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SQL Exercise: All customers will be served by a salesman from a city

SQL JOINS: Exercise-18 with Solution

Write a SQL statement to create a Cartesian product between salesperson and customer, i.e. each salesperson will appear for all customers and vice versa for that salesperson who belongs to that city.

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 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 Solution:

-- Selecting all columns from the Cartesian product of the 'salesman' and 'customer' tables
SELECT * 
-- Specifying the tables to perform the cross join ('salesman' as 'a' and 'customer' as 'b')
FROM salesman a 
CROSS JOIN customer b 
-- Filtering the results based on the condition that the 'city' in 'salesman' is not null
WHERE a.city IS NOT NULL;

Output of the Query:

salesman_id	name	city		commission	customer_id	cust_name	city		grade	salesman_id
5001	James Hoog	New York	0.15		3002		Nick Rimando	New York	100	5001
5002	Nail Knite	Paris		0.13		3002		Nick Rimando	New York	100	5001
5005	Pit Alex	London		0.11		3002		Nick Rimando	New York	100	5001
5006	Mc Lyon		Paris		0.14		3002		Nick Rimando	New York	100	5001
5007	Paul Adam	Rome		0.13		3002		Nick Rimando	New York	100	5001
5003	Lauson Hen	San Jose	0.12		3002		Nick Rimando	New York	100	5001
5001	James Hoog	New York	0.15		3007		Brad Davis	New York	200	5001
5002	Nail Knite	Paris		0.13		3007		Brad Davis	New York	200	5001
5005	Pit Alex	London		0.11		3007		Brad Davis	New York	200	5001
5006	Mc Lyon		Paris		0.14		3007		Brad Davis	New York	200	5001
5007	Paul Adam	Rome		0.13		3007		Brad Davis	New York	200	5001
5003	Lauson Hen	San Jose	0.12		3007		Brad Davis	New York	200	5001
5001	James Hoog	New York	0.15		3005		Graham Zusi	California	200	5002
5002	Nail Knite	Paris		0.13		3005		Graham Zusi	California	200	5002
5005	Pit Alex	London		0.11		3005		Graham Zusi	California	200	5002
5006	Mc Lyon		Paris		0.14		3005		Graham Zusi	California	200	5002
5007	Paul Adam	Rome		0.13		3005		Graham Zusi	California	200	5002
5003	Lauson Hen	San Jose	0.12		3005		Graham Zusi	California	200	5002
5001	James Hoog	New York	0.15		3008		Julian Green	London		300	5002
5002	Nail Knite	Paris		0.13		3008		Julian Green	London		300	5002
5005	Pit Alex	London		0.11		3008		Julian Green	London		300	5002
5006	Mc Lyon		Paris		0.14		3008		Julian Green	London		300	5002
5007	Paul Adam	Rome		0.13		3008		Julian Green	London		300	5002
5003	Lauson Hen	San Jose	0.12		3008		Julian Green	London		300	5002
5001	James Hoog	New York	0.15		3004		Fabian Johnson	Paris		300	5006
5002	Nail Knite	Paris		0.13		3004		Fabian Johnson	Paris		300	5006
5005	Pit Alex	London		0.11		3004		Fabian Johnson	Paris		300	5006
5006	Mc Lyon		Paris		0.14		3004		Fabian Johnson	Paris		300	5006
5007	Paul Adam	Rome		0.13		3004		Fabian Johnson	Paris		300	5006
5003	Lauson Hen	San Jose	0.12		3004		Fabian Johnson	Paris		300	5006
5001	James Hoog	New York	0.15		3009		Geoff Cameron	Berlin		100	5003
5002	Nail Knite	Paris		0.13		3009		Geoff Cameron	Berlin		100	5003
5005	Pit Alex	London		0.11		3009		Geoff Cameron	Berlin		100	5003
5006	Mc Lyon		Paris		0.14		3009		Geoff Cameron	Berlin		100	5003
5007	Paul Adam	Rome		0.13		3009		Geoff Cameron	Berlin		100	5003
5003	Lauson Hen	San Jose	0.12		3009		Geoff Cameron	Berlin		100	5003
5001	James Hoog	New York	0.15		3003		Jozy Altidor	Moscow		200	5007
5002	Nail Knite	Paris		0.13		3003		Jozy Altidor	Moscow		200	5007
5005	Pit Alex	London		0.11		3003		Jozy Altidor	Moscow		200	5007
5006	Mc Lyon		Paris		0.14		3003		Jozy Altidor	Moscow		200	5007
5007	Paul Adam	Rome		0.13		3003		Jozy Altidor	Moscow		200	5007
5003	Lauson Hen	San Jose	0.12		3003		Jozy Altidor	Moscow		200	5007
5001	James Hoog	New York	0.15		3001		Brad Guzan	London			5005
5002	Nail Knite	Paris		0.13		3001		Brad Guzan	London			5005
5005	Pit Alex	London		0.11		3001		Brad Guzan	London			5005
5006	Mc Lyon		Paris		0.14		3001		Brad Guzan	London			5005
5007	Paul Adam	Rome		0.13		3001		Brad Guzan	London			5005
5003	Lauson Hen	San Jose	0.12		3001		Brad Guzan	London			5005

Explanation:

The said SQL query selects all columns (*) from the salesman table alias a and the customer table alias b, and performs a cross join between the two tables. The query also includes a WHERE clause that filters the results to only include rows from the salesman table where the 'city' column is not null.
This means that the query will return all combinations of rows from the salesman table where the 'city' column is not null and the customer table, effectively creating a Cartesian product of the two tables.

Visual Explanation:

Result of a cartesian product between salesman and customer i.e. each salesman will appear for all customer and vice versa for those customer who belongs to a city

Practice Online


Query Visualization:

Duration:

Query visualization of Prepare a cartesian product between salesman and customer i.e. each salesman will appear for all customer and vice versa for that salesman who belongs to a city - Duration

Rows:

Query visualization of Prepare a cartesian product between salesman and customer i.e. each salesman will appear for all customer and vice versa for that salesman who belongs to a city - Rows

Cost:

Query visualization of Prepare a cartesian product between salesman and customer i.e. each salesman will appear for all customer and vice versa for that salesman who belongs to a city - Cost

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Previous SQL Exercise: Salesman will appear for all customer and vice versa.
Next SQL Exercise: Salesmen belongs to a city, customers have a grade.

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