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[SPARK-26003][SQL][2.4] Improve SQLAppStatusListener.aggregateMetrics performance #25860

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[SPARK-26003][SQL][2.4] Improve SQLAppStatusListener.aggregateMetrics performance #25860

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5 changes: 2 additions & 3 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListener.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -181,18 +181,17 @@ class SQLAppStatusListener(
}

private def aggregateMetrics(exec: LiveExecutionData): Map[Long, String] = {
val metricIds = exec.metrics.map(_.accumulatorId).sorted
val metricTypes = exec.metrics.map { m => (m.accumulatorId, m.metricType) }.toMap
val metrics = exec.stages.toSeq
.flatMap { stageId => Option(stageMetrics.get(stageId)) }
.flatMap(_.taskMetrics.values().asScala)
.flatMap { metrics => metrics.ids.zip(metrics.values) }

val aggregatedMetrics = (metrics ++ exec.driverAccumUpdates.toSeq)
.filter { case (id, _) => metricIds.contains(id) }
.filter { case (id, _) => metricTypes.contains(id) }
.groupBy(_._1)
.map { case (id, values) =>
id -> SQLMetrics.stringValue(metricTypes(id), values.map(_._2).toSeq)
id -> SQLMetrics.stringValue(metricTypes(id), values.map(_._2))
}

// Check the execution again for whether the aggregated metrics data has been calculated.
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