wangyum commented on a change in pull request #29475:
URL: https://github.com/apache/spark/pull/29475#discussion_r476998449
##########
File path:
sql/core/src/test/scala/org/apache/spark/sql/DynamicPartitionPruningSuite.scala
##########
@@ -1304,6 +1304,55 @@ abstract class DynamicPartitionPruningSuiteBase
)
}
}
+
+ test("SPARK-32659: Fix the data issue of inserted DPP on non-atomic type") {
+ withSQLConf(
+ SQLConf.DYNAMIC_PARTITION_PRUNING_FALLBACK_FILTER_RATIO.key -> "2", //
Make sure insert DPP
+ SQLConf.DYNAMIC_PARTITION_PRUNING_REUSE_BROADCAST_ONLY.key -> "false") {
+ withTable("df1", "df2") {
+ spark.range(1000)
+ .select(col("id"), col("id").as("k"))
+ .write
+ .partitionBy("k")
+ .format(tableFormat)
+ .mode("overwrite")
+ .saveAsTable("df1")
+
+ spark.range(100)
+ .select(col("id"), col("id").as("k"))
+ .write
+ .partitionBy("k")
+ .format(tableFormat)
+ .mode("overwrite")
+ .saveAsTable("df2")
+
+ Seq(CodegenObjectFactoryMode.NO_CODEGEN,
+ CodegenObjectFactoryMode.CODEGEN_ONLY).foreach { mode =>
+ Seq(true, false).foreach { pruning =>
+ withSQLConf(
+ SQLConf.CODEGEN_FACTORY_MODE.key -> s"${mode.toString}",
+ SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED.key -> s"${pruning}") {
+ val df = sql(
+ """
+ |SELECT df1.id, df2.k
+ |FROM df1
+ | JOIN df2
+ | ON struct(df1.k) = struct(df2.k)
Review comment:
This will increase test time:
```
[info] - SPARK-32659: Fix the data issue when pruning DPP on non-atomic type
(48 seconds, 170 milliseconds)
```
This test tests `InSubqueryExec` use `InSet`.
`InSet` itself has these tests:
https://github.com/apache/spark/blob/1515d45b8db69de67cf61100f7cf4fa5c7cadbd4/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/PredicateSuite.scala#L321-L353
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