chore: Add checks to microbenchmarks for plan running natively in Comet

spark/src/test/scala/org/apache/spark/sql/benchmark/CometBenchmarkBase.scala

@@ -31,14 +31,18 @@ import org.apache.parquet.crypto.keytools.mocks.InMemoryKMS
 import org.apache.spark.SparkConf
 import org.apache.spark.benchmark.Benchmark
 import org.apache.spark.sql.{DataFrame, DataFrameWriter, Row, SparkSession}
+import org.apache.spark.sql.comet._
+import org.apache.spark.sql.comet.execution.shuffle.CometShuffleExchangeExec
+import org.apache.spark.sql.execution.{ColumnarToRowExec, InputAdapter, SparkPlan, WholeStageCodegenExec}
+import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper
 import org.apache.spark.sql.execution.benchmark.SqlBasedBenchmark
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.types.DecimalType
 
 import org.apache.comet.CometConf
 import org.apache.comet.CometSparkSessionExtensions
 
-trait CometBenchmarkBase extends SqlBasedBenchmark {
+trait CometBenchmarkBase extends SqlBasedBenchmark with AdaptiveSparkPlanHelper {
   override def getSparkSession: SparkSession = {
     val conf = new SparkConf()
       .setAppName("CometReadBenchmark")
@@ -88,28 +92,6 @@ trait CometBenchmarkBase extends SqlBasedBenchmark {
     }
   }
 
-  /** Runs function `f` with Comet on and off. */
-  final def runWithComet(name: String, cardinality: Long)(f: => Unit): Unit = {
-    val benchmark = new Benchmark(name, cardinality, output = output)
-
-    benchmark.addCase(s"$name - Spark ") { _ =>
-      withSQLConf(CometConf.COMET_ENABLED.key -> "false") {
-        f
-      }
-    }
-
-    benchmark.addCase(s"$name - Comet") { _ =>
-      withSQLConf(
-        CometConf.COMET_ENABLED.key -> "true",
-        CometConf.COMET_EXEC_ENABLED.key -> "true",
-        SQLConf.ANSI_ENABLED.key -> "false") {
-        f
-      }
-    }
-
-    benchmark.run()
-  }
-
   /**
    * Runs an expression benchmark with standard cases: Spark, Comet (Scan), Comet (Scan + Exec).
    * This provides a consistent benchmark structure for expression evaluation.
@@ -149,6 +131,29 @@ trait CometBenchmarkBase extends SqlBasedBenchmark {
       CometConf.COMET_EXEC_ENABLED.key -> "true",
       "spark.sql.optimizer.constantFolding.enabled" -> "false") ++ extraCometConfigs
 
+    // Check that the plan is fully Comet native before running the benchmark
+    withSQLConf(cometExecConfigs.toSeq: _*) {
+      val df = spark.sql(query)
+      df.noop()
+      val plan = stripAQEPlan(df.queryExecution.executedPlan)
+      findFirstNonCometOperator(plan) match {
+        case Some(op) =>
+          // scalastyle:off println
+          println()
+          println("=" * 80)
+          println("WARNING: Benchmark plan is NOT fully Comet native!")
+          println(s"First non-Comet operator: ${op.nodeName}")
+          println("=" * 80)
+          println("Query plan:")
+          println(plan.treeString)
+          println("=" * 80)
+          println()
+        // scalastyle:on println
+        case None =>
+        // All operators are Comet native, no warning needed
+      }
+    }
+
     benchmark.addCase("Comet (Scan + Exec)") { _ =>
       withSQLConf(cometExecConfigs.toSeq: _*) {
         spark.sql(query).noop()
@@ -158,6 +163,28 @@ trait CometBenchmarkBase extends SqlBasedBenchmark {
     benchmark.run()
   }
 
+  /**
+   * Finds the first non-Comet operator in the plan, if any. This is used to verify that
+   * benchmarks are running fully on Comet native when expected.
+   *
+   * Based on CometTestBase.findFirstNonCometOperator.
+   */
+  protected def findFirstNonCometOperator(plan: SparkPlan): Option[SparkPlan] = {
+    plan.foreach {
+      case _: CometNativeScanExec | _: CometScanExec | _: CometBatchScanExec |
+          _: CometIcebergNativeScanExec =>
+      case _: CometSinkPlaceHolder | _: CometScanWrapper =>
+      case _: CometColumnarToRowExec =>
+      case _: CometSparkToColumnarExec =>
+      case _: CometExec | _: CometShuffleExchangeExec =>
+      case _: CometBroadcastExchangeExec =>
+      case _: WholeStageCodegenExec | _: ColumnarToRowExec | _: InputAdapter =>
+      case op =>
+        return Some(op)
+    }
+    None
+  }
+
   protected def prepareTable(dir: File, df: DataFrame, partition: Option[String] = None): Unit = {
     val testDf = if (partition.isDefined) {
       df.write.partitionBy(partition.get)