[GitHub] [spark] cloud-fan commented on a change in pull request #28785: [SPARK-31958][SQL] normalize special floating numbers in subquery

[GitBox <gi...@apache.org>]

cloud-fan commented on a change in pull request #28785:
URL: https://github.com/apache/spark/pull/28785#discussion_r438568381



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File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/NormalizeFloatingNumbers.scala
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@@ -56,10 +56,6 @@ import org.apache.spark.sql.types._
 object NormalizeFloatingNumbers extends Rule[LogicalPlan] {
 
   def apply(plan: LogicalPlan): LogicalPlan = plan match {
-    // A subquery will be rewritten into join later, and will go through this rule
-    // eventually. Here we skip subquery, as we only need to run this rule once.
-    case _: Subquery => plan

Review comment:
       No we can't.
   
   This fix relies on the rule `OptimizeSubqueries`, which is an inner object of the `class Optimizer` as it needs to rerun the entire optimizer for subquery. So we can't use `OptimizeSubqueries` in `NormalizeFloatingPointNumbersSuite`.




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