sunchao commented on a change in pull request #33930:
URL: https://github.com/apache/spark/pull/33930#discussion_r707916583
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/expressions.scala
##########
@@ -797,6 +834,19 @@ object NullPropagation extends Rule[LogicalPlan] {
// a null literal.
case e: NullIntolerant if e.children.exists(isNullLiteral) =>
Literal.create(null, e.dataType)
+
+ // [SPARK-36665] Unwrap inside of IsNull/IsNotNull if the inside is
NullIntolerant
+ // E.g. IsNull(Not(null)) == IsNull(null)
+ // Cannot apply to `ExtractValue` as the query planner uses the trait to
resolve the columns.
+ // E.g. the planner may resolve column `a` to `a#123`, then
IsNull(a#123) cannot be optimized
+ // UnaryExpression only for now as applying this optimization to other
expressions is too
+ // disruptive for some tests (e.g. [SPARK-32290].) TODO remove
e.isInstanceOf[UnaryExpression]
+ case IsNull(e: NullIntolerant) if e.isInstanceOf[UnaryExpression] &&
Review comment:
I wonder if we should check whether `e` is deterministic - are we
allowed to skip evaluating it if it is not?
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/expressions.scala
##########
@@ -797,6 +834,19 @@ object NullPropagation extends Rule[LogicalPlan] {
// a null literal.
case e: NullIntolerant if e.children.exists(isNullLiteral) =>
Literal.create(null, e.dataType)
+
+ // [SPARK-36665] Unwrap inside of IsNull/IsNotNull if the inside is
NullIntolerant
+ // E.g. IsNull(Not(null)) == IsNull(null)
+ // Cannot apply to `ExtractValue` as the query planner uses the trait to
resolve the columns.
+ // E.g. the planner may resolve column `a` to `a#123`, then
IsNull(a#123) cannot be optimized
+ // UnaryExpression only for now as applying this optimization to other
expressions is too
+ // disruptive for some tests (e.g. [SPARK-32290].) TODO remove
e.isInstanceOf[UnaryExpression]
+ case IsNull(e: NullIntolerant) if e.isInstanceOf[UnaryExpression] &&
+ !e.isInstanceOf[ExtractValue] && e.children.nonEmpty =>
+ e.children.map(IsNull(_): Expression).reduceLeft(Or)
Review comment:
can we simplify this? shouldn't `UnaryExpression` only have one child?
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/expressions.scala
##########
@@ -441,6 +457,27 @@ object BooleanSimplification extends Rule[LogicalPlan]
with PredicateHelper {
case Not(IsNull(e)) => IsNotNull(e)
case Not(IsNotNull(e)) => IsNull(e)
+
+ // Move `Not` from one side of `EqualTo`/`EqualNullSafe` to the other
side if it's beneficial.
+ // E.g. `EqualTo(Not(a), b)` where `b = Not(c)`, it will become
+ // `EqualTo(a, Not(b))` => `EqualTo(a, Not(Not(c)))` => `EqualTo(a, c)`
+ // In addition, `if canSimplifyNot(b)` checks if the optimization can
converge
+ // that avoids the situation two conditions are returning to each other.
+ case EqualTo(Not(a), b) if !canSimplifyNot(a) && canSimplifyNot(b) =>
EqualTo(a, Not(b))
Review comment:
I wonder how much extra costs will this incur. Since now this transforms
the original expression to `EqualTo(a, Not(b))`, we'll need to apply
`BooleanSimplification` again to simplify the `Not(b)` (since it is a child of
`EqualTo` and the rule runs bottom-up. Does this mean we'd need to run more
iterations on the `operatorOptimizationBatch` (see `Optimizer`) until it can
reach a fix point?
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