Github user dilipbiswal commented on a diff in the pull request:
https://github.com/apache/spark/pull/17330#discussion_r107713751
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/subquery.scala
---
@@ -83,6 +116,20 @@ object SubqueryExpression {
case _ => false
}.isDefined
}
+
+ /**
+ * Clean the outer references by normalizing them to BindReference in
the same way
+ * we clean up the arguments during LogicalPlan.sameResult. This enables
to compare two
+ * plans which has subquery expressions. This method returns a
[[CanonicalizedSubqueryExpr]]
+ * which wraps the underlying [[SubqueryExpression]].
+ */
+ def canonicalize(e: SubqueryExpression, attrs: AttributeSeq):
CanonicalizedSubqueryExpr = {
+ // Normalize the outer references in the subquery plan.
+ val subPlan = e.plan.transformAllExpressions {
+ case OuterReference(r) => BindReferences.bindReference(r, attrs,
allowFailures = true)
--- End diff --
@cloud-fan Hi Wenchen, If we are able to normalize all the expression ids,
then i think we can solve the nondeterministic problem. I had actually tried
this for the new test cases i have added. But i didn't go with this as i felt i
may have to test this more. In my testing, i only normalized the
AttributeReference .. but we can have generated expression ids for other
expressions, right , Aliases, SubqueryExpression etc. We also need to normalize
these as well, no ?
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