sparksql-unpivot子句介绍

UNPIVOT [ { INCLUDE | EXCLUDE } NULLS ] (
    { single_value_column_unpivot | multi_value_column_unpivot }
) [[AS] alias]

single_value_column_unpivot:
    values_column
    FOR name_column
    IN (unpivot_column [[AS] alias] [, ...])

multi_value_column_unpivot:
    (values_column [, ...])
    FOR name_column
    IN ((unpivot_column [, ...]) [[AS] alias] [, ...])

CREATE TABLE sales_quarterly (year INT, q1 INT, q2 INT, q3 INT, q4 INT);
INSERT INTO sales_quarterly VALUES
    (2020, null, 1000, 2000, 2500),
    (2021, 2250, 3200, 4200, 5900),
    (2022, 4200, 3100, null, null);

-- 列名被用作反透视列
SELECT * FROM sales_quarterly
    UNPIVOT (
        sales FOR quarter IN (q1, q2, q3, q4)
    );
+------+---------+-------+
| year | quarter | sales |
+------+---------+-------+
| 2020 | q2      | 1000  |
| 2020 | q3      | 2000  |
| 2020 | q4      | 2500  |
| 2021 | q1      | 2250  |
| 2021 | q2      | 3200  |
| 2021 | q3      | 4200  |
| 2021 | q4      | 5900  |
| 2022 | q1      | 4200  |
| 2022 | q2      | 3100  |
+------+---------+-------+

-- 默认情况下，NULL 值会被排除在外，但可以选择包含它们
-- 反透视列可以起别名
-- 可以通过别名引用反透视结果
SELECT up.* FROM sales_quarterly
    UNPIVOT INCLUDE NULLS (
        sales FOR quarter IN (q1 AS Q1, q2 AS Q2, q3 AS Q3, q4 AS Q4)
    ) AS up;
+------+---------+-------+
| year | quarter | sales |
+------+---------+-------+
| 2020 | Q1      | NULL  |
| 2020 | Q2      | 1000  |
| 2020 | Q3      | 2000  |
| 2020 | Q4      | 2500  |
| 2021 | Q1      | 2250  |
| 2021 | Q2      | 3200  |
| 2021 | Q3      | 4200  |
| 2021 | Q4      | 5900  |
| 2022 | Q1      | 4200  |
| 2022 | Q2      | 3100  |
| 2022 | Q3      | NULL  |
| 2022 | Q4      | NULL  |
+------+---------+-------+

-- 多列值反透视
SELECT * FROM sales_quarterly
    UNPIVOT EXCLUDE NULLS (
        (first_quarter, second_quarter)
        FOR half_of_the_year IN (
            (q1, q2) AS H1,
            (q3, q4) AS H2
        )
    );
+------+------------------+---------------+----------------+
|  id  | half_of_the_year | first_quarter | second_quarter |
+------+------------------+---------------+----------------+
| 2020 | H1               | NULL          | 1000           |
| 2020 | H2               | 2000          | 2500           |
| 2021 | H1               | 2250          | 3200           |
| 2021 | H2               | 4200          | 5900           |
| 2022 | H1               | 4200          | 3100           |
+------+------------------+---------------+----------------+