You are viewing a plain text version of this content. The canonical link for it is here.
Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2020/11/16 07:04:50 UTC

[GitHub] [spark] cloud-fan commented on a change in pull request #30368: [SPARK-33442][SQL] Change Combine Limit to Eliminate limit using max row

cloud-fan commented on a change in pull request #30368:
URL: https://github.com/apache/spark/pull/30368#discussion_r523931544



##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
##########
@@ -1452,11 +1452,27 @@ object PushPredicateThroughJoin extends Rule[LogicalPlan] with PredicateHelper {
 }
 
 /**
- * Combines two adjacent [[Limit]] operators into one, merging the
- * expressions into one single expression.
+ * 1. Eliminate [[Limit]] operators if it's child max row <= limit.
+ * 2. Combines two adjacent [[Limit]] operators into one, merging the
+ *    expressions into one single expression.
  */
-object CombineLimits extends Rule[LogicalPlan] {
-  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
+object EliminateLimits extends Rule[LogicalPlan] {
+  private def canEliminate(limitExpr: Expression, child: LogicalPlan): Boolean = {
+    // We skip such case that Sort is after Limit since
+    // SparkStrategies will convert them to TakeOrderedAndProjectExec
+    val skipEliminate = child match {
+      case Sort(_, true, _) => true

Review comment:
       does `TakeOrderedAndProjectExec` really help if we need to get and sort all the output?




----------------------------------------------------------------
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.

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