Github user gatorsmile commented on a diff in the pull request: https://github.com/apache/spark/pull/19796#discussion_r230609716 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/catalog/Catalog.scala --- @@ -411,7 +410,29 @@ abstract class Catalog { tableName: String, source: String, schema: StructType, - options: Map[String, String]): DataFrame + options: Map[String, String]): DataFrame = { + createTable(tableName, source, schema, options, Nil) + } + + /** + * :: Experimental :: + * (Scala-specific) + * Create a table based on the dataset in a data source, a schema, a set of options and a set of partition columns. + * Then, returns the corresponding DataFrame. + * + * @param tableName is either a qualified or unqualified name that designates a table. + * If no database identifier is provided, it refers to a table in + * the current database. + * @since ??? + */ + @Experimental + @InterfaceStability.Evolving + def createTable( + tableName: String, + source: String, + schema: StructType, + options: Map[String, String], + partitionColumnNames : Seq[String]): DataFrame --- End diff -- I think we will not introduce a new API for partitioning columns in the current stage. Let us use SQL DDL for creating the table.
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