Github user yhuai commented on a diff in the pull request:

    https://github.com/apache/spark/pull/14207#discussion_r73940468
  
    --- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/command/createDataSourceTables.scala
 ---
    @@ -95,17 +95,39 @@ case class CreateDataSourceTableCommand(
           }
     
         // Create the relation to validate the arguments before writing the 
metadata to the metastore.
    -    DataSource(
    -      sparkSession = sparkSession,
    -      userSpecifiedSchema = userSpecifiedSchema,
    -      className = provider,
    -      bucketSpec = None,
    -      options = optionsWithPath).resolveRelation(checkPathExist = false)
    +    val dataSource: BaseRelation =
    +      DataSource(
    +        sparkSession = sparkSession,
    +        userSpecifiedSchema = userSpecifiedSchema,
    +        className = provider,
    +        bucketSpec = None,
    +        options = optionsWithPath).resolveRelation(checkPathExist = false)
    +
    +    val partitionColumns = if (userSpecifiedSchema.nonEmpty) {
    +      userSpecifiedPartitionColumns
    +    } else {
    +      val res = dataSource match {
    +        case r: HadoopFsRelation => r.partitionSchema.fieldNames
    +        case _ => Array.empty[String]
    +      }
    +      if (userSpecifiedPartitionColumns.length > 0) {
    +        // The table does not have a specified schema, which means that 
the schema will be inferred
    +        // when we load the table. So, we are not expecting partition 
columns and we will discover
    +        // partitions when we load the table. However, if there are 
specified partition columns,
    +        // we simply ignore them and provide a warning message.
    +        logWarning(
    +          s"Specified partition columns 
(${userSpecifiedPartitionColumns.mkString(",")}) will be " +
    +            s"ignored. The schema and partition columns of table 
$tableIdent are inferred. " +
    +            s"Schema: ${dataSource.schema.simpleString}; " +
    +            s"Partition columns: ${res.mkString("(", ", ", ")")}")
    +      }
    +      res
    +    }
     
         CreateDataSourceTableUtils.createDataSourceTable(
           sparkSession = sparkSession,
           tableIdent = tableIdent,
    -      userSpecifiedSchema = userSpecifiedSchema,
    +      schema = dataSource.schema,
    --- End diff --
    
    seems we should still use the user-specified schema, right?


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