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534. Game Play Analysis III

中文文档

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.

 

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: 
Activity table:
+-----------+-----------+------------+--------------+
| 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 = 11 games played by 2016-05-02, and 5 + 6 + 1 = 12 games played by 2017-06-25.
For the player with id 3, 0 + 5 = 5 games played by 2018-07-03.
Note that for each player we only care about the days when the player logged in.

Solutions

Solution 1: Window Function

We can use the window function SUM() OVER() to group by player_id, sort by event_date, and calculate the total number of games played by each user up to the current date.

# Write your MySQL query statement below
SELECT
  player_id,
  event_date,
  SUM(games_played) OVER (
    PARTITION BY player_id
    ORDER BY event_date
  ) AS games_played_so_far
FROM Activity;

Solution 2: Self-Join + Group By

We can also use a self-join to join the Activity table with itself on the condition of t1.player_id = t2.player_id AND t1.event_date >= t2.event_date, and then group by t1.player_id and t1.event_date, and calculate the cumulative sum of t2.games_played. This will give us the total number of games played by each user up to the current date.

# Write your MySQL query statement below
SELECT
  t1.player_id,
  t1.event_date,
  SUM(t2.games_played) AS games_played_so_far
FROM
  Activity AS t1,
  Activity AS t2
WHERE t1.player_id = t2.player_id AND t1.event_date >= t2.event_date
GROUP BY 1, 2;

Solution 3

# Write your MySQL query statement below
SELECT
  t1.player_id,
  t1.event_date,
  SUM(t2.games_played) AS games_played_so_far
FROM
  Activity AS t1
  CROSS JOIN Activity AS t2 ON t1.player_id = t2.player_id AND t1.event_date >= t2.event_date
GROUP BY 1, 2;

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