hvanhovell commented on a change in pull request #26434: [SPARK-29544] [SQL] 
optimize skewed partition based on data size
URL: https://github.com/apache/spark/pull/26434#discussion_r366349658
 
 

 ##########
 File path: 
sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/OptimizeSkewedJoin.scala
 ##########
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+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.adaptive
+
+import scala.collection.mutable
+import scala.collection.mutable.ArrayBuffer
+
+import org.apache.spark.{MapOutputStatistics, MapOutputTrackerMaster, SparkEnv}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.Attribute
+import org.apache.spark.sql.catalyst.plans._
+import org.apache.spark.sql.catalyst.plans.physical.{Partitioning, 
UnknownPartitioning}
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.execution._
+import org.apache.spark.sql.execution.exchange.ShuffleExchangeExec
+import org.apache.spark.sql.execution.joins.SortMergeJoinExec
+import org.apache.spark.sql.internal.SQLConf
+
+case class OptimizeSkewedJoin(conf: SQLConf) extends Rule[SparkPlan] {
+
+  private val supportedJoinTypes =
+    Inner :: Cross :: LeftSemi :: LeftAnti :: LeftOuter :: RightOuter :: Nil
+
+  /**
+   * A partition is considered as a skewed partition if its size is larger 
than the median
+   * partition size * spark.sql.adaptive.skewedPartitionFactor and also larger 
than
+   * spark.sql.adaptive.skewedPartitionSizeThreshold.
+   */
+  private def isSkewed(
+      stats: MapOutputStatistics,
+      partitionId: Int,
+      medianSize: Long): Boolean = {
+    val size = stats.bytesByPartitionId(partitionId)
+    size > medianSize * 
conf.getConf(SQLConf.ADAPTIVE_EXECUTION_SKEWED_PARTITION_FACTOR) &&
+      size > 
conf.getConf(SQLConf.ADAPTIVE_EXECUTION_SKEWED_PARTITION_SIZE_THRESHOLD)
+  }
+
+  private def medianSize(stats: MapOutputStatistics): Long = {
+    val numPartitions = stats.bytesByPartitionId.length
+    val bytes = stats.bytesByPartitionId.sorted
+    if (bytes(numPartitions / 2) > 0) bytes(numPartitions / 2) else 1
 
 Review comment:
   `math.min(bytes(numPartitions / 2), 1)`?
   
   OCD: you could argue that this median calculation is incorrect for an even 
number of elements. In that case it should be `(bytes(numPartitions / 2) + 
bytes((numPartitions + 1) / 2)) / 2`

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