Write an SQL query and identify first login date for each gamer.
Input Table: gamers_activity
player_id | device_id | event_date | games_played |
7 | 22 | 2017-04-02 | 4 |
7 | 22 | 2017-06-05 | 3 |
9 | 33 | 2018-02-26 | 0 |
6 | 11 | 2017-05-07 | 7 |
6 | 44 | 2019-08-06 | 3 |
Output Table:
player_id | first_login |
7 | 2017-04-02 |
9 | 2017-04-02 |
6 | 2017-04-02 |
Explanation:
“gamers_activity” table shows the activity of gamers who played any game. Each row represents a record of gamer who played a game on that particular date before logging out. He might not have played any game as well ( that’s why we have one record with 0 as games_played in input table).
Identify first login_date of each gamer irrespective of whether he played any game or not on very first day.
DDLs:
CREATE TABLE IF NOT EXISTS gamers_activity ( player_id INT, device_id INT, event_date DATE, games_played INT ); INSERT INTO gamers_activity VALUES (7, 22, '2017-04-02', 4); INSERT INTO gamers_activity VALUES (7, 22, '2017-06-05', 3); INSERT INTO gamers_activity VALUES (9, 33, '2018-02-26', 0); INSERT INTO gamers_activity VALUES (6, 11, '2017-05-07', 7); INSERT INTO gamers_activity VALUES (6, 44, '2019-08-06', 3);
Solution:
SELECT player_id, MIN(event_date) AS first_login FROM gamers_activity GROUP BY player_id ;