreePattern] = Seq()
+
+ override def elementSchema: StructType = null
+
+ override def arguments: Seq[Expression] =
+ Seq(arrays, asOfDate)
+
+ override def argumentTypes: Seq[AbstractDataType] =
+ Seq(ArrayType, TimestampType)
+
+ override def doGenCode(ctx: CodegenContext, exp: ExprCode): ExprCode =
null
+
+ override def functions: Seq[Expression] =
+ Seq(extractor)
+
+ override def functionTypes: Seq[TimestampType] =
+ Seq(TimestampType)
+
+ override def bind(f: (Expression,
+ Seq[(DataType, Boolean)]) => LambdaFunction): HigherOrderFunction =
null
+
+ override def timeZoneId: Option[String] = None
+
+ override def withTimeZone(timeZoneId: String): TimeZoneAwareExpression =
null
+ }
+
+ /* Should not get the error - value nodePatterns
+ ... cannot override final member, or conflict in nodePatterns between two
types
Review Comment:
Yeah I think you're pretty much dead on here, the correctness of the
optimiser will be up to the user to enforce; as they will need to ensure that
all node patterns are accounted for.
But, and it's a big one, it makes it possible to compose these interfaces,
even with the extra challenges... which it's just _not_ possible to do as of
Spark 3.2.
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