[GitHub] [spark] maryannxue commented on a change in pull request #27669: [SPARK-30918][SQL] improve the splitting of skewed partitions

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maryannxue commented on a change in pull request #27669: [SPARK-30918][SQL] improve the splitting of skewed partitions
URL: https://github.com/apache/spark/pull/27669#discussion_r382661964
 
 

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 File path: sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/OptimizeSkewedJoin.scala
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 @@ -61,6 +84,19 @@ case class OptimizeSkewedJoin(conf: SQLConf) extends Rule[SparkPlan] {
     }
   }
 
+  /**
+   * The goal of skew join optimization is to make the data distribution more even. The target size
+   * to split skewed partitions is the average size of non-skewed partition, or the
+   * target post-shuffle partition size if avg size is smaller than it.
+   */
+  private def targetSize(stats: MapOutputStatistics, medianSize: Long): Long = {
+    val targetPostShuffleSize = conf.getConf(SQLConf.SHUFFLE_TARGET_POSTSHUFFLE_INPUT_SIZE)
+    val nonSkewSizes = stats.bytesByPartitionId.filterNot(isSkewed(_, medianSize))
 
 Review comment:
   We can move this repetitive calc of non-skew average size out of this method, which will leave us just two local variables before the main loop below: `targetPostShuffleSizeConf` and `nonSkewAvgSize`. Then we only need to do: `max(targetPostShuffleSizeConf, nonSkewAvgSize)` without a method call.

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