Table: Activity
+--------------+---------+ | Column Name | Type | +--------------+---------+ | player_id | int | | device_id | int | | event_date | date | | games_played | int | +--------------+---------+ (player_id, event_date) is the primary key (combination of columns with unique values) of this table. This table shows the activity of players of some games. Each row is a record of a player who logged in and played a number of games (possibly 0) before logging out on someday using some device.
Write a solution to report the device that is first logged in for each player.
Return the result table in any order.
The result format is in the following example.
Example 1:
Input: Activity table: +-----------+-----------+------------+--------------+ | player_id | device_id | event_date | games_played | +-----------+-----------+------------+--------------+ | 1 | 2 | 2016-03-01 | 5 | | 1 | 2 | 2016-05-02 | 6 | | 2 | 3 | 2017-06-25 | 1 | | 3 | 1 | 2016-03-02 | 0 | | 3 | 4 | 2018-07-03 | 5 | +-----------+-----------+------------+--------------+ Output: +-----------+-----------+ | player_id | device_id | +-----------+-----------+ | 1 | 2 | | 2 | 3 | | 3 | 1 | +-----------+-----------+
We can use GROUP BY and MIN functions to find the first login date for each player, and then use a subquery with a composite key to find the first login device for each player.
We can use the window function rank(), which assigns a rank to each login date for each player, and then select the rows with a rank of 1.
| Approach | Complexity |
|---|---|
| Subquery | — |
| Window Function | — |
LeetCode 550: Game Play Analysis IV [SQL] • Frederik Müller • 10,657 views views
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