SQL Exercises with Solution - VIEW

Last update on September 14 2021 11:01:29 (UTC/GMT +8 hours)

SQL [16 exercises with solution]

1. From the following table, create a view for those salespersons belong to the city '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)

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3. From the following table, create a view to find the salespersons of 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)

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4. From the following table, create a view to count 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)

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5. From the following table, create a view to count the number of unique customer, compute average and 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 tables, create a view to find the salesperson who handles a customer who makes the highest order of a 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)

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8. From the following tables, create a view to find the salesperson who handles the customer with the highest order, at least 3 times on a 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)

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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 number of the salesperson 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 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)

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12. From the following tables, create a view to find those salespeople who handle more than one customer. 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)

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13. From the following tables, create a view that shows all matches of customers with salesperson such that at least one customer in the city of customer served by a 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
 ....

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14. From the following table, create a view to get number of orders in each 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
 ....

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15. From the following tables, create a view to find the salespersons who issued 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)

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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)

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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.