LeetCode 코딩 테스트 - Confirmation Rate(LV.Medium)

 

 

Table: Signups

+----------------+----------+
| Column Name    | Type     |
+----------------+----------+
| user_id        | int      |
| time_stamp     | datetime |
+----------------+----------+
user_id is the column of unique values for this table.
Each row contains information about the signup time for the user with ID user_id.

 

Table: Confirmations

+----------------+----------+
| Column Name    | Type     |
+----------------+----------+
| user_id        | int      |
| time_stamp     | datetime |
| action         | ENUM     |
+----------------+----------+
(user_id, time_stamp) is the primary key (combination of columns with unique values) for this table.
user_id is a foreign key (reference column) to the Signups table.
action is an ENUM (category) of the type ('confirmed', 'timeout')
Each row of this table indicates that the user with ID user_id requested a confirmation message at time_stamp and that confirmation message was either confirmed ('confirmed') or expired without confirming ('timeout').

 

The confirmation rate of a user is the number of 'confirmed' messages divided by the total number of requested confirmation messages. The confirmation rate of a user that did not request any confirmation messages is 0. Round the confirmation rate to two decimal places.

Write a solution to find the confirmation rate of each user.

Return the result table in any order.

The result format is in the following example.

 

Example 1:

Input: 
Signups table:
+---------+---------------------+
| user_id | time_stamp          |
+---------+---------------------+
| 3       | 2020-03-21 10:16:13 |
| 7       | 2020-01-04 13:57:59 |
| 2       | 2020-07-29 23:09:44 |
| 6       | 2020-12-09 10:39:37 |
+---------+---------------------+
Confirmations table:
+---------+---------------------+-----------+
| user_id | time_stamp          | action    |
+---------+---------------------+-----------+
| 3       | 2021-01-06 03:30:46 | timeout   |
| 3       | 2021-07-14 14:00:00 | timeout   |
| 7       | 2021-06-12 11:57:29 | confirmed |
| 7       | 2021-06-13 12:58:28 | confirmed |
| 7       | 2021-06-14 13:59:27 | confirmed |
| 2       | 2021-01-22 00:00:00 | confirmed |
| 2       | 2021-02-28 23:59:59 | timeout   |
+---------+---------------------+-----------+
Output: 
+---------+-------------------+
| user_id | confirmation_rate |
+---------+-------------------+
| 6       | 0.00              |
| 3       | 0.00              |
| 7       | 1.00              |
| 2       | 0.50              |
+---------+-------------------+
Explanation: 
User 6 did not request any confirmation messages. The confirmation rate is 0.
User 3 made 2 requests and both timed out. The confirmation rate is 0.
User 7 made 3 requests and all were confirmed. The confirmation rate is 1.
User 2 made 2 requests where one was confirmed and the other timed out. The confirmation rate is 1 / 2 = 0.5.

 

# 쿼리를 작성하는 목표, 확인할 지표 : 유저 별로 confirmed의 비율 구하기 / action
# 쿼리 계산 방법 : 1. signup 테이블을 기준으로 join -> 2. 유저별로 total과 confirmed 수 구하기(action 기록이 아예 없거나 confirmed가 없으면 0으로 표시되어야 함) -> 3. confirmed 비율 계산 -> 4. NULL 이면 0
# 데이터의 기간 : x
# 사용할 테이블 : signups, confirmations
# JOIN KEY : user_id
# 데이터 특징 : x
# 1
WITH base AS (
    SELECT
        s.user_id,
        c.action
    FROM signups AS s
    LEFT JOIN confirmations AS c
    ON s.user_id = c.user_id
)
SELECT
    # 3 & 4
    DISTINCT 
        user_id,
        COALESCE(ROUND(confirmed_cnt / total_cnt, 2), 0) AS confirmation_rate
FROM (
    # 2
    SELECT
        user_id,
        SUM(CASE WHEN action IS NOT NULL THEN 1 ELSE 0 END) OVER(PARTITION BY user_id) AS total_cnt,
        SUM(CASE WHEN action = 'confirmed' THEN 1 ELSE 0 END) OVER(PARTITION BY user_id) AS confirmed_cnt
    FROM base
) AS a