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SQL Test 

1. From the following table, write a SQL query to find the details of those salespeople who come from the 'Paris' City or 'Rome' City. Return salesman_id, name, city, commission.
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:
salesman_id	name		city	commission
5002		Nail Knite	Paris	0.13
5006		Mc Lyon		Paris	0.14
5007		Paul Adam	Rome	0.13


2. From the following table, write a SQL query to find the details of the salespeople who come from either 'Paris' or 'Rome'. Return salesman_id, name, city, commission. 
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:
salesman_id	name		city	commission
5002		Nail Knite	Paris	0.13
5006		Mc Lyon		Paris	0.14
5007		Paul Adam	Rome	0.13

3. From the following table, write a SQL query to find the details of those salespeople who live in cities other than Paris and Rome. Return salesman_id, name, city, commission.  
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:
salesman_id	name		city		commission
5001		James Hoog	New York	0.15
5005		Pit Alex	London		0.11
5003		Lauson Hen	San Jose	0.12

4. From the following table, write a SQL query to retrieve the details of all customers whose ID belongs to any of the values 3007, 3008 or 3009. Return customer_id, cust_name, city, grade, and salesman_id.  
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:
customer_id	cust_name	 city		grade	salesman_id
3007		Brad Davis	 New York	200		5001
3008		Julian Green   London		300		5002
3009		Geoff Cameron	Berlin		100		5003


5. From the following table, write a SQL query to find salespeople who receive commissions between 0.12 and 0.14 (begin and end values are included). Return salesman_id, name, city, and commission.  
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:
salesman_id	name		city	commission
5002		Nail Knite	Paris	0.13
5006		Mc Lyon		Paris	0.14
5007		Paul Adam	Rome	0.13
5003		Lauson Hen	San Jose0.12





6. From the following table, write a SQL query to select orders between 500 and 4000 (begin and end values are included). Exclude orders amount 948.50 and 1983.43. Return ord_no, purch_amt, ord_date, customer_id, and salesman_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_no	purch_amt	ord_date	customer_id	salesman_id
70005	2400.60		2012-07-27	3007		5001
70003	2480.40		2012-10-10	3009		5003
70013	3045.60		2012-04-25	3002		5001


7. From the following table, write a SQL query to retrieve the details of the salespeople whose names begin with any letter between 'A' and 'L' (not inclusive). Return salesman_id, name, city, commission. 
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:
salesman_id	name		city		commission
5001		James Hoog	New York	0.15

8. From the following table, write a SQL query to find the details of all salespeople except those whose names begin with any letter between 'A' and 'L' (not inclusive). Return salesman_id, name, city, commission.  
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:
salesman_id	name		city		commission
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


9. From the following table, write a SQL query to retrieve the details of the customers whose names begins with the letter 'B'. Return customer_id, cust_name, city, grade, salesman_id.. 
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:
customer_id	cust_name	city		grade	salesman_id
3007		Brad Davis	New York	200	5001
3001		Brad Guzan	London			5005


10. From the following table, write a SQL query to find the details of the customers whose names end with the letter 'n'. Return customer_id, cust_name, city, grade, salesman_id.
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:
customer_id	cust_name		city	grade	salesman_id
3008		Julian Green		London	300	5002
3004		Fabian Johnson		Paris	300	5006
3009		Geoff Cameron		Berlin	100	5003
3001		Brad Guzan		London		5005

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