sunchao commented on code in PR #5423:
URL: https://github.com/apache/datafusion-comet/pull/5423#discussion_r3846536589
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spark/src/main/scala/org/apache/spark/sql/comet/CometMetricNode.scala:
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@@ -61,6 +61,17 @@ case class CometMetricNode(metrics: Map[String, SQLMetric],
children: Seq[CometM
else children.flatMap(_.leafNodes)
}
+ private[comet] def withoutAggregateMetrics(plan: SparkPlan): CometMetricNode
=
Review Comment:
Good point. Range partitioning executes the native child once to sample
partition boundaries and then again for the real shuffle. If aggregate metrics
are updated in both passes, spill count, spilled bytes/rows, and peak native
memory are counted twice. The sampling pass therefore suppresses only aggregate
metrics; scan/input and other operator metrics remain intact, and the real
shuffle execution reports aggregate metrics normally. This is why the filtering
helper needs an explanatory comment.
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