[SPARK-31253][SQL] Add metrics to AQE shuffle reader

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### What changes were proposed in this pull request?
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Add SQL metrics to the AQE shuffle reader (`CustomShuffleReaderExec`)

### Why are the changes needed?
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to be more UI friendly

### Does this PR introduce any user-facing change?
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No

### How was this patch tested?
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new test

Closes #28022 from cloud-fan/metrics.

Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>

sql/core/src/main/scala/org/apache/spark/sql/execution/ShuffledRowRDD.scala

@@ -31,17 +31,23 @@ sealed trait ShufflePartitionSpec
 // A partition that reads data of one or more reducers, from `startReducerIndex` (inclusive) to
 // `endReducerIndex` (exclusive).
 case class CoalescedPartitionSpec(
-  startReducerIndex: Int, endReducerIndex: Int) extends ShufflePartitionSpec
+    startReducerIndex: Int,
+    endReducerIndex: Int) extends ShufflePartitionSpec
 
 // A partition that reads partial data of one reducer, from `startMapIndex` (inclusive) to
 // `endMapIndex` (exclusive).
 case class PartialReducerPartitionSpec(
-  reducerIndex: Int, startMapIndex: Int, endMapIndex: Int) extends ShufflePartitionSpec
+    reducerIndex: Int,
+    startMapIndex: Int,
+    endMapIndex: Int,
+    @transient dataSize: Long) extends ShufflePartitionSpec
 
 // A partition that reads partial data of one mapper, from `startReducerIndex` (inclusive) to
 // `endReducerIndex` (exclusive).
 case class PartialMapperPartitionSpec(
-  mapIndex: Int, startReducerIndex: Int, endReducerIndex: Int) extends ShufflePartitionSpec
+    mapIndex: Int,
+    startReducerIndex: Int,
+    endReducerIndex: Int) extends ShufflePartitionSpec
 
 /**
  * The [[Partition]] used by [[ShuffledRowRDD]].
@@ -162,7 +168,7 @@ class ShuffledRowRDD(
           tracker.getPreferredLocationsForShuffle(dependency, reducerIndex)
         }
 
-      case PartialReducerPartitionSpec(_, startMapIndex, endMapIndex) =>
+      case PartialReducerPartitionSpec(_, startMapIndex, endMapIndex, _) =>
         tracker.getMapLocation(dependency, startMapIndex, endMapIndex)
 
       case PartialMapperPartitionSpec(mapIndex, _, _) =>
@@ -184,7 +190,7 @@ class ShuffledRowRDD(
           context,
           sqlMetricsReporter)
 
-      case PartialReducerPartitionSpec(reducerIndex, startMapIndex, endMapIndex) =>
+      case PartialReducerPartitionSpec(reducerIndex, startMapIndex, endMapIndex, _) =>
         SparkEnv.get.shuffleManager.getReaderForRange(
           dependency.shuffleHandle,
           startMapIndex,

sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/CoalesceShufflePartitions.scala

@@ -83,7 +83,7 @@ case class CoalesceShufflePartitions(session: SparkSession) extends Rule[SparkPl
           // `partitionStartIndices`, so that all the leaf shuffles in a stage have the same
           // number of output partitions.
           case stage: ShuffleQueryStageExec if stageIds.contains(stage.id) =>
-            CustomShuffleReaderExec(stage, partitionSpecs, COALESCED_SHUFFLE_READER_DESCRIPTION)
+            CustomShuffleReaderExec(stage, partitionSpecs)
         }
       } else {
         plan
@@ -91,7 +91,3 @@ case class CoalesceShufflePartitions(session: SparkSession) extends Rule[SparkPl
     }
   }
 }
-
-object CoalesceShufflePartitions {
-  val COALESCED_SHUFFLE_READER_DESCRIPTION = "coalesced"
-}

sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/CustomShuffleReaderExec.scala

@@ -23,6 +23,7 @@ import org.apache.spark.sql.catalyst.expressions.{Attribute, Expression}
 import org.apache.spark.sql.catalyst.plans.physical.{Partitioning, UnknownPartitioning}
 import org.apache.spark.sql.execution._
 import org.apache.spark.sql.execution.exchange.{ReusedExchangeExec, ShuffleExchangeExec}
+import org.apache.spark.sql.execution.metric.{SQLMetric, SQLMetrics}
 
 
 /**
@@ -31,12 +32,10 @@ import org.apache.spark.sql.execution.exchange.{ReusedExchangeExec, ShuffleExcha
  * @param child           It is usually `ShuffleQueryStageExec`, but can be the shuffle exchange
  *                        node during canonicalization.
  * @param partitionSpecs  The partition specs that defines the arrangement.
- * @param description     The string description of this shuffle reader.
  */
 case class CustomShuffleReaderExec private(
     child: SparkPlan,
-    partitionSpecs: Seq[ShufflePartitionSpec],
+    partitionSpecs: Seq[ShufflePartitionSpec]) extends UnaryExecNode {
-    description: String) extends UnaryExecNode {
 
   override def output: Seq[Attribute] = child.output
   override lazy val outputPartitioning: Partitioning = {
@@ -62,20 +61,109 @@ case class CustomShuffleReaderExec private(
     }
   }
 
-  override def stringArgs: Iterator[Any] = Iterator(description)
+  override def stringArgs: Iterator[Any] = {
+    val desc = if (isLocalReader) {
+      "local"
+    } else if (hasCoalescedPartition && hasSkewedPartition) {
+      "coalesced and skewed"
+    } else if (hasCoalescedPartition) {
+      "coalesced"
+    } else if (hasSkewedPartition) {
+      "skewed"
+    } else {
+      ""
+    }
+    Iterator(desc)
+  }
 
-  private var cachedShuffleRDD: RDD[InternalRow] = null
+  def hasCoalescedPartition: Boolean = {
+    partitionSpecs.exists(_.isInstanceOf[CoalescedPartitionSpec])
+  }
+
+  def hasSkewedPartition: Boolean = {
+    partitionSpecs.exists(_.isInstanceOf[PartialReducerPartitionSpec])
+  }
+
+  def isLocalReader: Boolean = {
+    if (partitionSpecs.exists(_.isInstanceOf[PartialMapperPartitionSpec])) {
+      assert(partitionSpecs.forall(_.isInstanceOf[PartialMapperPartitionSpec]))
+      true
+    } else {
+      false
+    }
+  }
+
+  private def shuffleStage = child match {
+    case stage: ShuffleQueryStageExec => Some(stage)
+    case _ => None
+  }
+
+  private lazy val partitionDataSizeMetrics = {
+    val maxSize = SQLMetrics.createSizeMetric(sparkContext, "maximum partition data size")
+    val minSize = SQLMetrics.createSizeMetric(sparkContext, "minimum partition data size")
+    val avgSize = SQLMetrics.createSizeMetric(sparkContext, "average partition data size")
+    val mapStats = shuffleStage.get.mapStats.bytesByPartitionId
+    val sizes = partitionSpecs.map {
+      case CoalescedPartitionSpec(startReducerIndex, endReducerIndex) =>
+        startReducerIndex.until(endReducerIndex).map(mapStats(_)).sum
+      case p: PartialReducerPartitionSpec => p.dataSize
+      case p => throw new IllegalStateException("unexpected " + p)
+    }
+    maxSize.set(sizes.max)
+    minSize.set(sizes.min)
+    avgSize.set(sizes.sum / sizes.length)
+    Map(
+      "maxPartitionDataSize" -> maxSize,
+      "minPartitionDataSize" -> minSize,
+      "avgPartitionDataSize" -> avgSize)
+  }
+
+  private lazy val skewedPartitionMetrics = {
+    val metrics = SQLMetrics.createMetric(sparkContext, "number of skewed partitions")
+    val numSkewedPartitions = partitionSpecs.collect {
+      case p: PartialReducerPartitionSpec => p.reducerIndex
+    }.distinct.length
+    metrics.set(numSkewedPartitions)
+    Map("numSkewedPartitions" -> metrics)
+  }
+
+  override lazy val metrics: Map[String, SQLMetric] = {
+    if (shuffleStage.isDefined) {
+      val numPartitions = SQLMetrics.createMetric(sparkContext, "number of partitions")
+      numPartitions.set(partitionSpecs.length)
+      Map("numPartitions" -> numPartitions) ++ {
+        if (isLocalReader) {
+          // We split the mapper partition evenly when creating local shuffle reader, so no
+          // data size info is available.
+          Map.empty
+        } else {
+          partitionDataSizeMetrics
+        }
+      } ++ {
+        if (hasSkewedPartition) {
+          skewedPartitionMetrics
+        } else {
+          Map.empty
+        }
+      }
+    } else {
+      // It's a canonicalized plan, no need to report metrics.
+      Map.empty
+    }
+  }
+
+  private lazy val cachedShuffleRDD: RDD[InternalRow] = {
+    val executionId = sparkContext.getLocalProperty(SQLExecution.EXECUTION_ID_KEY)
+    SQLMetrics.postDriverMetricUpdates(sparkContext, executionId, metrics.values.toSeq)
+    shuffleStage.map { stage =>
+      new ShuffledRowRDD(
+        stage.shuffle.shuffleDependency, stage.shuffle.readMetrics, partitionSpecs.toArray)
+    }.getOrElse {
+      throw new IllegalStateException("operating on canonicalized plan")
+    }
+  }
 
   override protected def doExecute(): RDD[InternalRow] = {
-    if (cachedShuffleRDD == null) {
-      cachedShuffleRDD = child match {
-        case stage: ShuffleQueryStageExec =>
-          new ShuffledRowRDD(
-            stage.shuffle.shuffleDependency, stage.shuffle.readMetrics, partitionSpecs.toArray)
-        case _ =>
-          throw new IllegalStateException("operating on canonicalization plan")
-      }
-    }
     cachedShuffleRDD
   }
 }

sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/OptimizeLocalShuffleReader.scala

@@ -65,11 +65,10 @@ case class OptimizeLocalShuffleReader(conf: SQLConf) extends Rule[SparkPlan] {
 
   private def createLocalReader(plan: SparkPlan): CustomShuffleReaderExec = {
     plan match {
-      case c @ CustomShuffleReaderExec(s: ShuffleQueryStageExec, _, _) =>
+      case c @ CustomShuffleReaderExec(s: ShuffleQueryStageExec, _) =>
-        CustomShuffleReaderExec(
+        CustomShuffleReaderExec(s, getPartitionSpecs(s, Some(c.partitionSpecs.length)))
-          s, getPartitionSpecs(s, Some(c.partitionSpecs.length)), LOCAL_SHUFFLE_READER_DESCRIPTION)
       case s: ShuffleQueryStageExec =>
-        CustomShuffleReaderExec(s, getPartitionSpecs(s, None), LOCAL_SHUFFLE_READER_DESCRIPTION)
+        CustomShuffleReaderExec(s, getPartitionSpecs(s, None))
     }
   }
 
@@ -123,8 +122,6 @@ case class OptimizeLocalShuffleReader(conf: SQLConf) extends Rule[SparkPlan] {
 
 object OptimizeLocalShuffleReader {
 
-  val LOCAL_SHUFFLE_READER_DESCRIPTION: String = "local"
-
   object BroadcastJoinWithShuffleLeft {
     def unapply(plan: SparkPlan): Option[(SparkPlan, BuildSide)] = plan match {
       case join: BroadcastHashJoinExec if canUseLocalShuffleReader(join.left) =>
@@ -142,8 +139,10 @@ object OptimizeLocalShuffleReader {
   }
 
   def canUseLocalShuffleReader(plan: SparkPlan): Boolean = plan match {
-    case s: ShuffleQueryStageExec => s.shuffle.canChangeNumPartitions
+    case s: ShuffleQueryStageExec =>
-    case CustomShuffleReaderExec(s: ShuffleQueryStageExec, _, _) => s.shuffle.canChangeNumPartitions
+      s.shuffle.canChangeNumPartitions
+    case CustomShuffleReaderExec(s: ShuffleQueryStageExec, _) =>
+      s.shuffle.canChangeNumPartitions
     case _ => false
   }
 }

sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/OptimizeSkewedJoin.scala

@@ -120,7 +120,8 @@ case class OptimizeSkewedJoin(conf: SQLConf) extends Rule[SparkPlan] {
         } else {
           mapStartIndices(i + 1)
         }
-        PartialReducerPartitionSpec(reducerId, startMapIndex, endMapIndex)
+        val dataSize = startMapIndex.until(endMapIndex).map(mapPartitionSizes(_)).sum
+        PartialReducerPartitionSpec(reducerId, startMapIndex, endMapIndex, dataSize)
       })
     } else {
       None
@@ -182,8 +183,8 @@ case class OptimizeSkewedJoin(conf: SQLConf) extends Rule[SparkPlan] {
 
       val leftSidePartitions = mutable.ArrayBuffer.empty[ShufflePartitionSpec]
       val rightSidePartitions = mutable.ArrayBuffer.empty[ShufflePartitionSpec]
-      val leftSkewDesc = new SkewDesc
+      var numSkewedLeft = 0
-      val rightSkewDesc = new SkewDesc
+      var numSkewedRight = 0
       for (partitionIndex <- 0 until numPartitions) {
         val isLeftSkew = isSkewed(leftActualSizes(partitionIndex), leftMedSize) && canSplitLeft
         val leftPartSpec = left.partitionsWithSizes(partitionIndex)._1
@@ -199,9 +200,10 @@ case class OptimizeSkewedJoin(conf: SQLConf) extends Rule[SparkPlan] {
           val skewSpecs = createSkewPartitionSpecs(
             left.shuffleStage.shuffle.shuffleDependency.shuffleId, reducerId, leftTargetSize)
           if (skewSpecs.isDefined) {
-            logDebug(s"Left side partition $partitionIndex is skewed, split it into " +
+            val sizeStr = FileUtils.byteCountToDisplaySize(leftActualSizes(partitionIndex))
-              s"${skewSpecs.get.length} parts.")
+            logDebug(s"Left side partition $partitionIndex ($sizeStr) is skewed, " +
-            leftSkewDesc.addPartitionSize(leftActualSizes(partitionIndex))
+              s"split it into ${skewSpecs.get.length} parts.")
+            numSkewedLeft += 1
           }
           skewSpecs.getOrElse(Seq(leftPartSpec))
         } else {
@@ -214,9 +216,10 @@ case class OptimizeSkewedJoin(conf: SQLConf) extends Rule[SparkPlan] {
           val skewSpecs = createSkewPartitionSpecs(
             right.shuffleStage.shuffle.shuffleDependency.shuffleId, reducerId, rightTargetSize)
           if (skewSpecs.isDefined) {
-            logDebug(s"Right side partition $partitionIndex is skewed, split it into " +
+            val sizeStr = FileUtils.byteCountToDisplaySize(rightActualSizes(partitionIndex))
-              s"${skewSpecs.get.length} parts.")
+            logDebug(s"Right side partition $partitionIndex ($sizeStr) is skewed, " +
-            rightSkewDesc.addPartitionSize(rightActualSizes(partitionIndex))
+              s"split it into ${skewSpecs.get.length} parts.")
+            numSkewedRight += 1
           }
           skewSpecs.getOrElse(Seq(rightPartSpec))
         } else {
@@ -232,13 +235,10 @@ case class OptimizeSkewedJoin(conf: SQLConf) extends Rule[SparkPlan] {
         }
       }
 
-      logDebug("number of skewed partitions: " +
+      logDebug(s"number of skewed partitions: left $numSkewedLeft, right $numSkewedRight")
-        s"left ${leftSkewDesc.numPartitions}, right ${rightSkewDesc.numPartitions}")
+      if (numSkewedLeft > 0 || numSkewedRight > 0) {
-      if (leftSkewDesc.numPartitions > 0 || rightSkewDesc.numPartitions > 0) {
+        val newLeft = CustomShuffleReaderExec(left.shuffleStage, leftSidePartitions)
-        val newLeft = CustomShuffleReaderExec(
+        val newRight = CustomShuffleReaderExec(right.shuffleStage, rightSidePartitions)
-          left.shuffleStage, leftSidePartitions, leftSkewDesc.toString)
-        val newRight = CustomShuffleReaderExec(
-          right.shuffleStage, rightSidePartitions, rightSkewDesc.toString)
         smj.copy(
           left = s1.copy(child = newLeft), right = s2.copy(child = newRight), isSkewJoin = true)
       } else {
@@ -287,16 +287,14 @@ case class OptimizeSkewedJoin(conf: SQLConf) extends Rule[SparkPlan] {
 private object ShuffleStage {
   def unapply(plan: SparkPlan): Option[ShuffleStageInfo] = plan match {
     case s: ShuffleQueryStageExec =>
-      val mapStats = getMapStats(s)
+      val sizes = s.mapStats.bytesByPartitionId
-      val sizes = mapStats.bytesByPartitionId
       val partitions = sizes.zipWithIndex.map {
         case (size, i) => CoalescedPartitionSpec(i, i + 1) -> size
       }
-      Some(ShuffleStageInfo(s, mapStats, partitions))
+      Some(ShuffleStageInfo(s, s.mapStats, partitions))
 
-    case CustomShuffleReaderExec(s: ShuffleQueryStageExec, partitionSpecs, _) =>
+    case CustomShuffleReaderExec(s: ShuffleQueryStageExec, partitionSpecs) =>
-      val mapStats = getMapStats(s)
+      val sizes = s.mapStats.bytesByPartitionId
-      val sizes = mapStats.bytesByPartitionId
       val partitions = partitionSpecs.map {
         case spec @ CoalescedPartitionSpec(start, end) =>
           var sum = 0L
@@ -309,51 +307,13 @@ private object ShuffleStage {
         case other => throw new IllegalArgumentException(
           s"Expect CoalescedPartitionSpec but got $other")
       }
-      Some(ShuffleStageInfo(s, mapStats, partitions))
+      Some(ShuffleStageInfo(s, s.mapStats, partitions))
 
     case _ => None
   }
-
-  private def getMapStats(stage: ShuffleQueryStageExec): MapOutputStatistics = {
-    assert(stage.resultOption.isDefined, "ShuffleQueryStageExec should" +
-      " already be ready when executing OptimizeSkewedPartitions rule")
-    stage.resultOption.get.asInstanceOf[MapOutputStatistics]
-  }
 }
 
 private case class ShuffleStageInfo(
     shuffleStage: ShuffleQueryStageExec,
     mapStats: MapOutputStatistics,
     partitionsWithSizes: Seq[(CoalescedPartitionSpec, Long)])
-
-private class SkewDesc {
-  private[this] var numSkewedPartitions: Int = 0
-  private[this] var totalSize: Long = 0
-  private[this] var maxSize: Long = 0
-  private[this] var minSize: Long = 0
-
-  def numPartitions: Int = numSkewedPartitions
-
-  def addPartitionSize(size: Long): Unit = {
-    if (numSkewedPartitions == 0) {
-      maxSize = size
-      minSize = size
-    }
-    numSkewedPartitions += 1
-    totalSize += size
-    if (size > maxSize) maxSize = size
-    if (size < minSize) minSize = size
-  }
-
-  override def toString: String = {
-    if (numSkewedPartitions == 0) {
-      "no skewed partition"
-    } else {
-      val maxSizeStr = FileUtils.byteCountToDisplaySize(maxSize)
-      val minSizeStr = FileUtils.byteCountToDisplaySize(minSize)
-      val avgSizeStr = FileUtils.byteCountToDisplaySize(totalSize / numSkewedPartitions)
-      s"$numSkewedPartitions skewed partitions with " +
-        s"size(max=$maxSizeStr, min=$minSizeStr, avg=$avgSizeStr)"
-    }
-  }
-}

sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/QueryStageExec.scala

@@ -161,6 +161,11 @@ case class ShuffleQueryStageExec(
       case _ =>
     }
   }
+
+  def mapStats: MapOutputStatistics = {
+    assert(resultOption.isDefined)
+    resultOption.get.asInstanceOf[MapOutputStatistics]
+  }
 }
 
 /**

sql/core/src/test/scala/org/apache/spark/sql/execution/CoalesceShufflePartitionsSuite.scala

@@ -23,7 +23,6 @@ import org.apache.spark.{SparkConf, SparkFunSuite}
 import org.apache.spark.internal.config.UI.UI_ENABLED
 import org.apache.spark.sql._
 import org.apache.spark.sql.execution.adaptive._
-import org.apache.spark.sql.execution.adaptive.CoalesceShufflePartitions.COALESCED_SHUFFLE_READER_DESCRIPTION
 import org.apache.spark.sql.execution.adaptive.CustomShuffleReaderExec
 import org.apache.spark.sql.execution.exchange.ReusedExchangeExec
 import org.apache.spark.sql.functions._
@@ -108,7 +107,7 @@ class CoalesceShufflePartitionsSuite extends SparkFunSuite with BeforeAndAfterAl
         val finalPlan = agg.queryExecution.executedPlan
           .asInstanceOf[AdaptiveSparkPlanExec].executedPlan
         val shuffleReaders = finalPlan.collect {
-          case r @ CustomShuffleReaderExec(_, _, COALESCED_SHUFFLE_READER_DESCRIPTION) => r
+          case r @ CoalescedShuffleReader() => r
         }
         assert(shuffleReaders.length === 1)
         minNumPostShufflePartitions match {
@@ -155,7 +154,7 @@ class CoalesceShufflePartitionsSuite extends SparkFunSuite with BeforeAndAfterAl
         val finalPlan = join.queryExecution.executedPlan
           .asInstanceOf[AdaptiveSparkPlanExec].executedPlan
         val shuffleReaders = finalPlan.collect {
-          case r @ CustomShuffleReaderExec(_, _, COALESCED_SHUFFLE_READER_DESCRIPTION) => r
+          case r @ CoalescedShuffleReader() => r
         }
         assert(shuffleReaders.length === 2)
         minNumPostShufflePartitions match {
@@ -207,7 +206,7 @@ class CoalesceShufflePartitionsSuite extends SparkFunSuite with BeforeAndAfterAl
         val finalPlan = join.queryExecution.executedPlan
           .asInstanceOf[AdaptiveSparkPlanExec].executedPlan
         val shuffleReaders = finalPlan.collect {
-          case r @ CustomShuffleReaderExec(_, _, COALESCED_SHUFFLE_READER_DESCRIPTION) => r
+          case r @ CoalescedShuffleReader() => r
         }
         assert(shuffleReaders.length === 2)
         minNumPostShufflePartitions match {
@@ -259,7 +258,7 @@ class CoalesceShufflePartitionsSuite extends SparkFunSuite with BeforeAndAfterAl
         val finalPlan = join.queryExecution.executedPlan
           .asInstanceOf[AdaptiveSparkPlanExec].executedPlan
         val shuffleReaders = finalPlan.collect {
-          case r @ CustomShuffleReaderExec(_, _, COALESCED_SHUFFLE_READER_DESCRIPTION) => r
+          case r @ CoalescedShuffleReader() => r
         }
         assert(shuffleReaders.length === 2)
         minNumPostShufflePartitions match {
@@ -302,7 +301,7 @@ class CoalesceShufflePartitionsSuite extends SparkFunSuite with BeforeAndAfterAl
           val finalPlan = join.queryExecution.executedPlan
             .asInstanceOf[AdaptiveSparkPlanExec].executedPlan
           val shuffleReaders = finalPlan.collect {
-            case r @ CustomShuffleReaderExec(_, _, COALESCED_SHUFFLE_READER_DESCRIPTION) => r
+            case r @ CoalescedShuffleReader() => r
           }
           assert(shuffleReaders.length === 0)
         } finally {
@@ -332,7 +331,7 @@ class CoalesceShufflePartitionsSuite extends SparkFunSuite with BeforeAndAfterAl
       }.length == 2)
       assert(
         finalPlan.collect {
-          case p @ CustomShuffleReaderExec(_, _, COALESCED_SHUFFLE_READER_DESCRIPTION) => p
+          case r @ CoalescedShuffleReader() => r
         }.length == 3)
 
 
@@ -383,7 +382,7 @@ class CoalesceShufflePartitionsSuite extends SparkFunSuite with BeforeAndAfterAl
         .asInstanceOf[AdaptiveSparkPlanExec].executedPlan
       assert(
         finalPlan.collect {
-          case p @ CustomShuffleReaderExec(_, _, COALESCED_SHUFFLE_READER_DESCRIPTION) => p
+          case r @ CoalescedShuffleReader() => r
         }.isEmpty)
     }
     withSparkSession(test, 200, None)
@@ -404,9 +403,15 @@ class CoalesceShufflePartitionsSuite extends SparkFunSuite with BeforeAndAfterAl
       // the shuffle partition numbers.
       assert(
         finalPlan.collect {
-          case p @ CustomShuffleReaderExec(_, _, COALESCED_SHUFFLE_READER_DESCRIPTION) => p
+          case r @ CoalescedShuffleReader() => r
         }.isEmpty)
     }
     withSparkSession(test, 100, None)
   }
 }
+
+object CoalescedShuffleReader {
+  def unapply(reader: CustomShuffleReaderExec): Boolean = {
+    !reader.isLocalReader && !reader.hasSkewedPartition && reader.hasCoalescedPartition
+  }
+}

sql/core/src/test/scala/org/apache/spark/sql/execution/adaptive/AdaptiveQueryExecSuite.scala

@@ -25,9 +25,8 @@ import org.apache.log4j.Level
 import org.apache.spark.scheduler.{SparkListener, SparkListenerEvent, SparkListenerJobStart}
 import org.apache.spark.sql.QueryTest
 import org.apache.spark.sql.execution.{ReusedSubqueryExec, ShuffledRowRDD, SparkPlan}
-import org.apache.spark.sql.execution.adaptive.OptimizeLocalShuffleReader.LOCAL_SHUFFLE_READER_DESCRIPTION
 import org.apache.spark.sql.execution.exchange.{BroadcastExchangeExec, Exchange, ReusedExchangeExec}
-import org.apache.spark.sql.execution.joins.{BroadcastHashJoinExec, BuildRight, SortMergeJoinExec}
+import org.apache.spark.sql.execution.joins.{BroadcastHashJoinExec, BuildLeft, BuildRight, SortMergeJoinExec}
 import org.apache.spark.sql.execution.ui.SparkListenerSQLAdaptiveExecutionUpdate
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.test.SharedSparkSession
@@ -113,7 +112,7 @@ class AdaptiveQueryExecSuite
     }.length
 
     val numLocalReaders = collect(plan) {
-      case reader @ CustomShuffleReaderExec(_, _, LOCAL_SHUFFLE_READER_DESCRIPTION) => reader
+      case reader: CustomShuffleReaderExec if reader.isLocalReader => reader
     }
     numLocalReaders.foreach { r =>
       val rdd = r.execute()
@@ -149,7 +148,7 @@ class AdaptiveQueryExecSuite
       val bhj = findTopLevelBroadcastHashJoin(adaptivePlan)
       assert(bhj.size == 1)
       val localReaders = collect(adaptivePlan) {
-        case reader @ CustomShuffleReaderExec(_, _, LOCAL_SHUFFLE_READER_DESCRIPTION) => reader
+        case reader: CustomShuffleReaderExec if reader.isLocalReader => reader
       }
       assert(localReaders.length == 2)
       val localShuffleRDD0 = localReaders(0).execute().asInstanceOf[ShuffledRowRDD]
@@ -181,7 +180,7 @@ class AdaptiveQueryExecSuite
       val bhj = findTopLevelBroadcastHashJoin(adaptivePlan)
       assert(bhj.size == 1)
       val localReaders = collect(adaptivePlan) {
-        case reader @ CustomShuffleReaderExec(_, _, LOCAL_SHUFFLE_READER_DESCRIPTION) => reader
+        case reader: CustomShuffleReaderExec if reader.isLocalReader => reader
       }
       assert(localReaders.length == 2)
       val localShuffleRDD0 = localReaders(0).execute().asInstanceOf[ShuffledRowRDD]
@@ -781,4 +780,69 @@ class AdaptiveQueryExecSuite
       }
     }
   }
+
+  test("metrics of the shuffle reader") {
+    withSQLConf(SQLConf.ADAPTIVE_EXECUTION_ENABLED.key -> "true") {
+      val (_, adaptivePlan) = runAdaptiveAndVerifyResult(
+        "SELECT key FROM testData GROUP BY key")
+      val readers = collect(adaptivePlan) {
+        case r: CustomShuffleReaderExec => r
+      }
+      assert(readers.length == 1)
+      val reader = readers.head
+      assert(!reader.isLocalReader)
+      assert(!reader.hasSkewedPartition)
+      assert(reader.hasCoalescedPartition)
+      assert(reader.metrics.keys.toSeq.sorted == Seq(
+        "avgPartitionDataSize", "maxPartitionDataSize", "minPartitionDataSize", "numPartitions"))
+      assert(reader.metrics("numPartitions").value == reader.partitionSpecs.length)
+      assert(reader.metrics("avgPartitionDataSize").value > 0)
+      assert(reader.metrics("maxPartitionDataSize").value > 0)
+      assert(reader.metrics("minPartitionDataSize").value > 0)
+
+      withSQLConf(SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "80") {
+        val (_, adaptivePlan) = runAdaptiveAndVerifyResult(
+          "SELECT * FROM testData join testData2 ON key = a where value = '1'")
+        val join = collect(adaptivePlan) {
+          case j: BroadcastHashJoinExec => j
+        }.head
+        assert(join.buildSide == BuildLeft)
+
+        val readers = collect(join.right) {
+          case r: CustomShuffleReaderExec => r
+        }
+        assert(readers.length == 1)
+        val reader = readers.head
+        assert(reader.isLocalReader)
+        assert(reader.metrics.keys.toSeq == Seq("numPartitions"))
+        assert(reader.metrics("numPartitions").value == reader.partitionSpecs.length)
+      }
+
+      withSQLConf(
+        SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "-1",
+        SQLConf.ADVISORY_PARTITION_SIZE_IN_BYTES.key -> "2000",
+        SQLConf.SKEW_JOIN_SKEWED_PARTITION_THRESHOLD.key -> "2000") {
+        withTempView("skewData1", "skewData2") {
+          spark
+            .range(0, 1000, 1, 10)
+            .selectExpr("id % 2 as key1", "id as value1")
+            .createOrReplaceTempView("skewData1")
+          spark
+            .range(0, 1000, 1, 10)
+            .selectExpr("id % 1 as key2", "id as value2")
+            .createOrReplaceTempView("skewData2")
+          val (_, adaptivePlan) = runAdaptiveAndVerifyResult(
+            "SELECT * FROM skewData1 join skewData2 ON key1 = key2")
+          val reader = collect(adaptivePlan) {
+            case r: CustomShuffleReaderExec => r
+          }.head
+          assert(!reader.isLocalReader)
+          assert(reader.hasSkewedPartition)
+          assert(reader.hasCoalescedPartition)
+          assert(reader.metrics.contains("numSkewedPartitions"))
+          assert(reader.metrics("numSkewedPartitions").value > 0)
+        }
+      }
+    }
+  }
 }