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IshaSQL

Foundations Track · Easy · 15 min

Queries Quality and Percentage

Table: Queries +-------------+---------+ | Column Name | Type | +-------------+---------+ | query_name | varchar | | result | varchar | | position | int | | ...

Foundations Track
Easy
15 min
aggregation
filtering

Company labels are directional practice context, not official interview guidance.

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Objective

Practice aggregation through a IshaSQL-tagged business scenario.

Approach

Use this track to lock in clean query structure, basic filtering logic, and confidence with grouped output.

Company context

Company labels are directional practice context, not official interview guidance.

Prereq: query basics
Prereq: filtering

Table: Queries +-------------+---------+ | Column Name | Type | +-------------+---------+ | query_name | varchar | | result | varchar | | position | int | | rating | int | +-------------+---------+ This table 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 a solution 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 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

Queries
query_name VARCHAR(255
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