Github user gatorsmile commented on a diff in the pull request: https://github.com/apache/spark/pull/14207#discussion_r73968228 --- 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 -- Here, `dataSource.schema` could be inferred. Previously, we do not store the inferred schema. After this PR, we did and thus we use `dataSource.schema`. Actually, after re-checking the code, I found the schema might be adjusted a little even if users specify the schema. For example, the nullability could be changed : https://github.com/apache/spark/blob/64529b186a1c33740067cc7639d630bc5b9ae6e8/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala#L407 I think we should make such a change but maybe we should test and log it?
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