LeetCode in Kotlin
1211. Queries Quality and Percentage
Easy
SQL Schema
Table: Queries
+-------------+---------+
| Column Name | Type |
+-------------+---------+
| query_name | varchar |
| result | varchar |
| position | int |
| rating | int |
+-------------+---------+
There is no primary key for this table, it may have duplicate rows. This table contains information collected from some queries on a database. The position column has a value from 1 to 500. The rating column has a value from 1 to 5. Query with rating less than 3 is a poor query.
We define query quality as:
The average of the ratio between query rating and its position.
We also define poor query percentage as:
The percentage of all queries with rating less than 3.
Write an SQL query to find each query_name, the quality and poor_query_percentage.
Both quality and poor_query_percentage should be rounded to 2 decimal places.
Return the result table in any order.
The query result format is in the following example.
Example 1:
Input: Queries table:
+------------+-------------------+----------+--------+
| query_name | result | position | rating |
+------------+-------------------+----------+--------+
| Dog | Golden Retriever | 1 | 5 |
| Dog | German Shepherd | 2 | 5 |
| Dog | Mule | 200 | 1 |
| Cat | Shirazi | 5 | 2 |
| Cat | Siamese | 3 | 3 |
| Cat | Sphynx | 7 | 4 |
+------------+-------------------+----------+--------+
Output:
+------------+---------+-----------------------+
| query_name | quality | poor_query_percentage |
+------------+---------+-----------------------+
| Dog | 2.50 | 33.33 |
| Cat | 0.66 | 33.33 |
+------------+---------+-----------------------+
Explanation:
Dog queries quality is ((5 / 1) + (5 / 2) + (1 / 200)) / 3 = 2.50
Dog queries poor_ query_percentage is (1 / 3) * 100 = 33.33
Cat queries quality equals ((2 / 5) + (3 / 3) + (4 / 7)) / 3 = 0.66
Cat queries poor_ query_percentage is (1 / 3) * 100 = 33.33
Solution
# Write your MySQL query statement below
select query_name,
ROUND(AVG(rating / position), 2) AS quality,
round(SUM(rating<3)/count(query_name)*100,2) as poor_query_percentage
from queries
group by query_name;