ulysses-you commented on code in PR #57396:
URL: https://github.com/apache/spark/pull/57396#discussion_r3626874935


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sql/core/src/main/scala/org/apache/spark/sql/execution/PushDownLocalSort.scala:
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@@ -0,0 +1,136 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution
+
+import org.apache.spark.sql.catalyst.expressions.{Alias, Attribute, 
AttributeMap, AttributeReference, AttributeSet, SortOrder}
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.execution.aggregate.SortAggregateExec
+import org.apache.spark.sql.execution.window.{WindowExecBase, 
WindowGroupLimitExec}
+import org.apache.spark.sql.internal.SQLConf
+
+/**
+ * Pushes a wider local sort down through order-preserving operators onto a 
narrower local sort
+ * below, widening it so that a single sort satisfies several operators' 
ordering requirements
+ * instead of re-sorting once per operator.
+ *
+ * `EnsureRequirements` adds one local `SortExec` (`global = false`) above 
every operator whose
+ * `requiredChildOrdering` is not already satisfied. When such requirements 
are in a prefix-cover
+ * relationship, this produces multiple local sorts that only differ in width. 
A canonical case is a
+ * sort aggregate stacked on a window over the same clustering keys, where the 
aggregate needs a
+ * wider ordering than the window:
+ *
+ * {{{
+ *   SortAggregate(key = [a, b, c])
+ *     Sort([a, b, c], global = false)   <- upper, wider
+ *       Window([a], [b])
+ *         Sort([a, b], global = false)  <- lower, narrower
+ *           Exchange(hashpartitioning([a]))
+ * }}}
+ *
+ * Because every operator between the two sorts is order-preserving and the 
upper ordering
+ * prefix-covers everything required along the way, the wider ordering can be 
pushed down to widen
+ * the lower sort, and the upper sort then dropped entirely:
+ *
+ * {{{
+ *   SortAggregate(key = [a, b, c])
+ *     Window([a], [b])                  requiredChildOrdering [a, b] is 
satisfied by [a, b, c]
+ *       Sort([a, b, c], global = false) <- single sort now serves both 
operators
+ *         Exchange(hashpartitioning([a]))
+ * }}}
+ *
+ * When an operator on the path renames an ordering column in its output (a 
`ProjectExec` with
+ * `b AS x`, or a `SortAggregateExec` whose result renames a grouping key), 
the ordering is
+ * rewritten from the operator's output space back to its child's space (`x` 
-> `b`) as it is
+ * pushed through, so a sort over the renamed column is still matched below. 
Only plain renames
+ * are followed, and the rule never crosses a shuffle or a 
non-order-preserving operator.
+ */
+object PushDownLocalSort extends Rule[SparkPlan] {
+
+  def apply(plan: SparkPlan): SparkPlan = {
+    if (!conf.getConf(SQLConf.PUSH_DOWN_LOCAL_SORT_ENABLED)) {
+      return plan
+    }
+
+    plan.transform {
+      case upper @ SortExec(upperOrder, false, child, _) =>
+        pushDown(child, upperOrder).getOrElse(upper)
+    }
+  }
+
+  /**
+   * Walks down from `plan` through a chain of order-preserving unary 
operators, looking for a
+   * lower local `SortExec` that `upperOrder` strictly covers. When found, 
widens that lower sort
+   * to `upperOrder` and returns the rebuilt subtree (which re-exposes 
`upperOrder` at its top);
+   * returns `None` if no safe widening applies, leaving the plan untouched. 
As it crosses an
+   * operator that renames ordering columns, `upperOrder` is rewritten into 
that operator's child
+   * space so the search continues against the child's own attributes.
+   */
+  private def pushDown(
+      plan: SparkPlan,
+      upperOrder: Seq[SortOrder]): Option[SparkPlan] = plan match {
+    case lower @ SortExec(lowerOrder, false, _, _)
+        // Only widen when the upper ordering strictly covers the lower one. 
When they are
+        // equivalent the upper sort is plainly redundant and is left to 
`RemoveRedundantSorts`; a
+        // non-covering ordering cannot serve the lower requirement. The 
column check keeps the
+        // widened sort well-formed (every key of `upperOrder` is available 
below the lower sort).
+        if SortOrder.orderingSatisfies(upperOrder, lowerOrder) &&
+          !SortOrder.orderingSatisfies(lowerOrder, upperOrder) &&
+          
AttributeSet(upperOrder.flatMap(_.references)).subsetOf(lower.child.outputSet) 
=>
+      Some(SortExec(upperOrder, global = false, child = lower.child))
+
+    case op: UnaryExecNode if isOrderPreserving(op) =>
+      // Some order-preserving operators rename ordering columns in their 
output (a `ProjectExec`
+      // with `b AS x`, or a `SortAggregateExec` whose result renames a 
grouping key). Rewrite
+      // `upperOrder` from the operator's output space back to its child's 
space before pushing
+      // further down. Only plain renames are followed; an expression alias 
leaves the sort key
+      // referencing an output attribute the child does not produce, so the 
check below rejects it.
+      val outputExprs = plan match {
+        case p: ProjectExec => p.projectList
+        case a: SortAggregateExec => a.resultExpressions
+        case _ => Nil
+      }
+      val rewrittenUpperOrder = if (outputExprs.isEmpty) {
+        upperOrder
+      } else {
+        val aliasToAttributeMap = AttributeMap(outputExprs.collect {
+          case a @ Alias(child: AttributeReference, _) => (a.toAttribute, 
child: Attribute)
+        })
+        upperOrder.map { _.transformUp {
+            case a: Attribute => aliasToAttributeMap.getOrElse(a, a)
+          }.asInstanceOf[SortOrder]
+        }
+      }
+      if (SortOrder.orderingSatisfies(rewrittenUpperOrder, 
op.requiredChildOrdering.head) &&
+          
AttributeSet(rewrittenUpperOrder.flatMap(_.references)).subsetOf(op.child.outputSet))
 {
+        pushDown(op.child, rewrittenUpperOrder).map(newChild => 
op.withNewChildren(Seq(newChild)))
+      } else {
+        None
+      }
+
+    case _ => None
+  }
+
+  private def isOrderPreserving(plan: UnaryExecNode): Boolean = plan match {
+    case _: ProjectExec => true
+    case _: FilterExec => true
+    case _: SortAggregateExec => true

Review Comment:
   Agreed, and thanks for the careful trace — your reasoning is exactly right. 
I verified it three ways (constructed plans, a plan-level probe with the window 
and aggregate co-partitioned so no shuffle separates them, and the general 
argument): to push through a `SortAggregateExec`, line 118 forces the ordering 
to prefix-cover the grouping keys and line 119 forces every key to be a child 
column, but the aggregate’s child is already sorted by the full grouping keys, 
and any extra column would be an aggregate result absent from 
`child.outputSet`. So the pushed ordering can never be strictly wider than the 
sort `EnsureRequirements` places directly beneath the aggregate — the branch 
never fires.
   
   Dropped `SortAggregateExec` from `isOrderPreserving` and removed the 
`resultExpressions` rename path. The canonical window-to-sort-aggregate test 
still passes: there the aggregate is the top consumer and the push-down 
traverses the `Window`, so the aggregate itself is never traversed.



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