1651. Hopper Company Queries III
Hard
LeetCode
Database
JIAKAOBO
LeetCode
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Problem
Table: Drivers
+-------------+---------+
| Column Name | Type |
+-------------+---------+
| driver_id | int |
| join_date | date |
+-------------+---------+
driver_id is the primary key for this table.
Each row of this table contains the driver's ID and the date they joined the Hopper company.
Table: Rides
+--------------+---------+
| Column Name | Type |
+--------------+---------+
| ride_id | int |
| user_id | int |
| requested_at | date |
+--------------+---------+
ride_id is the primary key for this table.
Each row of this table contains the ID of a ride, the user's ID that requested it, and the day they requested it.
There may be some ride requests in this table that were not accepted.
Table: AcceptedRides
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| ride_id | int |
| driver_id | int |
| ride_distance | int |
| ride_duration | int |
+---------------+---------+
ride_id is the primary key for this table.
Each row of this table contains some information about an accepted ride.
It is guaranteed that each accepted ride exists in the Rides table.
Write an SQL query to compute the average_ride_distance and average_ride_duration of every 3-month window starting from January - March 2020 to October - December 2020. Round average_ride_distance and average_ride_duration to the nearest two decimal places.
The average_ride_distance is calculated by summing up the total ride_distance values from the three months and dividing it by 3. The average_ride_duration is calculated in a similar way.
Return the result table ordered by month in ascending order, where month is the starting month’s number (January is 1, February is 2, etc.).
The query result format is in the following example.
Example 1:
Input:
Drivers table:
+-----------+------------+
| driver_id | join_date |
+-----------+------------+
| 10 | 2019-12-10 |
| 8 | 2020-1-13 |
| 5 | 2020-2-16 |
| 7 | 2020-3-8 |
| 4 | 2020-5-17 |
| 1 | 2020-10-24 |
| 6 | 2021-1-5 |
+-----------+------------+
Rides table:
+---------+---------+--------------+
| ride_id | user_id | requested_at |
+---------+---------+--------------+
| 6 | 75 | 2019-12-9 |
| 1 | 54 | 2020-2-9 |
| 10 | 63 | 2020-3-4 |
| 19 | 39 | 2020-4-6 |
| 3 | 41 | 2020-6-3 |
| 13 | 52 | 2020-6-22 |
| 7 | 69 | 2020-7-16 |
| 17 | 70 | 2020-8-25 |
| 20 | 81 | 2020-11-2 |
| 5 | 57 | 2020-11-9 |
| 2 | 42 | 2020-12-9 |
| 11 | 68 | 2021-1-11 |
| 15 | 32 | 2021-1-17 |
| 12 | 11 | 2021-1-19 |
| 14 | 18 | 2021-1-27 |
+---------+---------+--------------+
AcceptedRides table:
+---------+-----------+---------------+---------------+
| ride_id | driver_id | ride_distance | ride_duration |
+---------+-----------+---------------+---------------+
| 10 | 10 | 63 | 38 |
| 13 | 10 | 73 | 96 |
| 7 | 8 | 100 | 28 |
| 17 | 7 | 119 | 68 |
| 20 | 1 | 121 | 92 |
| 5 | 7 | 42 | 101 |
| 2 | 4 | 6 | 38 |
| 11 | 8 | 37 | 43 |
| 15 | 8 | 108 | 82 |
| 12 | 8 | 38 | 34 |
| 14 | 1 | 90 | 74 |
+---------+-----------+---------------+---------------+
Output:
+-------+-----------------------+-----------------------+
| month | average_ride_distance | average_ride_duration |
+-------+-----------------------+-----------------------+
| 1 | 21.00 | 12.67 |
| 2 | 21.00 | 12.67 |
| 3 | 21.00 | 12.67 |
| 4 | 24.33 | 32.00 |
| 5 | 57.67 | 41.33 |
| 6 | 97.33 | 64.00 |
| 7 | 73.00 | 32.00 |
| 8 | 39.67 | 22.67 |
| 9 | 54.33 | 64.33 |
| 10 | 56.33 | 77.00 |
+-------+-----------------------+-----------------------+
Explanation:
By the end of January --> average_ride_distance = (0+0+63)/3=21, average_ride_duration = (0+0+38)/3=12.67
By the end of February --> average_ride_distance = (0+63+0)/3=21, average_ride_duration = (0+38+0)/3=12.67
By the end of March --> average_ride_distance = (63+0+0)/3=21, average_ride_duration = (38+0+0)/3=12.67
By the end of April --> average_ride_distance = (0+0+73)/3=24.33, average_ride_duration = (0+0+96)/3=32.00
By the end of May --> average_ride_distance = (0+73+100)/3=57.67, average_ride_duration = (0+96+28)/3=41.33
By the end of June --> average_ride_distance = (73+100+119)/3=97.33, average_ride_duration = (96+28+68)/3=64.00
By the end of July --> average_ride_distance = (100+119+0)/3=73.00, average_ride_duration = (28+68+0)/3=32.00
By the end of August --> average_ride_distance = (119+0+0)/3=39.67, average_ride_duration = (68+0+0)/3=22.67
By the end of Septemeber --> average_ride_distance = (0+0+163)/3=54.33, average_ride_duration = (0+0+193)/3=64.33
By the end of October --> average_ride_distance = (0+163+6)/3=56.33, average_ride_duration = (0+193+38)/3=77.00
Code
with recursive month as (
select 1 as month
union
select month + 1 as month from month where month < 12
)
, month_rides as(
select
MONTH(r.requested_at) as month,
sum(a.ride_distance) as ride_distance,
sum(a.ride_duration) as ride_duration
from Rides r join AcceptedRides a on a.ride_id = r.ride_id
where YEAR(r.requested_at) = '2020'
group by month
# order by month asc
)
, every_month_rides as(
select
m.month,
ifnull(mr.ride_distance,0) as ride_distance,
ifnull(mr.ride_duration,0) as ride_duration
from month m left join month_rides mr on mr.month = m.month
# order by 1
)
# select * from month
# select * from month_rides
# select * from every_month_rides
select
t1.month as month,
round((t1.ride_distance + t2.ride_distance + t3.ride_distance)/3,2) as average_ride_distance,
round((t1.ride_duration + t2.ride_duration + t3.ride_duration)/3,2) as average_ride_duration
from every_month_rides t1
join every_month_rides t2
join every_month_rides t3
on t1.month = t2.month -1 and t2.month = t3.month -1
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