cloud-fan commented on code in PR #40093:
URL: https://github.com/apache/spark/pull/40093#discussion_r1121416560
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/expressions.scala:
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@@ -200,14 +200,20 @@ object ConstantPropagation extends Rule[LogicalPlan] {
private def replaceConstants(condition: Expression, equalityPredicates:
EqualityPredicates)
: Expression = {
- val constantsMap = AttributeMap(equalityPredicates.map(_._1))
- val predicates = equalityPredicates.map(_._2).toSet
- def replaceConstants0(expression: Expression) = expression transform {
+ val allConstantsMap = AttributeMap(equalityPredicates.map(_._1))
+ val allPredicates = equalityPredicates.map(_._2).toSet
+ def replaceConstants0(
+ expression: Expression, constantsMap: AttributeMap[Literal]) =
expression transform {
case a: AttributeReference => constantsMap.getOrElse(a, a)
}
condition transform {
- case e @ EqualTo(_, _) if !predicates.contains(e) => replaceConstants0(e)
- case e @ EqualNullSafe(_, _) if !predicates.contains(e) =>
replaceConstants0(e)
+ case b: BinaryComparison =>
Review Comment:
It seems https://github.com/apache/spark/pull/24553 is a more comprehensive
optimization, but we should keep the algorithm simple:
1. Collecting constants for non-attribute expressions seems very complicated
to me. What if the non-attribute expressions have dependencies by themselves?
2. We should avoid replacing constants in expressions recursively. To
support `a = 1 AND a = 2` ===> `false`, can we detect it earlier when building
the attribute -> constant map and return false?
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