LeetCode-in-Java

3601. Find Drivers with Improved Fuel Efficiency

Medium

Table: drivers

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| driver_id   | int     |
| driver_name | varchar |
+-------------+---------+
driver_id is the unique identifier for this table. Each row contains information about a driver. 

Table: trips

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| trip_id       | int     |
| driver_id     | int     |
| trip_date     | date    |
| distance_km   | decimal |
| fuel_consumed | decimal |
+---------------+---------+
trip_id is the unique identifier for this table.
Each row represents a trip made by a driver, including the distance traveled and fuel consumed for that trip. 

Write a solution to find drivers whose fuel efficiency has improved by comparing their average fuel efficiency in the first half of the year with the second half of the year.

• Calculate fuel efficiency as distance_km / fuel_consumed for each trip
• First half: January to June, Second half: July to December
• Only include drivers who have trips in both halves of the year
• Calculate the efficiency improvement as (second_half_avg - first_half_avg)
• Round all results to 2 decimal places

Return the result table ordered by efficiency improvement in descending order, then by driver name in ascending order.

The result format is in the following example.

Example:

Input:

drivers table:

+-----------+---------------+
| driver_id | driver_name   |
+-----------+---------------+
| 1         | Alice Johnson |
| 2         | Bob Smith     |
| 3         | Carol Davis   |
| 4         | David Wilson  |
| 5         | Emma Brown    |
+-----------+---------------+ 

trips table:

+---------+-----------+------------+-------------+---------------+
| trip_id | driver_id | trip_date  | distance_km | fuel_consumed |
+---------+-----------+------------+-------------+---------------+
| 1       | 1         | 2023-02-15 | 120.5       | 10.2          |
| 2       | 1         | 2023-03-20 | 200.0       | 16.5          |
| 3       | 1         | 2023-08-10 | 150.0       | 11.0          |
| 4       | 1         | 2023-09-25 | 180.0       | 12.5          |
| 5       | 2         | 2023-01-10 | 100.0       | 9.0           |
| 6       | 2         | 2023-04-15 | 250.0       | 22.0          |
| 7       | 2         | 2023-10-05 | 200.0       | 15.0          |
| 8       | 3         | 2023-03-12 | 80.0        | 8.5           |
| 9       | 3         | 2023-05-18 | 90.0        | 9.2           |
| 10      | 4         | 2023-07-22 | 160.0       | 12.8          |
| 11      | 4         | 2023-11-30 | 140.0       | 11.0          |
| 12      | 5         | 2023-02-28 | 110.0       | 11.5          |
+---------+-----------+------------+-------------+---------------+ 

Output:

+-----------+---------------+------------------+-------------------+------------------------+
| driver_id | driver_name   | first_half_avg   | second_half_avg   | efficiency_improvement |
+-----------+---------------+------------------+-------------------+------------------------+
| 2         | Bob Smith     | 11.24            | 13.33             | 2.10                   |
| 1         | Alice Johnson | 11.97            | 14.02             | 2.05                   |
+-----------+---------------+------------------+-------------------+------------------------+ 

Explanation:

• Alice Johnson (driver_id = 1):
  • First half trips (Jan-Jun): Feb 15 (120.5/10.2 = 11.81), Mar 20 (200.0/16.5 = 12.12)
  • First half average efficiency: (11.81 + 12.12) / 2 = 11.97
  • Second half trips (Jul-Dec): Aug 10 (150.0/11.0 = 13.64), Sep 25 (180.0/12.5 = 14.40)
  • Second half average efficiency: (13.64 + 14.40) / 2 = 14.02
  • Efficiency improvement: 14.02 - 11.97 = 2.05
• Bob Smith (driver_id = 2):
  • First half trips: Jan 10 (100.0/9.0 = 11.11), Apr 15 (250.0/22.0 = 11.36)
  • First half average efficiency: (11.11 + 11.36) / 2 = 11.24
  • Second half trips: Oct 5 (200.0/15.0 = 13.33)
  • Second half average efficiency: 13.33
  • Efficiency improvement: 13.33 - 11.24 = 2.09
• Drivers not included:
  • Carol Davis (driver_id = 3): Only has trips in first half (Mar, May)
  • David Wilson (driver_id = 4): Only has trips in second half (Jul, Nov)
  • Emma Brown (driver_id = 5): Only has trips in first half (Feb)

The output table is ordered by efficiency improvement in descending order then by name in ascending order.

Solution

# Write your MySQL query statement below
WITH main_process AS (
    SELECT 
        t.driver_id,
        d.driver_name,
        ROUND(AVG(t.distance_km / t.fuel_consumed), 2) AS first_half_avg,
        ROUND(AVG(t1.distance_km / t1.fuel_consumed), 2) AS second_half_avg,
        ROUND(
            AVG(t1.distance_km / t1.fuel_consumed) - AVG(t.distance_km / t.fuel_consumed),
            2
        ) AS efficiency_improvement
    FROM 
        trips t
        INNER JOIN trips t1 ON t.driver_id = t1.driver_id
        INNER JOIN drivers d ON t.driver_id = d.driver_id
        AND EXTRACT(MONTH FROM t.trip_date) BETWEEN 1 AND 6
        AND EXTRACT(MONTH FROM t1.trip_date) BETWEEN 7 AND 12
    GROUP BY 
        t.driver_id,
        d.driver_name
    ORDER BY 
        efficiency_improvement DESC,
        d.driver_name ASC
)
SELECT 
    driver_id,
    driver_name,
    first_half_avg,
    second_half_avg,
    efficiency_improvement
FROM main_process
WHERE efficiency_improvement > 0;

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