sunchao commented on code in PR #7283:
URL: https://github.com/apache/datafusion-comet/pull/7283#discussion_r4404891675


##########
spark/src/main/scala/org/apache/comet/rules/MakeDateEvaluation.scala:
##########
@@ -0,0 +1,371 @@
+/*
+ * 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.comet.rules
+
+import org.apache.spark.sql.catalyst.expressions.{Add, Alias, And, Attribute, 
AttributeSet, BinaryComparison, Cast, ConditionalExpression, CreateArray, 
CreateNamedStruct, DateAdd, DateDiff, DateFormatClass, DateSub, EqualNullSafe, 
Expression, Greatest, HashExpression, IsNotNull, IsNull, Least, MakeDate, 
Multiply, Not, Or, SortOrder, Subtract, UnixDate}
+import org.apache.spark.sql.catalyst.optimizer.BuildLeft
+import org.apache.spark.sql.catalyst.trees.TreeNodeTag
+import org.apache.spark.sql.comet._
+import org.apache.spark.sql.comet.execution.shuffle.CometShuffleExchangeExec
+import org.apache.spark.sql.execution._
+import org.apache.spark.sql.execution.adaptive.{BroadcastQueryStageExec, 
QueryStageExec}
+import org.apache.spark.sql.execution.aggregate.{BaseAggregateExec, 
HashAggregateExec, ObjectHashAggregateExec}
+import org.apache.spark.sql.execution.exchange.{Exchange, ReusedExchangeExec}
+import org.apache.spark.sql.execution.joins.{BaseJoinExec, 
BroadcastHashJoinExec, BroadcastNestedLoopJoinExec}
+
+import org.apache.comet.CometConf
+import org.apache.comet.serde.CometMakeDate
+import org.apache.comet.shims.ShimCometWindowGroupLimit
+
+/** Keeps make_date on Spark's row path where native batching can change 
whether it throws. */
+private[rules] object MakeDateEvaluation {
+  private val sparkEvaluation = 
TreeNodeTag[String]("comet.makeDateSparkEvaluation")
+
+  private def enabled(plan: SparkPlan): Boolean =
+    CometConf.COMET_EXEC_MAKE_DATE_OPERATOR_FALLBACK_ENABLED.get(plan.conf)
+
+  def reason(plan: SparkPlan): Option[String] =
+    if (enabled(plan)) plan.getTagValue(sparkEvaluation) else None
+
+  private def containsMakeDate(expressions: Seq[Expression]): Boolean =
+    expressions.exists(_.exists(_.isInstanceOf[MakeDate]))
+
+  private case class ProjectionDemand(
+      boundary: String,
+      deferred: AttributeSet,
+      // Deferred inputs whose producers need guarding even when they contain 
no make_date.
+      guardedInputs: AttributeSet,
+      // Date argument lineage retained until a streamed join can skip its 
input rows.
+      dateInputs: AttributeSet)
+
+  // Attributes may stand for deferred expressions in a lower projection, not 
materialized values.
+  private def harmlessValue(expression: Expression): Boolean =
+    expression.references.isEmpty && 
CometMakeDate.canEvaluateEagerly(expression)
+
+  /** References that a consumer requires without exposing a potentially 
skipped sibling. */
+  private def eagerReferences(expression: Expression): AttributeSet = 
expression match {
+    case attribute: Attribute => AttributeSet(Seq(attribute))
+    case _ =>
+      val children = expression match {
+        case date: MakeDate =>
+          val firstNullable = date.children.indexWhere(_.nullable)
+          date.children.take(if (firstNullable < 0) date.children.size else 
firstNullable + 1)
+        case conditional: ConditionalExpression =>
+          val required = conditional.alwaysEvaluatedInputs
+          if 
(conditional.children.filterNot(required.contains).forall(harmlessValue)) 
required
+          else Nil
+        case _: Alias | _: Cast | _: IsNull | _: IsNotNull | _: Not | _: 
UnixDate =>
+          expression.children
+        case _: EqualNullSafe | _: CreateArray | _: CreateNamedStruct | _: 
Greatest | _: Least |
+            _: HashExpression[_] =>
+          expression.children
+        case _: And | _: Or =>
+          if (harmlessValue(expression.children(1))) 
expression.children.take(1) else Nil
+        case _: Add | _: Subtract | _: Multiply | _: BinaryComparison | _: 
DateAdd | _: DateSub |
+            _: DateDiff | _: DateFormatClass =>
+          val left = expression.children.head
+          val right = expression.children(1)
+          if (!left.nullable) expression.children
+          // A right-hand attribute can inline a throwing expression from an 
earlier projection.
+          // Only self-contained harmless values are safe without tracing that 
attribute's source.
+          else if (harmlessValue(right)) Seq(left)
+          else Nil
+        // Unknown expressions may skip inputs or catch errors raised by their 
children.

Review Comment:
   [P2] Follow the eager child of YEAR when computing projection demand
   
   Could this recognize eager date extractors such as `YEAR` while retaining 
any enclosing conditional mask? For `SELECT r, YEAR(dt), r + 1 FROM (SELECT 
rand(7) AS r, make_date(y,m,d) AS dt FROM t)`, the repeated `r` retains 
separate projections. `YEAR` evaluates its child, but the default `Nil` marks 
`dt` deferred and moves both projections to Spark even for this eager consumer.
   
   The same shape and an overflow control were reproduced in [the parent PR 
discussion](https://github.com/apache/datafusion-comet/pull/7117#discussion_r4367129483).
 Those measurements were on the parent revision, not this head.



##########
spark/src/main/scala/org/apache/comet/rules/MakeDateEvaluation.scala:
##########
@@ -0,0 +1,371 @@
+/*
+ * 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.comet.rules
+
+import org.apache.spark.sql.catalyst.expressions.{Add, Alias, And, Attribute, 
AttributeSet, BinaryComparison, Cast, ConditionalExpression, CreateArray, 
CreateNamedStruct, DateAdd, DateDiff, DateFormatClass, DateSub, EqualNullSafe, 
Expression, Greatest, HashExpression, IsNotNull, IsNull, Least, MakeDate, 
Multiply, Not, Or, SortOrder, Subtract, UnixDate}
+import org.apache.spark.sql.catalyst.optimizer.BuildLeft
+import org.apache.spark.sql.catalyst.trees.TreeNodeTag
+import org.apache.spark.sql.comet._
+import org.apache.spark.sql.comet.execution.shuffle.CometShuffleExchangeExec
+import org.apache.spark.sql.execution._
+import org.apache.spark.sql.execution.adaptive.{BroadcastQueryStageExec, 
QueryStageExec}
+import org.apache.spark.sql.execution.aggregate.{BaseAggregateExec, 
HashAggregateExec, ObjectHashAggregateExec}
+import org.apache.spark.sql.execution.exchange.{Exchange, ReusedExchangeExec}
+import org.apache.spark.sql.execution.joins.{BaseJoinExec, 
BroadcastHashJoinExec, BroadcastNestedLoopJoinExec}
+
+import org.apache.comet.CometConf
+import org.apache.comet.serde.CometMakeDate
+import org.apache.comet.shims.ShimCometWindowGroupLimit
+
+/** Keeps make_date on Spark's row path where native batching can change 
whether it throws. */
+private[rules] object MakeDateEvaluation {
+  private val sparkEvaluation = 
TreeNodeTag[String]("comet.makeDateSparkEvaluation")
+
+  private def enabled(plan: SparkPlan): Boolean =
+    CometConf.COMET_EXEC_MAKE_DATE_OPERATOR_FALLBACK_ENABLED.get(plan.conf)
+
+  def reason(plan: SparkPlan): Option[String] =
+    if (enabled(plan)) plan.getTagValue(sparkEvaluation) else None
+
+  private def containsMakeDate(expressions: Seq[Expression]): Boolean =
+    expressions.exists(_.exists(_.isInstanceOf[MakeDate]))
+
+  private case class ProjectionDemand(
+      boundary: String,
+      deferred: AttributeSet,
+      // Deferred inputs whose producers need guarding even when they contain 
no make_date.
+      guardedInputs: AttributeSet,
+      // Date argument lineage retained until a streamed join can skip its 
input rows.
+      dateInputs: AttributeSet)
+
+  // Attributes may stand for deferred expressions in a lower projection, not 
materialized values.
+  private def harmlessValue(expression: Expression): Boolean =
+    expression.references.isEmpty && 
CometMakeDate.canEvaluateEagerly(expression)
+
+  /** References that a consumer requires without exposing a potentially 
skipped sibling. */
+  private def eagerReferences(expression: Expression): AttributeSet = 
expression match {
+    case attribute: Attribute => AttributeSet(Seq(attribute))
+    case _ =>
+      val children = expression match {
+        case date: MakeDate =>
+          val firstNullable = date.children.indexWhere(_.nullable)
+          date.children.take(if (firstNullable < 0) date.children.size else 
firstNullable + 1)
+        case conditional: ConditionalExpression =>
+          val required = conditional.alwaysEvaluatedInputs
+          if 
(conditional.children.filterNot(required.contains).forall(harmlessValue)) 
required
+          else Nil
+        case _: Alias | _: Cast | _: IsNull | _: IsNotNull | _: Not | _: 
UnixDate =>
+          expression.children
+        case _: EqualNullSafe | _: CreateArray | _: CreateNamedStruct | _: 
Greatest | _: Least |
+            _: HashExpression[_] =>
+          expression.children
+        case _: And | _: Or =>
+          if (harmlessValue(expression.children(1))) 
expression.children.take(1) else Nil
+        case _: Add | _: Subtract | _: Multiply | _: BinaryComparison | _: 
DateAdd | _: DateSub |
+            _: DateDiff | _: DateFormatClass =>
+          val left = expression.children.head
+          val right = expression.children(1)
+          if (!left.nullable) expression.children
+          // A right-hand attribute can inline a throwing expression from an 
earlier projection.
+          // Only self-contained harmless values are safe without tracing that 
attribute's source.
+          else if (harmlessValue(right)) Seq(left)
+          else Nil
+        // Unknown expressions may skip inputs or catch errors raised by their 
children.
+        case _ => Nil
+      }
+      AttributeSet(children.flatMap(eagerReferences))
+  }
+
+  private def copyLogicalLinks(from: SparkPlan, to: SparkPlan): Unit = {
+    if (from ne to) {
+      // setLogicalLink promotes inherited links to direct links and rewrites 
descendants.
+      // Keep each tag's role and retain the fallback plan's links when the 
source has none.
+      Seq(SparkPlan.LOGICAL_PLAN_TAG, 
SparkPlan.LOGICAL_PLAN_INHERITED_TAG).foreach { tag =>
+        from.getTagValue(tag).foreach(to.setTagValue(tag, _))
+      }
+    }
+  }
+
+  private def nativeBroadcastInput(plan: SparkPlan): Option[SparkPlan] = plan 
match {
+    case _: CometBroadcastExchangeExec => Some(plan)
+    case stage: BroadcastQueryStageExec => 
nativeBroadcastInput(stage.plan).map(_ => stage)
+    case reuse: ReusedExchangeExec => nativeBroadcastInput(reuse.child).map(_ 
=> reuse)
+    case sink: CometSinkPlaceHolder => nativeBroadcastInput(sink.child)
+    case wrapper: CometScanWrapper => 
nativeBroadcastInput(wrapper.originalPlan)
+    case _ => None
+  }
+
+  private def restoreBroadcast(plan: SparkPlan, reason: String): SparkPlan =
+    nativeBroadcastInput(plan)
+      .map { input =>
+        // Spark joins need a HashedRelation (or rows for a nested-loop join), 
not Arrow buffers.
+        // The existing transition decodes the cached broadcast and applies 
its Spark broadcast
+        // mode, including through AQE/reuse wrappers, without re-executing 
the build input.
+        val restored = CometColumnarToRowExec(input)
+        restored.setTagValue(sparkEvaluation, reason)
+        copyLogicalLinks(plan, restored)
+        restored
+      }
+      .getOrElse(plan)
+
+  /**
+   * Run before bottom-up conversion and join rewriting. Reasons propagate 
back to the consuming
+   * operator, keeping the row pipeline together instead of inserting an eager 
Arrow batch between
+   * a throwing projection and its lazy consumer. Exchanges materialize their 
input independently;
+   * local sorts and aggregates do so only after their consumer requests input.
+   */
+  def preserve(plan: SparkPlan): SparkPlan = {
+    if (!enabled(plan)) return plan
+
+    def visit(
+        node: SparkPlan,
+        rowDemand: Option[String],
+        projectionDemand: Option[ProjectionDemand]): (SparkPlan, 
Option[String], AttributeSet) = {
+      node match {
+        // Materialized stages are independent producers. Their plans have 
already been guarded.
+        case _: QueryStageExec | _: ReusedExchangeExec => return (node, None, 
AttributeSet.empty)
+        // These wrappers do not have the child shape of their original Spark 
operator.
+        case wrapper: CometScanWrapper =>
+          val (child, childReason, dateOutputs) =
+            visit(wrapper.originalPlan, rowDemand, projectionDemand)
+          return if (childReason.isDefined) (child, childReason, dateOutputs)
+          else (wrapper.copy(originalPlan = child), None, dateOutputs)
+        case sink: CometSinkPlaceHolder =>
+          val (child, childReason, dateOutputs) = visit(sink.child, rowDemand, 
projectionDemand)
+          return if (childReason.isDefined) (child, childReason, dateOutputs)
+          else (sink.withNewChildren(Seq(child)), None, dateOutputs)
+        case _ =>
+      }
+
+      val original = node match {
+        case scan: CometScanExec =>
+          scan.wrapped.copy(
+            partitionFilters = scan.partitionFilters,
+            dataFilters = scan.dataFilters)
+        case scan: CometNativeScanExec => scan.sparkFallback(Nil)
+        case native: CometExec => native.originalPlan
+        case shuffle: CometShuffleExchangeExec => shuffle.originalPlan
+        case broadcast: CometBroadcastExchangeExec => broadcast.originalPlan
+        case _ => node
+      }
+      val evaluatesDate = containsMakeDate(original.expressions)
+      val exchange = original.isInstanceOf[Exchange]
+      val join = original.isInstanceOf[BaseJoinExec]
+      // Broadcast joins can inline streamed expressions into their consumer. 
Their build side
+      // materializes rows; shuffled hash and sort-merge joins also isolate 
the streamed input.
+      val streamedChildIndex = original match {
+        case hash: BroadcastHashJoinExec if hash.supportCodegen =>
+          Some(if (hash.buildSide == BuildLeft) 1 else 0)
+        case nestedLoop: BroadcastNestedLoopJoinExec if 
nestedLoop.supportCodegen =>
+          Some(if (nestedLoop.buildSide == BuildLeft) 1 else 0)
+        case _ => None
+      }
+      val localMaterialization = original match {
+        case _: SortExec | _: HashAggregateExec | _: ObjectHashAggregateExec 
=> true
+        case _: TakeOrderedAndProjectExec => true
+        case _ => false
+      }
+      val startsLimit = original match {
+        case _: CollectLimitExec | _: LocalLimitExec | _: GlobalLimitExec => 
true
+        case topK: TakeOrderedAndProjectExec =>
+          SortOrder.orderingSatisfies(topK.child.outputOrdering, 
topK.sortOrder)
+        case _
+            if 
ShimCometWindowGroupLimit.windowGroupLimitClass.exists(_.isInstance(original)) 
=>
+          true
+        case _ => false
+      }
+      val childDemand = original match {
+        case _ if exchange => None
+        // A join can leave a local sort or aggregate completely unpolled.
+        case _ if join || rowDemand.contains("JOIN") => Some("JOIN")
+        case _ if startsLimit => Some("LIMIT")
+        case _: SampleExec => Some("SAMPLE")
+        case _: MapPartitionsExec => Some("a mapPartitions function")
+        case _ if localMaterialization => None
+        case _ => rowDemand
+      }
+      val childProjectionDemand = original match {
+        // Generated filters can defer deterministic projection outputs until 
a row is accepted.
+        case filter: FilterExec =>
+          Some(
+            ProjectionDemand(
+              "FILTER",
+              filter.child.outputSet,
+              
projectionDemand.map(_.guardedInputs).getOrElse(AttributeSet.empty),
+              
projectionDemand.map(_.dateInputs).getOrElse(AttributeSet.empty)))
+        case project: ProjectExec =>
+          val deferred = 
projectionDemand.map(_.deferred).getOrElse(AttributeSet.empty)
+          val eager = project.projectList
+            .filter(output => !output.deterministic || 
!deferred.contains(output.toAttribute))
+            .flatMap(eagerReferences)
+          // ProjectExec forces repeated inputs and nondeterministic outputs. 
Other inputs can
+          // remain inlined in a consumer's conditional, even across 
intervening aliases.
+          val skipped = project.child.outputSet -- project.usedInputs -- 
AttributeSet(eager)
+          val inheritedInputs =
+            projectionDemand.map(_.guardedInputs).getOrElse(AttributeSet.empty)
+          // A consumer can require the date but still skip another output of 
this projection.
+          val guardedOutputs = inheritedInputs ++
+            (if (evaluatesDate) deferred else AttributeSet.empty)
+          val directDateInputs = AttributeSet(project.projectList.flatMap { 
output =>
+            output.collect { case date: MakeDate => date 
}.flatMap(_.references)
+          })
+          val inputsToGuard =
+            directDateInputs ++ AttributeSet(project.projectList.flatMap { 
output =>
+              if ((output.deterministic || rowDemand.isDefined) &&
+                guardedOutputs.contains(output.toAttribute)) {
+                output.references.toSeq
+              } else {
+                Nil
+              }
+            })
+          // Keep argument lineage through eager aliases too. A join below 
this projection can
+          // discard an input row before this projection ever requires the 
argument's value.
+          val dateInputs =
+            directDateInputs ++ AttributeSet(project.projectList.flatMap { 
output =>
+              if 
(projectionDemand.exists(_.dateInputs.contains(output.toAttribute))) {
+                output.references.toSeq
+              } else {
+                Nil
+              }
+            })
+          // A lazy row consumer can skip even the date's required arguments 
on unread rows.
+          val guardedChildInputs =
+            inputsToGuard.intersect(if (rowDemand.isDefined) 
project.child.outputSet else skipped)
+          if (skipped.isEmpty && guardedChildInputs.isEmpty && 
dateInputs.isEmpty) {
+            None
+          } else {
+            Some(
+              ProjectionDemand(
+                projectionDemand.map(_.boundary).getOrElse("PROJECT"),
+                skipped,
+                guardedChildInputs,
+                dateInputs))
+          }
+        case _ if exchange || localMaterialization => None
+        case _ => projectionDemand
+      }
+      val visited = node.children.zipWithIndex.map { case (child, index) =>
+        val demand = if (!join) {
+          childProjectionDemand
+        } else if (streamedChildIndex.contains(index)) {
+          childProjectionDemand.map { demand =>
+            // Keys and conditions force their inputs on each visited row. An 
outer row consumer
+            // can still skip that row altogether, so retain its guarded 
inputs in that case.
+            val required = if (rowDemand.isDefined) AttributeSet.empty else 
original.references
+            val streamedOutputs = original.children(index).outputSet
+            val forwarded = streamedOutputs -- required
+            demand.copy(
+              deferred = demand.deferred.intersect(forwarded),
+              guardedInputs = (demand.guardedInputs ++ 
demand.dateInputs).intersect(forwarded),
+              // A key is required only on this join's input rows. An earlier 
join can still
+              // discard rows before producing that key, so retain its 
argument lineage.
+              dateInputs = demand.dateInputs.intersect(streamedOutputs))
+          }
+        } else {
+          None
+        }
+        visit(child, childDemand, demand)
+      }
+      val childReason = visited.flatMap(_._2).headOption
+      val childDateOutputs = AttributeSet(visited.zipWithIndex.flatMap {
+        case ((_, _, outputs), index) if !join || 
streamedChildIndex.contains(index) => outputs
+        case _ => AttributeSet.empty
+      })
+      // Date provenance flows up through aliases while deferred evaluation 
flows down. This
+      // also finds a skipped sibling computed in a projection above the 
date's producer.
+      val dateDerivedOutputs = if (exchange || localMaterialization) {
+        AttributeSet.empty
+      } else {
+        original match {
+          case project: ProjectExec =>
+            AttributeSet(
+              project.projectList
+                .filter { output =>
+                  containsMakeDate(Seq(output)) || output.references
+                    .intersect(childDateOutputs)
+                    .nonEmpty
+                }
+                .map(_.toAttribute))
+          case _ => childDateOutputs.intersect(original.outputSet)
+        }
+      }
+      val ownReason = reason(node).orElse {
+        val rowReason = if (evaluatesDate) {
+          rowDemand.map(boundary => s"make_date requires Spark evaluation 
below $boundary")
+        } else None
+        rowReason.orElse(original match {
+          case project: ProjectExec =>
+            projectionDemand
+              .filter(demand =>
+                project.projectList.exists { output =>
+                  val computation = output match {
+                    case alias: Alias => alias.child
+                    case other => other
+                  }
+                  val deferredDate = output.deterministic &&
+                    demand.deferred.contains(output.toAttribute) && 
containsMakeDate(Seq(output))
+                  val deferredComputation = (output.deterministic || 
rowDemand.isDefined) &&
+                    (demand.guardedInputs.contains(output.toAttribute) ||
+                      (dateDerivedOutputs.nonEmpty && demand.deferred.contains(
+                        output.toAttribute))) &&
+                    !CometMakeDate.canEvaluateEagerly(computation)
+                  deferredDate || deferredComputation
+                })
+              .map(demand => s"make_date requires Spark evaluation below 
${demand.boundary}")
+          // Join keys/conditions and aggregate updates can be skipped inside 
the operator.
+          case _: BaseJoinExec | _: BaseAggregateExec | _: 
TakeOrderedAndProjectExec

Review Comment:
   [P2] Preserve native execution for eager single-argument COUNT
   
   Could an unfiltered `COUNT(make_date(y,m,d))` remain eligible for native 
aggregation when its argument is evaluated for every input row? This blanket 
aggregate fallback moves that eager update to Spark as well as the filtered or 
short-circuiting cases that need protection. A grouped two-million-row case 
previously converted all input rows instead of one result row when this guard 
was active.
   
   The reproducer and measurements are in [the parent PR 
discussion](https://github.com/apache/datafusion-comet/pull/7117#discussion_r4367129480);
 they predate this head, whose fallback path I checked in source.



##########
spark/src/main/scala/org/apache/comet/rules/MakeDateEvaluation.scala:
##########
@@ -0,0 +1,371 @@
+/*
+ * 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.comet.rules
+
+import org.apache.spark.sql.catalyst.expressions.{Add, Alias, And, Attribute, 
AttributeSet, BinaryComparison, Cast, ConditionalExpression, CreateArray, 
CreateNamedStruct, DateAdd, DateDiff, DateFormatClass, DateSub, EqualNullSafe, 
Expression, Greatest, HashExpression, IsNotNull, IsNull, Least, MakeDate, 
Multiply, Not, Or, SortOrder, Subtract, UnixDate}
+import org.apache.spark.sql.catalyst.optimizer.BuildLeft
+import org.apache.spark.sql.catalyst.trees.TreeNodeTag
+import org.apache.spark.sql.comet._
+import org.apache.spark.sql.comet.execution.shuffle.CometShuffleExchangeExec
+import org.apache.spark.sql.execution._
+import org.apache.spark.sql.execution.adaptive.{BroadcastQueryStageExec, 
QueryStageExec}
+import org.apache.spark.sql.execution.aggregate.{BaseAggregateExec, 
HashAggregateExec, ObjectHashAggregateExec}
+import org.apache.spark.sql.execution.exchange.{Exchange, ReusedExchangeExec}
+import org.apache.spark.sql.execution.joins.{BaseJoinExec, 
BroadcastHashJoinExec, BroadcastNestedLoopJoinExec}
+
+import org.apache.comet.CometConf
+import org.apache.comet.serde.CometMakeDate
+import org.apache.comet.shims.ShimCometWindowGroupLimit
+
+/** Keeps make_date on Spark's row path where native batching can change 
whether it throws. */
+private[rules] object MakeDateEvaluation {
+  private val sparkEvaluation = 
TreeNodeTag[String]("comet.makeDateSparkEvaluation")
+
+  private def enabled(plan: SparkPlan): Boolean =
+    CometConf.COMET_EXEC_MAKE_DATE_OPERATOR_FALLBACK_ENABLED.get(plan.conf)
+
+  def reason(plan: SparkPlan): Option[String] =
+    if (enabled(plan)) plan.getTagValue(sparkEvaluation) else None
+
+  private def containsMakeDate(expressions: Seq[Expression]): Boolean =
+    expressions.exists(_.exists(_.isInstanceOf[MakeDate]))
+
+  private case class ProjectionDemand(
+      boundary: String,
+      deferred: AttributeSet,
+      // Deferred inputs whose producers need guarding even when they contain 
no make_date.
+      guardedInputs: AttributeSet,
+      // Date argument lineage retained until a streamed join can skip its 
input rows.
+      dateInputs: AttributeSet)
+
+  // Attributes may stand for deferred expressions in a lower projection, not 
materialized values.
+  private def harmlessValue(expression: Expression): Boolean =
+    expression.references.isEmpty && 
CometMakeDate.canEvaluateEagerly(expression)
+
+  /** References that a consumer requires without exposing a potentially 
skipped sibling. */
+  private def eagerReferences(expression: Expression): AttributeSet = 
expression match {
+    case attribute: Attribute => AttributeSet(Seq(attribute))
+    case _ =>
+      val children = expression match {
+        case date: MakeDate =>
+          val firstNullable = date.children.indexWhere(_.nullable)
+          date.children.take(if (firstNullable < 0) date.children.size else 
firstNullable + 1)
+        case conditional: ConditionalExpression =>
+          val required = conditional.alwaysEvaluatedInputs
+          if 
(conditional.children.filterNot(required.contains).forall(harmlessValue)) 
required
+          else Nil
+        case _: Alias | _: Cast | _: IsNull | _: IsNotNull | _: Not | _: 
UnixDate =>
+          expression.children
+        case _: EqualNullSafe | _: CreateArray | _: CreateNamedStruct | _: 
Greatest | _: Least |
+            _: HashExpression[_] =>
+          expression.children
+        case _: And | _: Or =>
+          if (harmlessValue(expression.children(1))) 
expression.children.take(1) else Nil
+        case _: Add | _: Subtract | _: Multiply | _: BinaryComparison | _: 
DateAdd | _: DateSub |
+            _: DateDiff | _: DateFormatClass =>
+          val left = expression.children.head
+          val right = expression.children(1)
+          if (!left.nullable) expression.children
+          // A right-hand attribute can inline a throwing expression from an 
earlier projection.
+          // Only self-contained harmless values are safe without tracing that 
attribute's source.
+          else if (harmlessValue(right)) Seq(left)
+          else Nil
+        // Unknown expressions may skip inputs or catch errors raised by their 
children.
+        case _ => Nil
+      }
+      AttributeSet(children.flatMap(eagerReferences))
+  }
+
+  private def copyLogicalLinks(from: SparkPlan, to: SparkPlan): Unit = {
+    if (from ne to) {
+      // setLogicalLink promotes inherited links to direct links and rewrites 
descendants.
+      // Keep each tag's role and retain the fallback plan's links when the 
source has none.
+      Seq(SparkPlan.LOGICAL_PLAN_TAG, 
SparkPlan.LOGICAL_PLAN_INHERITED_TAG).foreach { tag =>
+        from.getTagValue(tag).foreach(to.setTagValue(tag, _))
+      }
+    }
+  }
+
+  private def nativeBroadcastInput(plan: SparkPlan): Option[SparkPlan] = plan 
match {
+    case _: CometBroadcastExchangeExec => Some(plan)
+    case stage: BroadcastQueryStageExec => 
nativeBroadcastInput(stage.plan).map(_ => stage)
+    case reuse: ReusedExchangeExec => nativeBroadcastInput(reuse.child).map(_ 
=> reuse)
+    case sink: CometSinkPlaceHolder => nativeBroadcastInput(sink.child)
+    case wrapper: CometScanWrapper => 
nativeBroadcastInput(wrapper.originalPlan)
+    case _ => None
+  }
+
+  private def restoreBroadcast(plan: SparkPlan, reason: String): SparkPlan =
+    nativeBroadcastInput(plan)
+      .map { input =>
+        // Spark joins need a HashedRelation (or rows for a nested-loop join), 
not Arrow buffers.
+        // The existing transition decodes the cached broadcast and applies 
its Spark broadcast
+        // mode, including through AQE/reuse wrappers, without re-executing 
the build input.
+        val restored = CometColumnarToRowExec(input)
+        restored.setTagValue(sparkEvaluation, reason)
+        copyLogicalLinks(plan, restored)
+        restored
+      }
+      .getOrElse(plan)
+
+  /**
+   * Run before bottom-up conversion and join rewriting. Reasons propagate 
back to the consuming
+   * operator, keeping the row pipeline together instead of inserting an eager 
Arrow batch between
+   * a throwing projection and its lazy consumer. Exchanges materialize their 
input independently;
+   * local sorts and aggregates do so only after their consumer requests input.
+   */
+  def preserve(plan: SparkPlan): SparkPlan = {
+    if (!enabled(plan)) return plan
+
+    def visit(
+        node: SparkPlan,
+        rowDemand: Option[String],
+        projectionDemand: Option[ProjectionDemand]): (SparkPlan, 
Option[String], AttributeSet) = {
+      node match {
+        // Materialized stages are independent producers. Their plans have 
already been guarded.
+        case _: QueryStageExec | _: ReusedExchangeExec => return (node, None, 
AttributeSet.empty)
+        // These wrappers do not have the child shape of their original Spark 
operator.
+        case wrapper: CometScanWrapper =>
+          val (child, childReason, dateOutputs) =
+            visit(wrapper.originalPlan, rowDemand, projectionDemand)
+          return if (childReason.isDefined) (child, childReason, dateOutputs)
+          else (wrapper.copy(originalPlan = child), None, dateOutputs)
+        case sink: CometSinkPlaceHolder =>
+          val (child, childReason, dateOutputs) = visit(sink.child, rowDemand, 
projectionDemand)
+          return if (childReason.isDefined) (child, childReason, dateOutputs)
+          else (sink.withNewChildren(Seq(child)), None, dateOutputs)
+        case _ =>
+      }
+
+      val original = node match {
+        case scan: CometScanExec =>
+          scan.wrapped.copy(
+            partitionFilters = scan.partitionFilters,
+            dataFilters = scan.dataFilters)
+        case scan: CometNativeScanExec => scan.sparkFallback(Nil)
+        case native: CometExec => native.originalPlan
+        case shuffle: CometShuffleExchangeExec => shuffle.originalPlan
+        case broadcast: CometBroadcastExchangeExec => broadcast.originalPlan
+        case _ => node
+      }
+      val evaluatesDate = containsMakeDate(original.expressions)
+      val exchange = original.isInstanceOf[Exchange]
+      val join = original.isInstanceOf[BaseJoinExec]
+      // Broadcast joins can inline streamed expressions into their consumer. 
Their build side
+      // materializes rows; shuffled hash and sort-merge joins also isolate 
the streamed input.
+      val streamedChildIndex = original match {
+        case hash: BroadcastHashJoinExec if hash.supportCodegen =>
+          Some(if (hash.buildSide == BuildLeft) 1 else 0)
+        case nestedLoop: BroadcastNestedLoopJoinExec if 
nestedLoop.supportCodegen =>
+          Some(if (nestedLoop.buildSide == BuildLeft) 1 else 0)
+        case _ => None
+      }
+      val localMaterialization = original match {
+        case _: SortExec | _: HashAggregateExec | _: ObjectHashAggregateExec 
=> true
+        case _: TakeOrderedAndProjectExec => true
+        case _ => false
+      }
+      val startsLimit = original match {
+        case _: CollectLimitExec | _: LocalLimitExec | _: GlobalLimitExec => 
true
+        case topK: TakeOrderedAndProjectExec =>
+          SortOrder.orderingSatisfies(topK.child.outputOrdering, 
topK.sortOrder)
+        case _
+            if 
ShimCometWindowGroupLimit.windowGroupLimitClass.exists(_.isInstance(original)) 
=>
+          true
+        case _ => false
+      }
+      val childDemand = original match {
+        case _ if exchange => None
+        // A join can leave a local sort or aggregate completely unpolled.
+        case _ if join || rowDemand.contains("JOIN") => Some("JOIN")
+        case _ if startsLimit => Some("LIMIT")
+        case _: SampleExec => Some("SAMPLE")
+        case _: MapPartitionsExec => Some("a mapPartitions function")
+        case _ if localMaterialization => None
+        case _ => rowDemand
+      }
+      val childProjectionDemand = original match {
+        // Generated filters can defer deterministic projection outputs until 
a row is accepted.
+        case filter: FilterExec =>
+          Some(
+            ProjectionDemand(
+              "FILTER",
+              filter.child.outputSet,
+              
projectionDemand.map(_.guardedInputs).getOrElse(AttributeSet.empty),
+              
projectionDemand.map(_.dateInputs).getOrElse(AttributeSet.empty)))
+        case project: ProjectExec =>
+          val deferred = 
projectionDemand.map(_.deferred).getOrElse(AttributeSet.empty)
+          val eager = project.projectList
+            .filter(output => !output.deterministic || 
!deferred.contains(output.toAttribute))
+            .flatMap(eagerReferences)
+          // ProjectExec forces repeated inputs and nondeterministic outputs. 
Other inputs can
+          // remain inlined in a consumer's conditional, even across 
intervening aliases.
+          val skipped = project.child.outputSet -- project.usedInputs -- 
AttributeSet(eager)
+          val inheritedInputs =
+            projectionDemand.map(_.guardedInputs).getOrElse(AttributeSet.empty)
+          // A consumer can require the date but still skip another output of 
this projection.
+          val guardedOutputs = inheritedInputs ++
+            (if (evaluatesDate) deferred else AttributeSet.empty)
+          val directDateInputs = AttributeSet(project.projectList.flatMap { 
output =>
+            output.collect { case date: MakeDate => date 
}.flatMap(_.references)
+          })
+          val inputsToGuard =
+            directDateInputs ++ AttributeSet(project.projectList.flatMap { 
output =>
+              if ((output.deterministic || rowDemand.isDefined) &&
+                guardedOutputs.contains(output.toAttribute)) {
+                output.references.toSeq
+              } else {
+                Nil
+              }
+            })
+          // Keep argument lineage through eager aliases too. A join below 
this projection can
+          // discard an input row before this projection ever requires the 
argument's value.
+          val dateInputs =
+            directDateInputs ++ AttributeSet(project.projectList.flatMap { 
output =>
+              if 
(projectionDemand.exists(_.dateInputs.contains(output.toAttribute))) {
+                output.references.toSeq
+              } else {
+                Nil
+              }
+            })
+          // A lazy row consumer can skip even the date's required arguments 
on unread rows.
+          val guardedChildInputs =
+            inputsToGuard.intersect(if (rowDemand.isDefined) 
project.child.outputSet else skipped)
+          if (skipped.isEmpty && guardedChildInputs.isEmpty && 
dateInputs.isEmpty) {
+            None
+          } else {
+            Some(
+              ProjectionDemand(
+                projectionDemand.map(_.boundary).getOrElse("PROJECT"),
+                skipped,
+                guardedChildInputs,
+                dateInputs))
+          }
+        case _ if exchange || localMaterialization => None
+        case _ => projectionDemand
+      }
+      val visited = node.children.zipWithIndex.map { case (child, index) =>
+        val demand = if (!join) {
+          childProjectionDemand
+        } else if (streamedChildIndex.contains(index)) {
+          childProjectionDemand.map { demand =>
+            // Keys and conditions force their inputs on each visited row. An 
outer row consumer
+            // can still skip that row altogether, so retain its guarded 
inputs in that case.
+            val required = if (rowDemand.isDefined) AttributeSet.empty else 
original.references
+            val streamedOutputs = original.children(index).outputSet
+            val forwarded = streamedOutputs -- required
+            demand.copy(
+              deferred = demand.deferred.intersect(forwarded),
+              guardedInputs = (demand.guardedInputs ++ 
demand.dateInputs).intersect(forwarded),
+              // A key is required only on this join's input rows. An earlier 
join can still
+              // discard rows before producing that key, so retain its 
argument lineage.
+              dateInputs = demand.dateInputs.intersect(streamedOutputs))
+          }
+        } else {
+          None
+        }
+        visit(child, childDemand, demand)
+      }
+      val childReason = visited.flatMap(_._2).headOption
+      val childDateOutputs = AttributeSet(visited.zipWithIndex.flatMap {
+        case ((_, _, outputs), index) if !join || 
streamedChildIndex.contains(index) => outputs
+        case _ => AttributeSet.empty
+      })
+      // Date provenance flows up through aliases while deferred evaluation 
flows down. This
+      // also finds a skipped sibling computed in a projection above the 
date's producer.
+      val dateDerivedOutputs = if (exchange || localMaterialization) {
+        AttributeSet.empty
+      } else {
+        original match {
+          case project: ProjectExec =>
+            AttributeSet(
+              project.projectList
+                .filter { output =>
+                  containsMakeDate(Seq(output)) || output.references
+                    .intersect(childDateOutputs)
+                    .nonEmpty
+                }
+                .map(_.toAttribute))
+          case _ => childDateOutputs.intersect(original.outputSet)
+        }
+      }
+      val ownReason = reason(node).orElse {
+        val rowReason = if (evaluatesDate) {

Review Comment:
   [P2] Clear the outer limit's demand at the shuffle itself
   
   Could the exchange's partitioning expressions be treated as materialized 
along with its child? With `df.repartition(8, 
expr("make_date(y,m,d)")).limit(10).collect()`, Spark must evaluate the 
partition key for every shuffle input before the limit can consume output. The 
child demand is cleared at the exchange, but this `rowDemand` check still 
forces the exchange to Spark, losing native hash shuffle without avoiding 
evaluation of a date that Spark would skip.
   
   The same case was reproduced and measured on the split parent in [this 
discussion](https://github.com/apache/datafusion-comet/pull/7117#discussion_r4367129475).
 I traced the corresponding path on this head but did not rerun that benchmark 
here.



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