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SQL Exercises with Solution - VIEW

SQL [16 exercises with solution]

1. From the following table, create a view for those salespeople who belong to the city of New York. 

Sample table: salesman


Sample Output:

sqlpractice=# select * from newyorkstaff;
 salesman_id |    name    |   city   | commission
-------------+------------+----------+------------
        5001 | James Hoog | New York |       0.15
(1 row)

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2. From the following table, create a view for all salespersons. Return salesperson ID, name, and city.  

Sample table: salesman


output

sqlpractice=# SELECT *
sqlpractice-# FROM salesown;
 salesman_id |     name     |   city
-------------+--------------+----------
        5002 | Nail Knite   | Paris
        5005 | Pit Alex     | London
        5006 | Mc Lyon      | Paris
        5003 | Lauson Hense |
        5001 | James Hoog   | New York
        5007 | Paul Adam    | London
(6 rows)

Click me to see the solution

3. From the following table, create a view to locate the salespeople in the city 'New York'.

Sample table: salesman


output:

sqlpractice=# SELECT *
sqlpractice-# FROM newyorkstaff
sqlpractice-# WHERE commission > .13;
 salesman_id | name       |   city   | commission
-------------+------------+----------+------------
        5001 | James Hoog | New York |       0.15
(1 row)

Click me to see the solution

4. From the following table, create a view that counts the number of customers in each grade.  

Sample table: customer


output:

sqlpractice=# SELECT *
sqlpractice-# FROM gradecount
sqlpractice-# WHERE number = 2;
 grade | number
-------+--------
       |      2
   200 |      2
   300 |      2
(3 rows)

Click me to see the solution

5. From the following table, create a view to count the number of unique customers, compute the average and the total purchase amount of customer orders by each date.

Sample table : orders


output:

sqlpractice=# SELECT *
sqlpractice-# FROM totalforday;
  ord_date  | count |          avg          |   sum
------------+-------+-----------------------+---------
 2012-04-25 |     1 | 3045.6000000000000000 | 3045.60
 2012-06-27 |     1 |  250.4500000000000000 |  250.45
 2012-07-27 |     1 | 2400.6000000000000000 | 2400.60
 2012-08-17 |     3 |   95.2633333333333333 |  285.79
 2012-09-10 |     3 | 2326.3833333333333333 | 6979.15
 2012-09-22 |     1 |  322.0000000000000000 |  322.00
 2012-10-05 |     2 |  132.6300000000000000 |  265.26
 2012-10-10 |     2 | 2231.9150000000000000 | 4463.83
(8 rows)

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6. From the following tables, create a view to get the salesperson and customer by name. Return order name, purchase amount, salesperson ID, name, customer name.

Sample table: salesman


Sample table: customer


Sample table: orders


output:

sqlpractice=# SELECT *
sqlpractice-# FROM nameorders
sqlpractice-# WHERE name = 'Mc Lyon';
 ord_no | purch_amt | salesman_id |  name   |   cust_name
--------+-----------+-------------+---------+----------------
  70010 |   1983.43 |        5006 | Mc Lyon | Fabian Johnson
  70015 |    322.00 |        5006 | Mc Lyon | Varun
(2 rows)

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7. From the following table, create a view to find the salesperson who handles a customer who makes the highest order of the day. Return order date, salesperson ID, name.

Sample table: salesman


Sample table: orders


output:

sqlpractice=# SELECT *
sqlpractice-# FROM elitsalesman;
  ord_date  | salesman_id |     name
------------+-------------+--------------
 2012-08-17 |        5003 | Lauson Hense
 2012-07-27 |        5001 | James Hoog 
 2012-09-10 |        5001 | James Hoog 
 2012-10-10 |        5003 | Lauson Hense
 2012-06-27 |        5002 | Nail Knite
 2012-04-25 |        5001 | James Hoog 
 2012-10-05 |        5002 | Nail Knite
 2012-09-22 |        5006 | Mc Lyon
(8 rows)

Click me to see the solution

8. From the following table, create a view to find the salesperson who deals with the customer with the highest order at least three times per day. Return salesperson ID and name.

Sample table: customer


Sample table: elitsalesman


output:

sqlpractice=# SELECT *
sqlpractice-# FROM incentive;
 salesman_id | name
-------------+------------
        5001 | James Hoog 
(1 row)

Click me to see the solution

9. From the following table, create a view to find all the customers who have the highest grade. Return all the fields of customer.

Sample table: customer


output:

sqlex=# select * from highgrade;
 customer_id |   cust_name    |  city  | grade | salesman_id 
-------------+----------------+--------+-------+-------------
        3008 | Julian Green   | London |   300 |        5002
        3004 | Fabian Johnson | Paris  |   300 |        5006
(2 rows)

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10. From the following table, create a view to count the number of salespeople in each city. Return city, number of salespersons.

Sample table: salesman


output:

sqlpractice-# FROM citynum;
   city   | count
----------+-------
 London   |     1
 New York |     1
 Paris    |     2
 Rome     |     1
          |     1
(5 rows)

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11. From the following table, create a view to compute the average purchase amount and total purchase amount for each salesperson. Return name, average purchase and total purchase amount. (Assume all names are unique.).

Sample table: salesman


Sample table: orders


output:

sqlpractice=# SELECT *
sqlpractice-# FROM norders;
     name     |          avg          |   sum
--------------+-----------------------+----------
 Mc Lyon      | 1152.7150000000000000 |  2305.43
 James Hoog   | 2817.8650000000000000 | 11271.46
 Pit Alex     |  270.6500000000000000 |   270.65
 Lauson Hense | 1295.4500000000000000 |  2590.90
 Paul Adam    |   87.6450000000000000 |   175.29
 Nail Knite   |  466.3166666666666667 |  1398.95
(6 rows)

Click me to see the solution

12. From the following table, create a view to identify salespeople who work with multiple clients. Return all the fields of salesperson.

Sample table: salesman


Sample table: customer


output:

sqlpractice=# SELECT *
sqlpractice-# FROM mcustomer;
 salesman_id |     name     |   city   | commission
-------------+--------------+----------+------------
        5002 | Nail Knite   | Paris    |       0.13
        5001 | James Hoog   | New York |       0.15
(2 rows)

Click me to see the solution

13. From the following table, create a view that shows all matching customers with salespeople, ensuring that at least one customer in the city of the customer is served by the salesperson in the city of the salesperson.

Sample table: salesman


Sample table: customer


output:

sqlpractice=# SELECT *
sqlpractice-# FROM citymatch;
  custcity  | salescity
------------+-----------
 Seattle    | Paris
 Moscow     | Rome
 New York   | New York
 NC         |
 Paris      | Paris
 ....
 

Click me to see the solution

14. From the following table, create a view to display the number of orders per day. Return order date and number of orders.

Sample table: orders


output:

sqlpractice=# SELECT *
sqlpractice-# FROM dateord;
  ord_date  | odcount
------------+---------
 2012-10-05 |       2
 2012-08-17 |       3
 2012-07-27 |       1
 2012-09-22 |       1
 ....
 

Click me to see the solution

15. From the following table, create a view to find the salespeople who placed orders on October 10th, 2012. Return all the fields of salesperson.

Sample table: salesman


Sample table: orders


output:

sqlpractice=# SELECT *
sqlpractice-# FROM salesmanonoct;
 salesman_id |     name     | city  | commission
-------------+--------------+-------+------------
        5006 | Mc Lyon      | Paris |       0.14
        5003 | Lauson Hense |       |       0.12
(2 rows)

Click me to see the solution

16. From the following table, create a view to find the salespersons who issued orders on either August 17th, 2012 or October 10th, 2012. Return salesperson ID, order number and customer ID.

Sample table: orders


output:

sqlpractice=# SELECT *
sqlpractice-# FROM sorder;
 salesman_id | ord_no | customer_id
-------------+--------+-------------
        5003 |  70004 |        3009
        5006 |  70010 |        3004
        5003 |  70003 |        3009
        5007 |  70011 |        3003
        5007 |  70014 |        3005
(5 rows)

Click me to see the solution

More to Come!

Query visualizations are generated using Postgres Explain Visualizer (pev)

Do not submit any solution of the above exercises at here, if you want to contribute go to the appropriate exercise page.



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