[SPARK-26003] Improve SQLAppStatusListener.aggregateMetrics performance

## What changes were proposed in this pull request?

In `SQLAppStatusListener.aggregateMetrics`, we use the `metricIds` only to filter the relevant metrics. And this is a Seq which is also sorted. When there are many metrics involved, this can be pretty inefficient. The PR proposes to use a Set for it.

## How was this patch tested?

NA

Closes #23002 from mgaido91/SPARK-26003.

Authored-by: Marco Gaido <[email protected]>
Signed-off-by: Wenchen Fan <[email protected]>

Author: mgaido91

sql/core/src/main/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListener.scala

@@ -159,18 +159,17 @@ 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.