key_columns = [F.col(column_name) for column_name in self.config.deduplication_key_columns] order_by_columns = [F.col(column_name).desc() for column_name in self.config.deduplication_order_columns] if self.config.deduplicate_order_by_type == "asc": order_by_columns = [F.col(column_name) for column_name in self.config.deduplication_order_columns] ranking_column = "duplicates_rank" is_deleted_column = "IsDeleted" if (self.config.filter_deleted_flag) & ( is_deleted_column in df.columns): # if True removes records that marked deleted filter = (F.col(ranking_column) == 1) & (F.col(is_deleted_column) == "False") else: self.logger.warning(f"Records marked as deleted will be loaded to {self.config.table_full_name} table!") filter = F.col(ranking_column) == 1这里能看出源数据是怎么样的df结构，给我一个例子，并且告诉我sql怎么筛选df的列出来

假设源数据`df`的列名和数据如下：

+----+-------+--------+-----------+
| id | name  | gender | is_deleted|
+----+-------+--------+-----------+
|  1 | Alice | female | False     |
|  2 | Bob   | male   | False     |
|  3 | Bob   | male   | True      |
|  4 | Alice | female | True      |
|  5 | Carol | female | False     |
+----+-------+--------+-----------+

则根据Python代码，可以使用以下SQL语句筛选出`key_columns`和`is_deleted_column`所对应的列：

SELECT id, name, gender, is_deleted
FROM source_table;

即将`source_table`替换为源数据表的表名，将`id, name, gender, is_deleted`替换为`self.config.deduplication_key_columns`和`is_deleted_column`所对应的列名，即可筛选出指定的列。