Table: Activity
+--------------+---------+ | Column Name | Type | +--------------+---------+ | player_id | int | | device_id | int | | event_date | date | | games_played | int | +--------------+---------+ (player_id,event_date)是此表的主键(具有唯一值的列的组合)。 这张表显示了某些游戏的玩家的活动情况。 每一行是一个玩家的记录,他在某一天使用某个设备注销之前登录并玩了很多游戏(可能是 0)。
编写解决方案,报告在首次登录的第二天再次登录的玩家的 比率,四舍五入到小数点后两位。换句话说,你需要计算从首次登录日期开始至少连续两天登录的玩家的数量,然后除以玩家总数。
结果格式如下所示:
示例 1:
输入: Activity table: +-----------+-----------+------------+--------------+ | player_id | device_id | event_date | games_played | +-----------+-----------+------------+--------------+ | 1 | 2 | 2016-03-01 | 5 | | 1 | 2 | 2016-03-02 | 6 | | 2 | 3 | 2017-06-25 | 1 | | 3 | 1 | 2016-03-02 | 0 | | 3 | 4 | 2018-07-03 | 5 | +-----------+-----------+------------+--------------+ 输出: +-----------+ | fraction | +-----------+ | 0.33 | +-----------+ 解释: 只有 ID 为 1 的玩家在第一天登录后才重新登录,所以答案是 1/3 = 0.33
# Write your MySQL query statement below
SELECT round(AVG(b.event_date IS NOT NULL), 2) AS fraction
FROM
(
SELECT
player_id,
MIN(event_date) AS event_date
FROM activity
GROUP BY player_id
) AS a
LEFT JOIN activity AS b
ON a.player_id = b.player_id AND DATEDIFF(a.event_date, b.event_date) = -1;
# Write your MySQL query statement below
WITH
T AS (
SELECT
player_id,
datediff(
lead(event_date) OVER (
PARTITION BY player_id
ORDER BY event_date
),
event_date
) AS diff,
row_number() OVER (
PARTITION BY player_id
ORDER BY event_date
) AS rk
FROM Activity
)
SELECT
round(
count(DISTINCT if(diff = 1, player_id, NULL)) / count(
DISTINCT player_id
),
2
) AS fraction
FROM T
WHERE rk = 1;