[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_r387341483
 
 

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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 +85,19 @@ 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)
 
 Review comment:
   After coming across the config description of `ADAPTIVE_EXECUTION_SKEWED_PARTITION_SIZE_THRESHOLD`, I probably get @JkSelf 's point. In the description, it is meant to test if a partition is skewed... but the way it is actually used here in this class, it is more like the target size for splitting the skewed partitions.
   So we need to changes here:
   1. bring this conf back and use it in `isSkewed` instead.
   2. if eventually the entire "skewed" partition is not split at all because the size is smaller than the target size, we need to avoid adding the SkewDesc for that partition.

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