Using window function to retrieve values from a column depending on another

Question

In a dataframe like below:

id    date      product
1   2010-02-01     c
1   2010-02-02     v
1   2010-02-03     d
1   2010-02-04     g
2   2010-02-03     h
2   2010-02-04     w
2   2010-02-05     t
2   2010-02-06     d
3   2010-02-04     x
3   2010-02-05     f
3   2010-02-06     x

I want to add another column giving the product that the user used in the minimum date. So it needs to be like below:

id    date      product  early_product
1   2010-02-01     c         c
1   2010-02-02     v         c
1   2010-02-03     d         c
1   2010-02-04     g         c
2   2010-02-03     h         h
2   2010-02-04     w         h
2   2010-02-05     t         h
2   2010-02-06     d         h
3   2010-02-04     x         x
3   2010-02-05     f         x
3   2010-02-06     x         x

I know I need to use the window function and started with the one below. But that will provide me the earliest date per user. I need to find the product used in the earliest day for user:

min(date) over (partition by id) as earliest_date

Answer 1

Use FIRST_VALUE as Window function

CREATE TABLE table1 (
  `id` INTEGER,
  `date` Date,
  `product` VARCHAR(1)
);

INSERT INTO table1
  (`id`, `date`, `product`)
VALUES
  ('1', '2010-02-01', 'c'),
  ('1', '2010-02-02', 'v'),
  ('1', '2010-02-03', 'd'),
  ('1', '2010-02-04', 'g'),
  ('2', '2010-02-03', 'h'),
  ('2', '2010-02-04', 'w'),
  ('2', '2010-02-05', 't'),
  ('2', '2010-02-06', 'd'),
  ('3', '2010-02-04', 'x'),
  ('3', '2010-02-05', 'f'),
  ('3', '2010-02-06', 'x');

SELECT `id`, `date`, `product` 
, FIRST_VALUE(`product`) OVER(PARTITION BY `id` ORDER BY `date` ROWS UNBOUNDED PRECEDING) minproduct
FROM table1

id | date       | product | minproduct
-: | :--------- | :------ | :---------
 1 | 2010-02-01 | c       | c         
 1 | 2010-02-02 | v       | c         
 1 | 2010-02-03 | d       | c         
 1 | 2010-02-04 | g       | c         
 2 | 2010-02-03 | h       | h         
 2 | 2010-02-04 | w       | h         
 2 | 2010-02-05 | t       | h         
 2 | 2010-02-06 | d       | h         
 3 | 2010-02-04 | x       | x         
 3 | 2010-02-05 | f       | x         
 3 | 2010-02-06 | x       | x         

db<>fiddle here