cloud-fan commented on code in PR #57346:
URL: https://github.com/apache/spark/pull/57346#discussion_r3766860109


##########
sql/core/src/main/scala/org/apache/spark/sql/execution/window/SlidingWindowMinMaxFunctionFrame.scala:
##########
@@ -0,0 +1,280 @@
+/*
+ * 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.window
+
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.expressions.aggregate._
+import org.apache.spark.sql.catalyst.util.TypeUtils
+import org.apache.spark.sql.execution.ExternalAppendOnlyUnsafeRowArray
+import org.apache.spark.sql.execution.metric.SQLMetric
+import org.apache.spark.sql.types._
+
+/**
+ * An optimized sliding window frame that calculates min and/or max aggregate 
functions using
+ * monotonic deques. This provides O(N) time complexity instead of O(N * W) of
+ * [[SlidingWindowFunctionFrame]] or O(N log W) of 
[[SegmentTreeWindowFunctionFrame]].
+ *
+ * This frame is only instantiated when `isMinMaxOnly` is true (all window 
functions are Min or
+ * Max and no FILTER clause is used), enforced upstream in 
[[WindowEvaluatorFactoryBase]].
+ */
+private[window] final class SlidingWindowMinMaxFunctionFrame(
+    target: InternalRow,
+    processor: AggregateProcessor,
+    lbound: BoundOrdering,
+    ubound: BoundOrdering,
+    functions: Array[Expression],
+    inputSchema: Seq[Attribute],
+    numMonotonicDequeFrames: Option[SQLMetric] = None)
+    extends WindowFunctionFrame {
+
+  /** Rows of the partition currently being processed. */
+  private[this] var input: ExternalAppendOnlyUnsafeRowArray = null
+
+  // Spill-safety: when `input` (ExternalAppendOnlyUnsafeRowArray) spills, its
+  // iterator reuses a single UnsafeRow whose pointer is rebound on each 
next().
+  // This is safe because both cursors follow a read-before-advance pattern:
+  // `lowerRow`/`nextRow` are used for comparison *before* calling 
getNextOrNull.
+  // Values are extracted from the row via `evaluateAndCopy` before advancing.
+  // DO NOT cache a historical row without an explicit .copy(); the shared
+  // reusable UnsafeRow would silently mutate.
+  private[this] var lowerIterator: Iterator[UnsafeRow] = _
+  private[this] var inputIterator: Iterator[UnsafeRow] = _
+
+  /** The row at lowerBound. */
+  private[this] var lowerRow: UnsafeRow = null
+
+  /** The next row from `input`. */
+  private[this] var nextRow: InternalRow = null
+
+  /**
+   * Index of the first input row with a value equal to or greater than the 
lower bound of the
+   * current output row.
+   */
+  private[this] var lowerBound = 0
+
+  /**
+   * Index of the first input row with a value greater than the upper bound of 
the current output
+   * row.
+   */
+  private[this] var upperBound = 0
+
+  // `sourceRow` is used as the `source` argument to 
`processor.evaluate(source, target)`.
+  // Layout compatibility is guaranteed because Min/Max each contribute 
exactly one
+  // `aggBufferAttributes` entry typed `child.dataType`, which equals 
`Min/Max.dataType`.
+  // Neither is a `SizeBasedWindowFunction`, so no extra slot is prepended.
+  // `isMinMaxOnly` (enforced in WindowEvaluatorFactoryBase) ensures this 
invariant holds.
+  private[this] val sourceRow = new 
SpecificInternalRow(functions.map(_.dataType).toIndexedSeq)
+
+  // Each deque is addressed by its position in this array (one entry per 
Min/Max function),

Review Comment:
   **Nit:**
   
   This comment is now history-dependent: `bufferIndex` and its `zipWithIndex` 
producer have been removed, and the positional access is evident from the 
array. Please remove the stale comment as well.



##########
sql/core/src/test/scala/org/apache/spark/sql/execution/window/WindowSegmentTreeAllowlistSuite.scala:
##########
@@ -30,22 +30,26 @@ import org.apache.spark.sql.test.SharedSparkSession
  * Coverage for the explicit segment-tree aggregate allowlist
  * ([[WindowSegmentTree.EligibleAggregates]]):
  *   - allowlisted aggregates route to segtree (`numSegmentTreeFrames` bumps).
- *   - non-allowlisted aggregates fall through to the sliding path without
- *     crashing or producing wrong results (segtree counters stay at 0).
- * Eligibility gating only; exhaustive equivalence lives in
- * [[SegmentTreeWindowFunctionSuite]].
+ *   - non-allowlisted aggregates fall through to the sliding path without 
crashing or producing

Review Comment:
   **Non-blocking:**
   
   This suite claims that non-allowlisted aggregates fall through without 
producing wrong results, but each negative test only collects the query and 
checks that the segment-tree metric is zero. That proves routing and absence of 
a crash, not correctness. Please compare the returned rows with expected values 
or with the same query under the optimization disabled for the enumerated 
negative cases.



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