`CometBenchmarkBase.runExpressionBenchmark` checks the initial AQE plan, not the executed plan

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Valutazione

Difficoltà
4/5
Tempo stimato
3-5 giorni
Idoneità per principianti
55/100
Tipo di issue
Bug
Chiarezza
Specificata chiaramente
Stato di attività
Attiva
Stack tecnologico
scala, spark
Ambito
performance, testing

Direzione di ricerca

Read spark/src/test/scala/org/apache/spark/sql/benchmark/CometBenchmarkBase.scala and spark/src/test/scala/org/apache/spark/sql/comet/CometPlanChecker.scala. Start by checking how the benchmark executes its DataFrame and how the plan checker traverses AQE query stages. Done means the check inspects the final executed plan, recognizes the AQE wrapper nodes, and reports any non-native operator in that plan.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

bug priority:low
Describe the bug

Before timing a case, runExpressionBenchmark in
spark/src/test/scala/org/apache/spark/sql/benchmark/CometBenchmarkBase.scala checks that the
Comet plan is fully native:

// Check that the plan is fully Comet native before running the benchmark. Unlike the check
// above this one does execute the query, because AQE can re-plan a join after the first
// stage completes and the Comet operators are what we are checking for.
withSQLConf(cometConfigs: _*) {
  val df = spark.sql(query)
  df.noop()
  val plan = stripAQEPlan(df.queryExecution.executedPlan)
  findFirstNonCometOperator(plan).foreach { op => ...

df.noop() runs a separate write query. It does not execute df's own plan. After it,
df.queryExecution.executedPlan is still AdaptiveSparkPlan isFinalPlan=false, and
stripAQEPlan returns the initial plan. The check therefore never sees what AQE changes during
execution, which is what the comment says it is checking for. The warning it prints shows the
initial plan, not the plan that ran.

Steps to reproduce

Run on main (0f7f8e453) with the default profile (Spark 4.1.3), in a CometBenchmarkBase
subclass, over a Parquet table of 4096 rows made with
spark.range(4096).selectExpr("id % 10 AS k", "id AS v"), with
spark.comet.exec.shuffle.enabled=false. The query is SELECT k, sum(v) FROM t GROUP BY k.

  1. With the three lines above, after df.noop(), df.queryExecution.executedPlan is
    AdaptiveSparkPlan isFinalPlan=false. The plan that the check reads, and that the warning
    prints, is
    HashAggregate > Exchange > CometHashAggregate > CometNativeScan.
    It has no CometColumnarToRow, AQEShuffleRead or ShuffleQueryStage.
  2. For a second DataFrame of the same query, after collect(),
    executedPlan is AdaptiveSparkPlan isFinalPlan=true, and the plan is
    ResultQueryStage > HashAggregate > AQEShuffleRead coalesced > ShuffleQueryStage >
    Exchange > CometColumnarToRow > CometHashAggregate > CometNativeScan.
Expected behavior

The check reads the plan that ran, after AQE has finished, and the warning prints that plan.

Additional context

Executing the DataFrame's own plan, for example with
df.queryExecution.executedPlan.execute().foreach(_ => ()), makes the plan final. The final plan
contains query stages. findFirstNonCometOperator in
spark/src/test/scala/org/apache/spark/sql/comet/CometPlanChecker.scala walks the plan with
foreach, which does not descend into a QueryStageExec (a leaf node), and its allow-list
contains neither QueryStageExec nor AQEShuffleReadExec. So a fix also needs the walk to go
into the query stages, for example through AdaptiveSparkPlanHelper, and to allow the AQE
wrapper nodes.

🤖 Generated with Claude Code

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