Print Fill in the Blanks Game: Mastering SQL Aggregation Problems ()

amount total_sales SELECT FROM AS SUM sales

Problem 1 : Total Sales
Question : You have a table sales ( order_id INT , amount DECIMAL ) . Write a SQL query to calculate the total sales amount .

Solution :

____________________ ____________________ ( ____________________ ) ____________________ ____________________
____________________ ____________________ ;

SELECT SUM ( amount ) AS total_sales
FROM sales ;

Explanation : The SUM ( ) function aggregates the total sales by summing up all the amount values in the sales table .

amount FROM sales average_sale_amount AVG SELECT AS

Problem 2 : Average Sales per Order
Question : Calculate the average sales amount per order from the sales table .

Solution :

____________________ ____________________ ( ____________________ ) ____________________ ____________________
____________________ ____________________ ;

SELECT AVG ( amount ) AS average_sale_amount
FROM sales ;

Explanation : The AVG ( ) function calculates the average amount of sales by dividing the total sum of the amount column by the count of rows ( i . e . , number of orders ) .

FROM DISTINCT SELECT order_details COUNT product_id distinct_products AS

Problem 3 : Count of Distinct Products Sold
Question : Given a table order_details ( order_id INT , product_id INT ) , find the number of distinct products sold .

Solution :

____________________ ____________________ ( ____________________ ____________________ ) ____________________ ____________________
____________________ ____________________ ;

SELECT COUNT ( DISTINCT product_id ) AS distinct_products
FROM order_details ;

Explanation : COUNT ( DISTINCT product_id ) counts the unique product IDs in the order_details table , ignoring duplicates .

amount sales max_sale MIN MAX FROM amount AS min_sale AS SELECT

Problem 4 : Maximum and Minimum Sale
Question : Find both the largest and smallest sale amounts from the sales table .

Solution :

____________________ ____________________ ( ____________________ ) ____________________ ____________________ , ____________________ ( ____________________ ) ____________________ ____________________
____________________ ____________________ ;

SELECT MAX ( amount ) AS max_sale , MIN ( amount ) AS min_sale
FROM sales ;

Explanation : The MAX ( ) and MIN ( ) functions are used to find the highest and lowest values in the amount column of the sales table .

BY FROM YEAR sale_date total_sales SELECT ORDER AS FROM MONTH sale_date FROM EXTRACT sale_month SUM YEAR sale_date BY sale_month amount EXTRACT FROM sale_year sale_date FROM AS sales AS EXTRACT sale_year EXTRACT GROUP MONTH

Problem 5 : Grouped Sales by Month
Question : Assuming a table sales ( order_id INT , amount DECIMAL , sale_date DATE ) , calculate total sales for each month .

Solution :

____________________ ____________________ ( ____________________ ____________________ ____________________ ) ____________________ ____________________ ,
____________________ ( ____________________ ____________________ ____________________ ) ____________________ ____________________ ,
____________________ ( ____________________ ) ____________________ ____________________
____________________ ____________________
____________________ ____________________ ____________________ ( ____________________ ____________________ ____________________ ) , ____________________ ( ____________________ ____________________ ____________________ )
____________________ ____________________ ____________________ , ____________________ ;

SELECT EXTRACT ( YEAR FROM sale_date ) AS sale_year ,
EXTRACT ( MONTH FROM sale_date ) AS sale_month ,
SUM ( amount ) AS total_sales
FROM sales
GROUP BY EXTRACT ( YEAR FROM sale_date ) , EXTRACT ( MONTH FROM sale_date )
ORDER BY sale_year , sale_month ;

Explanation : The SUM ( ) function is used to aggregate sales per month , grouped by year and month extracted from sale_date . The GROUP BY clause groups the data into sets that share the same year and month so that SUM ( ) can compute totals for each group .