Description
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 (column 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.
Problem Statement
Write a solution to report for each player and date, how many games played so far by the player. That is, the total number of games played by the player until that date. Check the example for clarity.
Return the result table in any order. The result format is in the following example.
Example 1:
Input:
Activitytable:
| player_id | device_id | event_date | games_played |
|---|---|---|---|
| 1 | 2 | 2016-03-01 | 5 |
| 1 | 2 | 2016-05-02 | 6 |
| 1 | 3 | 2017-06-25 | 1 |
| 3 | 1 | 2016-03-02 | 0 |
| 3 | 4 | 2018-07-03 | 5 |
Output:
| player_id | event_date | games_played_so_far |
|---|---|---|
| 1 | 2016-03-01 | 5 |
| 1 | 2016-05-02 | 11 |
| 1 | 2017-06-25 | 12 |
| 3 | 2016-03-02 | 0 |
| 3 | 2018-07-03 | 5 |
Explanation:
- For the player with id 1,
5 + 6 = 11games played by2016-05-02, and5 + 6 + 1 = 12games played by2017-06-25. - For the player with id 3,
0 + 5 = 5games played by2018-07-03.
Note that for each player we only care about the days when the player logged in.
Solution
The problem essentially wants to find rolling sum of games played by each player. The rolling sum can be implemented using window functions in SQL. In this case, window is defined by partitioning player_id and ordering the window by event_date column. You can calculate sum of games played for each window using SUM() window function.
1SELECT player_id, event_date,
2 SUM(games_played) OVER (PARTITION BY player_id ORDER BY event_date) AS games_played_so_far
3 FROM Activity;
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