new_df = new_df.select(*self.fill_empty_colums(new_df_cols, total)).withColumn("row_priority",F.lit(0)) older_df = older_df.select(*self.fill_empty_colums(old_df_cols, total)).withColumn("row_priority",F.lit(1)) key_column = [F.col(column_name) for column_name in key_columns]

这段代码的SQL实现如下：

-- 对 new_df 进行处理
WITH new_df_filled AS (
  SELECT 
    *,
    CASE WHEN col1 IS NULL THEN 'default_value' ELSE col1 END AS col1_filled,
    CASE WHEN col2 IS NULL THEN 'default_value' ELSE col2 END AS col2_filled,
    ...,
    CASE WHEN coln IS NULL THEN 'default_value' ELSE coln END AS coln_filled
  FROM new_df
),
new_df_processed AS (
  SELECT 
    col1_filled,
    col2_filled,
    ...,
    coln_filled,
    0 AS row_priority
  FROM new_df_filled
),

-- 对 older_df 进行处理
older_df_filled AS (
  SELECT 
    *,
    CASE WHEN col1 IS NULL THEN 'default_value' ELSE col1 END AS col1_filled,
    CASE WHEN col2 IS NULL THEN 'default_value' ELSE col2 END AS col2_filled,
    ...,
    CASE WHEN coln IS NULL THEN 'default_value' ELSE coln END AS coln_filled
  FROM older_df
),
older_df_processed AS (
  SELECT 
    col1_filled,
    col2_filled,
    ...,
    coln_filled,
    1 AS row_priority
  FROM older_df_filled
)

-- 合并两个DataFrame
SELECT 
  col1_filled,
  col2_filled,
  ...,
  coln_filled,
  row_priority
FROM (
  SELECT * FROM new_df_processed UNION ALL SELECT * FROM older_df_processed
) AS merged_df
WHERE (col1_filled, col2_filled, ..., coln_filled) IN (
  SELECT col1_filled, col2_filled, ..., coln_filled
  FROM new_df_processed
  UNION
  SELECT col1_filled, col2_filled, ..., coln_filled
  FROM older_df_processed
  WHERE NOT (col1_filled, col2_filled, ..., coln_filled) IN (
    SELECT col1_filled, col2_filled, ..., coln_filled
    FROM new_df_processed
  )
)

其中，`new_df`和`older_df`分别是原始的DataFrame，`new_df_cols`和`old_df_cols`是DataFrame中的列名列表，`total`是总列数，`key_columns`是用于合并两个DataFrame的关键列。首先，对`new_df`和`older_df`分别进行处理，填充空列并添加`row_priority`列。然后，将两个DataFrame合并，并使用`WHERE`子句过滤出唯一的行。最后，选择填充后的列和`row_priority`列。需要注意的是，这段代码中的`NOT IN`子句可能会对性能产生负面影响，可以考虑使用`LEFT JOIN`和`NULL`判断来代替。