SQL Functions and Group by - Exercises, Practice, Solution
This resource offers a total of 125 SQL Aggregate Functions problems for practice. It includes 25 main exercises, each accompanied by solutions, detailed explanations, and four related problems.
[An Editor is available at the bottom of the page to write and execute the scripts.]
1. Calculate Total Purchase Amount of All Orders
From the following table, write a SQL query to calculate total purchase amount of all orders. Return total purchase amount.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
sum 17541.18
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2. Calculate Average Purchase Amount of All Orders
From the following table, write a SQL query to calculate the average purchase amount of all orders. Return average purchase amount.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
avg 1461.7650000000000000
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3. Count the Number of Unique Salespeople
From the following table, write a SQL query that counts the number of unique salespeople. Return number of salespeople.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
count 6
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4. Count the Number of Customers
From the following table, write a SQL query to count the number of customers. Return number of customers.
Sample table: customer
customer_id | cust_name | city | grade | salesman_id
-------------+----------------+------------+-------+-------------
3002 | Nick Rimando | New York | 100 | 5001
3007 | Brad Davis | New York | 200 | 5001
3005 | Graham Zusi | California | 200 | 5002
3008 | Julian Green | London | 300 | 5002
3004 | Fabian Johnson | Paris | 300 | 5006
3009 | Geoff Cameron | Berlin | 100 | 5003
3003 | Jozy Altidor | Moscow | 200 | 5007
3001 | Brad Guzan | London | | 5005
Sample Output:
count 8
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5. Count Customers with at Least One Grade
From the following table, write a SQL query to determine the number of customers who received at least one grade for their activity.
Sample table: customer
customer_id | cust_name | city | grade | salesman_id
-------------+----------------+------------+-------+-------------
3002 | Nick Rimando | New York | 100 | 5001
3007 | Brad Davis | New York | 200 | 5001
3005 | Graham Zusi | California | 200 | 5002
3008 | Julian Green | London | 300 | 5002
3004 | Fabian Johnson | Paris | 300 | 5006
3009 | Geoff Cameron | Berlin | 100 | 5003
3003 | Jozy Altidor | Moscow | 200 | 5007
3001 | Brad Guzan | London | | 5005
Sample Output:
count 7
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6. Find Maximum Purchase Amount
From the following table, write a SQL query to find the maximum purchase amount.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
max 5760.00
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7. Find Minimum Purchase Amount
From the following table, write a SQL query to find the minimum purchase amount.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
min 65.26
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8. Find Highest Customer Grade in Each City
From the following table, write a SQL query to find the highest grade of the customers in each city. Return city, maximum grade.
Sample table: customer
customer_id | cust_name | city | grade | salesman_id
-------------+----------------+------------+-------+-------------
3002 | Nick Rimando | New York | 100 | 5001
3007 | Brad Davis | New York | 200 | 5001
3005 | Graham Zusi | California | 200 | 5002
3008 | Julian Green | London | 300 | 5002
3004 | Fabian Johnson | Paris | 300 | 5006
3009 | Geoff Cameron | Berlin | 100 | 5003
3003 | Jozy Altidor | Moscow | 200 | 5007
3001 | Brad Guzan | London | | 5005
Sample Output:
city max London 300 Paris 300 New York 200 California 200 Berlin 100 Moscow 200
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9. Find Highest Purchase Amount Ordered by Each Customer
From the following table, write a SQL query to find the highest purchase amount ordered by each customer. Return customer ID, maximum purchase amount.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
customer_id max 3007 2400.60 3008 250.45 3002 5760.00 3001 270.65 3009 2480.40 3004 1983.43 3003 75.29 3005 948.50
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10. Highest Purchase by Customer on Date
From the following table, write a SQL query to find the highest purchase amount ordered by each customer on a particular date. Return, order date and highest purchase amount.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
customer_id ord_date max 3002 2012-10-05 65.26 3003 2012-08-17 75.29 3005 2012-10-05 150.50 3007 2012-07-27 2400.60 3009 2012-08-17 110.50 3001 2012-09-10 270.65 3002 2012-09-10 5760.00 3005 2012-09-10 948.50 3009 2012-10-10 2480.40 3008 2012-06-27 250.45 3004 2012-10-10 1983.43 3002 2012-04-25 3045.60
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11. Highest Purchase Amount by Salesperson on '2012-08-17'
From the following table, write a SQL query to determine the highest purchase amount made by each salesperson on '2012-08-17'. Return salesperson ID, purchase amount
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
salesman_id max 5003 110.50 5007 75.29
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12. Highest Purchase Amount by Customer on Specific Date
From the following table, write a SQL query to find the highest order (purchase) amount by each customer on a particular order date. Filter the result by highest order (purchase) amount above 2000.00. Return customer id, order date and maximum purchase amount.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
customer_id ord_date max 3007 2012-07-27 2400.60 3002 2012-09-10 5760.00 3009 2012-10-10 2480.40 3002 2012-04-25 3045.60
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13. Max Purchase Amount by Customer and Order Date (2000-6000)
From the following table, write a SQL query to find the maximum order (purchase) amount in the range 2000 - 6000 (Begin and end values are included.) by combination of each customer and order date. Return customer id, order date and maximum purchase amount.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
customer_id ord_date max 3007 2012-07-27 2400.60 3002 2012-09-10 5760.00 3009 2012-10-10 2480.40 3002 2012-04-25 3045.60
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14. Max Purchase Amount by Customer and Order Date (Filter)
From the following table, write a SQL query to find the maximum order (purchase) amount based on the combination of each customer and order date. Filter the rows for maximum order (purchase) amount is either 2000, 3000, 5760, 6000. Return customer id, order date and maximum purchase amount.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
customer_id ord_date max 3002 2012-09-10 5760.00
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15. Max Purchase Amount for Customers (ID Range 3002-3007)
From the following table, write a SQL query to determine the maximum order amount for each customer. The customer ID should be in the range 3002 and 3007(Begin and end values are included.). Return customer id and maximum purchase amount.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
customer_id max 3002 5760.00 3007 2400.60 3004 1983.43 3003 75.29 3005 948.50
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16. Max Purchase > 1000 for Customers (ID 3002-3007)
From the following table, write a SQL query to find the maximum order (purchase) amount for each customer. The customer ID should be in the range 3002 and 3007(Begin and end values are included.). Filter the rows for maximum order (purchase) amount is higher than 1000. Return customer id and maximum purchase amount.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
customer_id max 3002 5760.00 3007 2400.60 3004 1983.43
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17. Max Purchase by Salesperson (ID 5003-5008)
From the following table, write a SQL query to determine the maximum order (purchase) amount generated by each salesperson. Filter the rows for the salesperson ID is in the range 5003 and 5008 (Begin and end values are included.). Return salesperson id and maximum purchase amount.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
salesman_id max 5005 270.65 5003 2480.40 5007 75.29 5006 1983.43
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18. Count Orders on '2012-08-17'
From the following table, write a SQL query to count all the orders generated on '2012-08-17'. Return number of orders.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
count 2
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19. Count Salespeople in a City
From the following table, write a SQL query to count the number of salespeople in a city. Return number of salespeople.
Sample table: salesman
salesman_id | name | city | commission
-------------+------------+----------+------------
5001 | James Hoog | New York | 0.15
5002 | Nail Knite | Paris | 0.13
5005 | Pit Alex | London | 0.11
5006 | Mc Lyon | Paris | 0.14
5007 | Paul Adam | Rome | 0.13
5003 | Lauson Hen | San Jose | 0.12
Sample Output:
count 6
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20. Count Orders by Order Date and Salesperson
From the following table, write a SQL query to count the number of orders based on the combination of each order date and salesperson. Return order date, salesperson id.
Sample table: orders
ord_no purch_amt ord_date customer_id salesman_id ---------- ---------- ---------- ----------- ----------- 70001 150.5 2012-10-05 3005 5002 70009 270.65 2012-09-10 3001 5005 70002 65.26 2012-10-05 3002 5001 70004 110.5 2012-08-17 3009 5003 70007 948.5 2012-09-10 3005 5002 70005 2400.6 2012-07-27 3007 5001 70008 5760 2012-09-10 3002 5001 70010 1983.43 2012-10-10 3004 5006 70003 2480.4 2012-10-10 3009 5003 70012 250.45 2012-06-27 3008 5002 70011 75.29 2012-08-17 3003 5007 70013 3045.6 2012-04-25 3002 5001
Sample Output:
ord_date salesman_id count 2012-07-27 5001 1 2012-08-17 5007 1 2012-04-25 5001 1 2012-09-10 5002 1 2012-10-05 5002 1 2012-10-10 5003 1 2012-09-10 5005 1 2012-08-17 5003 1 2012-06-27 5002 1 2012-09-10 5001 1 2012-10-05 5001 1 2012-10-10 5006 1
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21. Calculate Average Product Price
From the following table, write a SQL query to calculate the average product price. Return average product price.
Sample table: item_mast
PRO_ID PRO_NAME PRO_PRICE PRO_COM
------- ------------------------- -------------- ----------
101 Mother Board 3200.00 15
102 Key Board 450.00 16
103 ZIP drive 250.00 14
104 Speaker 550.00 16
105 Monitor 5000.00 11
106 DVD drive 900.00 12
107 CD drive 800.00 12
108 Printer 2600.00 13
109 Refill cartridge 350.00 13
110 Mouse 250.00 12
Sample Output:
Average Price 1435.0000000000000000
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22. Count Products with Price >= 350
From the following table, write a SQL query to count the number of products whose price are higher than or equal to 350. Return number of products.
Sample table: item_mast
PRO_ID PRO_NAME PRO_PRICE PRO_COM
------- ------------------------- -------------- ----------
101 Mother Board 3200.00 15
102 Key Board 450.00 16
103 ZIP drive 250.00 14
104 Speaker 550.00 16
105 Monitor 5000.00 11
106 DVD drive 900.00 12
107 CD drive 800.00 12
108 Printer 2600.00 13
109 Refill cartridge 350.00 13
110 Mouse 250.00 12
Sample Output:
Number of Products 8
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23. Average Price for Unique Companies
From the following table, write a SQL query to compute the average price for unique companies. Return average price and company id.
Sample table: item_mast
PRO_ID PRO_NAME PRO_PRICE PRO_COM
------- ------------------------- -------------- ----------
101 Mother Board 3200.00 15
102 Key Board 450.00 16
103 ZIP drive 250.00 14
104 Speaker 550.00 16
105 Monitor 5000.00 11
106 DVD drive 900.00 12
107 CD drive 800.00 12
108 Printer 2600.00 13
109 Refill cartridge 350.00 13
110 Mouse 250.00 12
Sample Output:
Average Price Company ID 250.0000000000000000 14 650.0000000000000000 12 3200.0000000000000000 15 5000.0000000000000000 11 1475.0000000000000000 13 500.0000000000000000 16
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24. Sum of Allotment Amount for All Departments
From the following table, write a SQL query to compute the sum of the allotment amount of all departments. Return sum of the allotment amount.
Sample table: emp_department
DPT_CODE DPT_NAME DPT_ALLOTMENT
-------- --------------- -------------
57 IT 65000
63 Finance 15000
47 HR 240000
27 RD 55000
89 QC 75000
Sample Output:
sum 450000
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25. Count of Employees in Each Department
From the following table, write a SQL query to count the number of employees in each department. Return department code and number of employees.
Sample table: emp_details
EMP_IDNO EMP_FNAME EMP_LNAME EMP_DEPT --------- --------------- --------------- ---------- 127323 Michale Robbin 57 526689 Carlos Snares 63 843795 Enric Dosio 57 328717 Jhon Snares 63 444527 Joseph Dosni 47 659831 Zanifer Emily 47 847674 Kuleswar Sitaraman 57 748681 Henrey Gabriel 47 555935 Alex Manuel 57 539569 George Mardy 27 733843 Mario Saule 63 631548 Alan Snappy 27 839139 Maria Foster 57
Sample Output:
emp_dept count 27 2 57 5 47 3 63 3
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Practice Online
More to Come !
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Do not submit any solution of the above exercises at here, if you want to contribute go to the appropriate exercise page.