Github user cloud-fan commented on a diff in the pull request: https://github.com/apache/spark/pull/16626#discussion_r107048698 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/SessionCatalog.scala --- @@ -296,6 +311,51 @@ class SessionCatalog( } /** + * Alter the schema of a table identified by the provided table identifier. The new schema + * should still contain the existing bucket columns and partition columns used by the table. This + * method will also update any Spark SQL-related parameters stored as Hive table properties (such + * as the schema itself). + * + * @param identifier TableIdentifier + * @param newSchema Updated schema to be used for the table (must contain existing partition and + * bucket columns) + */ + def alterTableSchema( + identifier: TableIdentifier, + newSchema: StructType): Unit = { + val db = formatDatabaseName(identifier.database.getOrElse(getCurrentDatabase)) + val table = formatTableName(identifier.table) + val tableIdentifier = TableIdentifier(table, Some(db)) + requireDbExists(db) + requireTableExists(tableIdentifier) + checkDuplication(newSchema) + + val catalogTable = externalCatalog.getTable(db, table) + val oldSchema = catalogTable.schema + + // not supporting dropping columns yet + val nonExistentColumnNames = oldSchema.map(_.name).filterNot(columnNameResolved(newSchema, _)) + if (nonExistentColumnNames.nonEmpty) { + throw new AnalysisException( + s""" + |Some existing schema fields (${nonExistentColumnNames.mkString("[", ",", "]")}) are + |not present in the new schema. We don't support dropping columns yet. + """.stripMargin) + } + + // make sure partition columns are at the end + val partitionSchema = catalogTable.partitionSchema --- End diff -- `CatalogTable.partitionSchema` will throw exception if partition columns are not at the end, so we can just call `partitionSchema`, no need to do the reordering.
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