viirya commented on code in PR #6883:
URL: https://github.com/apache/datafusion-comet/pull/6883#discussion_r4316487044


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spark-local/src/main/scala/org/apache/comet/local/CometLocalResultExec.scala:
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@@ -0,0 +1,134 @@
+/*
+ * 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.local
+
+import java.util.concurrent.ConcurrentHashMap
+import java.util.concurrent.atomic.AtomicLong
+
+import scala.collection.mutable.ArrayBuffer
+
+import org.apache.spark.SparkException
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.{Attribute, SortOrder, 
UnsafeRow}
+import org.apache.spark.sql.catalyst.plans.physical.Partitioning
+import org.apache.spark.sql.execution.{ColumnarToRowExec, SparkPlan, 
UnaryExecNode}
+
+/**
+ * Row result boundary of a local query. Spark's collect encodes and 
compresses every row of a
+ * result partition in its task, then decodes them on the driver. A local 
query has one result
+ * partition, so that work would run on a single thread. Admission requires an 
in-process local
+ * master, so collect and take still run one Spark task (keeping cancellation, 
job groups and SQL
+ * metrics) but hand copied rows to the driver in this JVM.
+ */
+case class CometLocalResultExec(child: SparkPlan) extends UnaryExecNode {
+  override def output: Seq[Attribute] = child.output
+  override def outputPartitioning: Partitioning = child.outputPartitioning
+  override def outputOrdering: Seq[SortOrder] = child.outputOrdering
+
+  override protected def doExecute(): RDD[InternalRow] = child.execute()
+
+  override def executeCollect(): Array[InternalRow] =
+    if (sparkContext.isLocal) LocalResultHandoff.collect(execute(), -1, 
maxResultSize)
+    else super.executeCollect()
+
+  override def executeTake(n: Int): Array[InternalRow] =
+    if (n <= 0) Array.empty
+    else if (sparkContext.isLocal) LocalResultHandoff.collect(execute(), n, 
maxResultSize)
+    else super.executeTake(n)
+
+  /**
+   * Runs the query as ordinary Comet execution instead. An iterator fetches 
one result partition
+   * at a time to bound what it holds, and a local query has a single 
partition holding the whole
+   * result, so the native block runs as Spark tasks, one per partition, as 
without local
+   * execution.
+   */
+  override def executeToIterator(): Iterator[InternalRow] =

Review Comment:
   Thanks, confirmed: `tailToPython` calls `executeTail`, which scans 
partitions from the last one, and the single local partition made it evaluate 
the whole query. `CometLocalResultExec.executeTail` now runs the admitted 
native block as ordinary Comet execution, as `executeToIterator` does 
(b82f38783). Your ANSI example is now a test that compares `executeTail` with 
Spark.
   
   I also went through the other entry points that read a result partition by 
partition: `executeCollect` and `executeTake`, including `Dataset.isEmpty`, use 
the result handoff; `executeToIterator` covers `toLocalIterator`, the Thrift 
server's incremental collect and SQL cursors; and Scala's `tail` plans a 
`CollectTailExec`, which is not admitted.
   



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