cloud-fan 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_r358059773
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File path:
sql/core/src/test/scala/org/apache/spark/sql/execution/adaptive/AdaptiveQueryExecSuite.scala
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@@ -32,6 +33,30 @@ class AdaptiveQueryExecSuite
import testImplicits._
+ protected lazy val skewData1: DataFrame = {
+ val df1 =
+ spark
+ .range(0, 1000, 1, 10)
+ .selectExpr("id % 5 as key1", "id as value1").toDF()
+ df1.createOrReplaceTempView("skewData1")
+ df1
+ }
+
+ protected lazy val skewData2: DataFrame = {
+ val df2 =
+ spark
+ .range(0, 1000, 1, 10)
+ .selectExpr("id % 1 as key2", "id as value2").toDF()
+ df2.createOrReplaceTempView("skewData2")
+ df2
+ }
+
+ protected override def beforeAll(): Unit = {
+ super.beforeAll()
+ skewData1
Review comment:
what's the point here? We can just make them `val` not `lazy val`
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