You are viewing a plain text version of this content. The canonical link for it is here.
Posted to reviews@spark.apache.org by "cloud-fan (via GitHub)" <gi...@apache.org> on 2023/09/18 05:33:12 UTC

[GitHub] [spark] cloud-fan commented on a diff in pull request #42971: [SPARK-43979][SQL][FOLLOWUP] Handle non alias-only project case

cloud-fan commented on code in PR #42971:
URL: https://github.com/apache/spark/pull/42971#discussion_r1328261941


##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala:
##########
@@ -1131,17 +1130,24 @@ trait CheckAnalysis extends PredicateHelper with LookupCatalog with QueryErrorsB
    * remove extra project which only re-assign expr ids from the plan so that we can identify exact
    * duplicates metric definition.
    */
-  private def simplifyPlanForCollectedMetrics(plan: LogicalPlan): LogicalPlan = {
+  def simplifyPlanForCollectedMetrics(plan: LogicalPlan): LogicalPlan = {
     plan.resolveOperators {
       case p: Project if p.projectList.size == p.child.output.size =>
-        val assignExprIdOnly = p.projectList.zipWithIndex.forall {
+        var assignExprIdOnly = p.projectList.zipWithIndex.forall {
           case (Alias(attr: AttributeReference, _), index) =>
             // The input plan of this method is already canonicalized. The attribute id becomes the
             // ordinal of this attribute in the child outputs. So an alias-only Project means the
             // the id of the aliased attribute is the same as its index in the project list.
             attr.exprId.id == index
           case _ => false

Review Comment:
   I think we just need to add one more case match here
   ```
   // Both Attribute has been canonicalized to use index as the attr id, so `semanticEquals` still works here.
   case (left: Attribute, right: Attribute) => left.semanticEquals(right)
   ```



-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org


---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org