[GitHub] [spark] Yikf commented on a change in pull request #35527: [SPARK-38216][SQL] Fail early if all the columns are partitioned columns when creating a Hive table

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Yikf commented on a change in pull request #35527:
URL: https://github.com/apache/spark/pull/35527#discussion_r807625071



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File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala
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@@ -319,15 +319,7 @@ case class PreprocessTableCreation(sparkSession: SparkSession) extends Rule[Logi
       conf.resolver)
 
     if (schema.nonEmpty && normalizedPartitionCols.length == schema.length) {
-      if (DDLUtils.isHiveTable(table)) {

Review comment:
       There doesn't seem to be any relevant information in the commit history message, It seems we did this on purpose from comment.
   
   But in [HiveClientImpl.toHiveTable](https://github.com/apache/spark/blob/1ef5638177dcf06ebca4e9b0bc88401e0fce2ae8/sql/hive/src/main/scala/org/apache/spark/sql/hive/client/HiveClientImpl.scala#L1069-L1072), we partitioned the partition cols and other cols, If all columns are partitioned columns, `hivetabl.getFields` will get an empty result, so Hive will throw an exception cols has at least one column
   
   If Hive allows cols to inherit partitioned columns, we should not do `partition` in `toHiveTable`, if not, we should fail early, I'm sorry I'm not sure about that
   




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