Github user EntilZha commented on a diff in the pull request:
https://github.com/apache/spark/pull/7580#discussion_r35294529
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
---
@@ -35,3 +36,47 @@ case class Size(child: Expression) extends
UnaryExpression with ExpectsInputType
nullSafeCodeGen(ctx, ev, c => s"${ev.primitive} = ($c).size();")
}
}
+
+case class ArrayContains(left: Expression, right: Expression) extends
BinaryExpression with ExpectsInputTypes {
+ override def dataType: DataType = BooleanType
+
+ override def inputTypes: Seq[AbstractDataType] = Seq(ArrayType,
AnyDataType)
--- End diff --
My more specific question would be, how should `checkInputDataTypes` look?
It seems that the array type and value type should match in "class" of types
(eg ints/longs, floats/doubles, perhaps numerics in general, and separately
strings etc). I tried using `acceptsType`, but that doesn't seem to be general
enough. Should I enumerate all those cases or is there a shortcut?
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