LeetCode in Kotlin
601. Human Traffic of Stadium
Hard
SQL Schema
Table: Stadium
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| id | int |
| visit_date | date |
| people | int |
+---------------+---------+
visit_date is the primary key for this table.
Each row of this table contains the visit date and visit id to the stadium with the number of people during
the visit.
No two rows will have the same visit_date, and as the id increases, the dates increase as well.
Write an SQL query to display the records with three or more rows with consecutive id’s, and the number of people is greater than or equal to 100 for each.
Return the result table ordered by visit_date in ascending order.
The query result format is in the following example.
Example 1:
Input:
Stadium table:
+------+------------+-----------+
| id | visit_date | people |
+------+------------+-----------+
| 1 | 2017-01-01 | 10 |
| 2 | 2017-01-02 | 109 |
| 3 | 2017-01-03 | 150 |
| 4 | 2017-01-04 | 99 |
| 5 | 2017-01-05 | 145 |
| 6 | 2017-01-06 | 1455 |
| 7 | 2017-01-07 | 199 |
| 8 | 2017-01-09 | 188 |
+------+------------+-----------+
Output:
+------+------------+-----------+
| id | visit_date | people |
+------+------------+-----------+
| 5 | 2017-01-05 | 145 |
| 6 | 2017-01-06 | 1455 |
| 7 | 2017-01-07 | 199 |
| 8 | 2017-01-09 | 188 |
+------+------------+-----------+
Explanation:
The four rows with ids 5, 6, 7, and 8 have consecutive ids and each of them has >= 100 people attended.
Note that row 8 was included even though the visit\_date was not the next day after row 7.
The rows with ids 2 and 3 are not included because we need at least three consecutive ids.
Solution
# Write your MySQL query statement below
with new_group as(
select id,visit_date,people,id - row_number() over(order by id) as new
from Stadium
where people >= 100
)
select id,visit_date,people
from new_group
where new in(
select new
from new_group
group by new
having count(id) >= 3
);