Leetcode 1113. 1132 Reported Posts
drop table Actions
Create table Actions (user_id int, post_id int, action_date date, action varchar(20), extra varchar(20))
insert into Actions (user_id, post_id, action_date, action, extra) values ('1', '1', '2019-07-01', 'view', 'None')
insert into Actions (user_id, post_id, action_date, action, extra) values ('1', '1', '2019-07-01', 'like', 'None')
insert into Actions (user_id, post_id, action_date, action, extra) values ('1', '1', '2019-07-01', 'share', 'None')
insert into Actions (user_id, post_id, action_date, action, extra) values ('2', '4', '2019-07-04', 'view', 'None')
insert into Actions (user_id, post_id, action_date, action, extra) values ('2', '4', '2019-07-04', 'report', 'spam')
insert into Actions (user_id, post_id, action_date, action, extra) values ('3', '4', '2019-07-04', 'view', 'None')
insert into Actions (user_id, post_id, action_date, action, extra) values ('3', '4', '2019-07-04', 'report', 'spam')
insert into Actions (user_id, post_id, action_date, action, extra) values ('4', '3', '2019-07-02', 'view', 'None')
insert into Actions (user_id, post_id, action_date, action, extra) values ('4', '3', '2019-07-02', 'report', 'spam')
insert into Actions (user_id, post_id, action_date, action, extra) values ('5', '2', '2019-07-04', 'view', 'None')
insert into Actions (user_id, post_id, action_date, action, extra) values ('5', '2', '2019-07-04', 'report', 'racism')
insert into Actions (user_id, post_id, action_date, action, extra) values ('5', '5', '2019-07-04', 'view', 'None')
insert into Actions (user_id, post_id, action_date, action, extra) values ('5', '5', '2019-07-04', 'report', 'racism')Leetcode 1113. Reported Posts
Write an SQL query that reports the number of posts reported yesterday for each report reason. Assume today is 2019-07-05.
select extra as report_reason,count(distinct post_id) as report_count
from Actions
where DATEDIFF(DAY,action_date,'2019-07-05')=1
and action = 'report'
group by extra
order by extra desc1132. Reported Posts II
Write an SQL query to find the average for daily percentage of posts that got removed after being reported as spam, rounded to 2 decimal places.
Table: Actions
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| user_id | int |
| post_id | int |
| action_date | date |
| action | enum |
| extra | varchar |
+---------------+---------+
There is no primary key for this table, it may have duplicate rows.
The action column is an ENUM type of ('view', 'like', 'reaction', 'comment', 'report', 'share').
The extra column has optional information about the action such as a reason for report or a type of reaction.
Table: Removals
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| post_id | int |
| remove_date | date |
+---------------+---------+
post_id is the primary key of this table.
Each row in this table indicates that some post was removed as a result of being reported or as a result of an admin review.
Write an SQL query to find the average for daily percentage of posts that got removed after being reported as spam, rounded to 2 decimal places.
The query result format is in the following example:
Actions table:
+---------+---------+-------------+--------+--------+
| user_id | post_id | action_date | action | extra |
+---------+---------+-------------+--------+--------+
| 1 | 1 | 2019-07-01 | view | null |
| 1 | 1 | 2019-07-01 | like | null |
| 1 | 1 | 2019-07-01 | share | null |
| 2 | 2 | 2019-07-04 | view | null |
| 2 | 2 | 2019-07-04 | report | spam |
| 3 | 4 | 2019-07-04 | view | null |
| 3 | 4 | 2019-07-04 | report | spam |
| 4 | 3 | 2019-07-02 | view | null |
| 4 | 3 | 2019-07-02 | report | spam |
| 5 | 2 | 2019-07-03 | view | null |
| 5 | 2 | 2019-07-03 | report | racism |
| 5 | 5 | 2019-07-03 | view | null |
| 5 | 5 | 2019-07-03 | report | racism |
+---------+---------+-------------+--------+--------+
Removals table:
+---------+-------------+
| post_id | remove_date |
+---------+-------------+
| 2 | 2019-07-20 |
| 3 | 2019-07-18 |
+---------+-------------+
Result table:
+-----------------------+
| average_daily_percent |
+-----------------------+
| 75.00 |
+-----------------------+
The percentage for 2019-07-04 is 50% because only one post of two spam reported posts was removed.
The percentage for 2019-07-02 is 100% because one post was reported as spam and it was removed.
The other days had no spam reports so the average is (50 + 100) / 2 = 75%
Note that the output is only one number and that we do not care about the remove dates.
with cte as
(
SELECT action_date,
COUNT(DISTINCT r.post_id) AS removed_post,
COUNT(DISTINCT a.post_id) AS total_post
FROM Actions a
LEFT JOIN Removals r
ON a.post_id = r.post_id
WHERE action = 'report' AND extra = 'spam'
GROUP BY action_date
) SELECT ROUND(AVG(cast(removed_post as float)/cast(total_post as float)) * 100, 2)
AS average_daily_percent from cte