在多日期列的mysql中需要取消透视的帮助

Question

Here is my input. I want to see my output like : (I am trying to do unpivot in mysql data transform in Domo)

Product Type, Date, Revenue

A, 12-31-2015, 100
B, 12-31-2015, 0
C, 12-31-2015, 200
D, 12-31-2015, 300
E, 12-31-2015, 400 
A, 01-31-2016, 400
B, 01-31-2016, 86.88
C, 01-31-2016, 400 
D, 01-31-2016, 55
E, 01-31-2016, 455

so on

I am trying to use stored procedure:

create PROCEDURE unpivot_cols()
BEGIN
SET @sql = NULL;
SELECT GROUP_CONCAT(DISTINCT
CONCAT('select `Product Type`, ' '''', COLUMN_NAME, ''' col, ', column_name, ' as value from testing_unpivot'
) separator ' union all '
) INTO @sql
FROM INFORMATION_SCHEMA.COLUMNS
where table_name = 'testing_unpivot'
and column_name <> 'Product Type';
set @sql = CONCAT(@sql);
PREPARE stmt FROM @sql;
EXECUTE stmt;
DEALLOCATE PREPARE stmt;
END

When i try to execute above procedure , I see no output. Can anyone help me? PS: I tried using all help available on stack overflow. But non were helpful in my case.

Answer 1

I tested the following on MySQL 8.0.1:

SELECT GROUP_CONCAT(
  CONCAT(
    'SELECT `Product Type`, ', 
       QUOTE(COLUMN_NAME), ' AS `Date`, ',
       '`', COLUMN_NAME, '` AS `Revenue` ',
    'FROM testing_unpivot'
  ) SEPARATOR ' UNION ALL '
)
FROM INFORMATION_SCHEMA.COLUMNS
WHERE TABLE_NAME = 'testing_unpivot'
AND COLUMN_NAME <> 'Product Type';

Using the QUOTE() function makes it simpler, because it eliminates the need to figure out the triple vs. quad quotes.

Output:

SELECT `Product Type`, '01-31-2016' AS `Date`, `01-31-2016` AS `Revenue` FROM testing_unpivot 
UNION ALL 
SELECT `Product Type`, '02-29-2016' AS `Date`, `02-29-2016` AS `Revenue` FROM testing_unpivot 
UNION ALL 
SELECT `Product Type`, '12-31-2015' AS `Date`, `12-31-2015` AS `Revenue` FROM testing_unpivot

Then I did copy & paste to run that query and got this output:

+--------------+------------+---------+
| Product Type | Date       | Revenue |
+--------------+------------+---------+
| A            | 01-31-2016 |  400.00 |
| B            | 01-31-2016 |   86.88 |
| C            | 01-31-2016 |  400.00 |
| D            | 01-31-2016 |   55.00 |
| E            | 01-31-2016 |  455.00 |
| A            | 02-29-2016 |   55.00 |
| B            | 02-29-2016 |   55.00 |
| C            | 02-29-2016 |   55.00 |
| D            | 02-29-2016 |   11.00 |
| E            | 02-29-2016 |   22.00 |
| A            | 12-31-2015 |  100.00 |
| B            | 12-31-2015 |    0.00 |
| C            | 12-31-2015 |  200.00 |
| D            | 12-31-2015 |  300.00 |
| E            | 12-31-2015 |  400.00 |
+--------------+------------+---------+

I just loaded my test data with your first three dates worth of data.