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SQL join three or more tables based on a parent-child relationship

In this page, we are going to discuss such a join which involves the participation of three tables and there is a parent-child relationship between these tables.

A parent-child relationship between two tables can be created only when there is a PRIMARY KEY in one table and FOREIGN KEY in another table.

Syntax diagram - SQL JOIN of three tables

syntax diagram - Sql JOIN of three tables

Example: SQL JOIN - three or more tables

Here is an example of SQL join three tables with conditions.

Sample table : agents
 
+------------+----------------------+--------------------+------------+-----------------+---------+
| AGENT_CODE | AGENT_NAME           | WORKING_AREA       | COMMISSION | PHONE_NO        | COUNTRY |
+------------+----------------------+--------------------+------------+-----------------+---------+
| A007       | Ramasundar           | Bangalore          |       0.15 | 077-25814763    |         |
| A003       | Alex                 | London             |       0.13 | 075-12458969    |         |
| A008       | Alford               | New York           |       0.12 | 044-25874365    |         |
| A011       | Ravi Kumar           | Bangalore          |       0.15 | 077-45625874    |         |
| A010       | Santakumar           | Chennai            |       0.14 | 007-22388644    |         |
| A012       | Lucida               | San Jose           |       0.12 | 044-52981425    |         |
| A005       | Anderson             | Brisban            |       0.13 | 045-21447739    |         |
| A001       | Subbarao             | Bangalore          |       0.14 | 077-12346674    |         |
| A002       | Mukesh               | Mumbai             |       0.11 | 029-12358964    |         |
| A006       | McDen                | London             |       0.15 | 078-22255588    |         |
| A004       | Ivan                 | Torento            |       0.15 | 008-22544166    |         |
| A009       | Benjamin             | Hampshair          |       0.11 | 008-22536178    |         |
+------------+----------------------+--------------------+------------+-----------------+---------+
Sample table : customer
  
+-----------+-------------+-------------+--------------+--------------+-------+-------------+-------------+-------------+---------------+--------------+------------+  
|CUST_CODE  | CUST_NAME   | CUST_CITY   | WORKING_AREA | CUST_COUNTRY | GRADE | OPENING_AMT | RECEIVE_AMT | PAYMENT_AMT |OUTSTANDING_AMT| PHONE_NO     | AGENT_CODE |
+-----------+-------------+-------------+--------------+--------------+-------+-------------+-------------+-------------+---------------+--------------+------------+
| C00013    | Holmes      | London      | London       | UK           |     2 |     6000.00 |     5000.00 |     7000.00 |       4000.00 | BBBBBBB      | A003       |
| C00001    | Micheal     | New York    | New York     | USA          |     2 |     3000.00 |     5000.00 |     2000.00 |       6000.00 | CCCCCCC      | A008       |
| C00020    | Albert      | New York    | New York     | USA          |     3 |     5000.00 |     7000.00 |     6000.00 |       6000.00 | BBBBSBB      | A008       |
| C00025    | Ravindran   | Bangalore   | Bangalore    | India        |     2 |     5000.00 |     7000.00 |     4000.00 |       8000.00 | AVAVAVA      | A011       |
| C00024    | Cook        | London      | London       | UK           |     2 |     4000.00 |     9000.00 |     7000.00 |       6000.00 | FSDDSDF      | A006       |
| C00015    | Stuart      | London      | London       | UK           |     1 |     6000.00 |     8000.00 |     3000.00 |      11000.00 | GFSGERS      | A003       |
| C00002    | Bolt        | New York    | New York     | USA          |     3 |     5000.00 |     7000.00 |     9000.00 |       3000.00 | DDNRDRH      | A008       |
| C00018    | Fleming     | Brisban     | Brisban      | Australia    |     2 |     7000.00 |     7000.00 |     9000.00 |       5000.00 | NHBGVFC      | A005       |
| C00021    | Jacks       | Brisban     | Brisban      | Australia    |     1 |     7000.00 |     7000.00 |     7000.00 |       7000.00 | WERTGDF      | A005       |
| C00019    | Yearannaidu | Chennai     | Chennai      | India        |     1 |     8000.00 |     7000.00 |     7000.00 |       8000.00 | ZZZZBFV      | A010       |
| C00005    | Sasikant    | Mumbai      | Mumbai       | India        |     1 |     7000.00 |    11000.00 |     7000.00 |      11000.00 | 147-25896312 | A002       |
| C00007    | Ramanathan  | Chennai     | Chennai      | India        |     1 |     7000.00 |    11000.00 |     9000.00 |       9000.00 | GHRDWSD      | A010       |
| C00022    | Avinash     | Mumbai      | Mumbai       | India        |     2 |     7000.00 |    11000.00 |     9000.00 |       9000.00 | 113-12345678 | A002       |
| C00004    | Winston     | Brisban     | Brisban      | Australia    |     1 |     5000.00 |     8000.00 |     7000.00 |       6000.00 | AAAAAAA      | A005       |
| C00023    | Karl        | London      | London       | UK           |     0 |     4000.00 |     6000.00 |     7000.00 |       3000.00 | AAAABAA      | A006       |
| C00006    | Shilton     | Torento     | Torento      | Canada       |     1 |    10000.00 |     7000.00 |     6000.00 |      11000.00 | DDDDDDD      | A004       |
| C00010    | Charles     | Hampshair   | Hampshair    | UK           |     3 |     6000.00 |     4000.00 |     5000.00 |       5000.00 | MMMMMMM      | A009       |
| C00017    | Srinivas    | Bangalore   | Bangalore    | India        |     2 |     8000.00 |     4000.00 |     3000.00 |       9000.00 | AAAAAAB      | A007       |
| C00012    | Steven      | San Jose    | San Jose     | USA          |     1 |     5000.00 |     7000.00 |     9000.00 |       3000.00 | KRFYGJK      | A012       |
| C00008    | Karolina    | Torento     | Torento      | Canada       |     1 |     7000.00 |     7000.00 |     9000.00 |       5000.00 | HJKORED      | A004       |
| C00003    | Martin      | Torento     | Torento      | Canada       |     2 |     8000.00 |     7000.00 |     7000.00 |       8000.00 | MJYURFD      | A004       |
| C00009    | Ramesh      | Mumbai      | Mumbai       | India        |     3 |     8000.00 |     7000.00 |     3000.00 |      12000.00 | Phone No     | A002       |
| C00014    | Rangarappa  | Bangalore   | Bangalore    | India        |     2 |     8000.00 |    11000.00 |     7000.00 |      12000.00 | AAAATGF      | A001       |
| C00016    | Venkatpati  | Bangalore   | Bangalore    | India        |     2 |     8000.00 |    11000.00 |     7000.00 |      12000.00 | JRTVFDD      | A007       |
| C00011    | Sundariya   | Chennai     | Chennai      | India        |     3 |     7000.00 |    11000.00 |     7000.00 |      11000.00 | PPHGRTS      | A010       |
+-----------+-------------+-------------+--------------+--------------+-------+-------------+-------------+-------------+---------------+--------------+------------+
Sample table: orders
   ORD_NUM ORD_AMOUNT ADVANCE_AMOUNT ORD_DATE  CUST_CODE       AGENT_CODE      ORD_DESCRIPTION
---------- ---------- -------------- --------- --------------- --------------- -----------------
    200114       3500           2000 15-AUG-08 C00002          A008
    200122       2500            400 16-SEP-08 C00003          A004
    200118        500            100 20-JUL-08 C00023          A006
    200119       4000            700 16-SEP-08 C00007          A010
    200121       1500            600 23-SEP-08 C00008          A004
    200130       2500            400 30-JUL-08 C00025          A011
    200134       4200           1800 25-SEP-08 C00004          A005
    200108       4000            600 15-FEB-08 C00008          A004
    200103       1500            700 15-MAY-08 C00021          A005
    200105       2500            500 18-JUL-08 C00025          A011
    200109       3500            800 30-JUL-08 C00011          A010
    200101       3000           1000 15-JUL-08 C00001          A008
    200111       1000            300 10-JUL-08 C00020          A008
    200104       1500            500 13-MAR-08 C00006          A004
    200106       2500            700 20-APR-08 C00005          A002
    200125       2000            600 10-OCT-08 C00018          A005
    200117        800            200 20-OCT-08 C00014          A001
    200123        500            100 16-SEP-08 C00022          A002
    200120        500            100 20-JUL-08 C00009          A002
    200116        500            100 13-JUL-08 C00010          A009
    200124        500            100 20-JUN-08 C00017          A007
    200126        500            100 24-JUN-08 C00022          A002
    200129       2500            500 20-JUL-08 C00024          A006
    200127       2500            400 20-JUL-08 C00015          A003
    200128       3500           1500 20-JUL-08 C00009          A002
    200135       2000            800 16-SEP-08 C00007          A010
    200131        900            150 26-AUG-08 C00012          A012
    200133       1200            400 29-JUN-08 C00009          A002
    200100       1000            600 08-JAN-08 C00015          A003
    200110       3000            500 15-APR-08 C00019          A010
    200107       4500            900 30-AUG-08 C00007          A010
    200112       2000            400 30-MAY-08 C00016          A007
    200113       4000            600 10-JUN-08 C00022          A002
    200102       2000            300 25-MAY-08 C00012          A012

To get 'ord_num' and 'cust_code' columns from the table 'orders' and 'cust_name' and 'cust_city' columns from the table 'customer' and 'agent_code' column from the table 'agents' after a joining, with following conditions -

1. 'a', 'b' and 'c' are the aliases of 'orders', 'customer' and 'agents' table,

2. 'orders' and 'customer' tables are child table of 'agents' table because 'agent_code' is primary key in 'agents' table and foreign key in 'customer' and 'orders' table,

3. 'orders' table is child table of 'customer' table because 'cust_code' is primary key in 'customer' table and foreign key in 'orders' table,

4. 'cust_city' and 'working_area' of 'customer' and 'agents' table must be same,

5. 'cust_code' of 'orders' and 'customer' table must be same,

6. 'agent_code' of 'orders' and 'agents' table must be same,

the following SQL statement can be used :

SQL Code:


-- Selecting specific columns: 'ord_num' from table 'a' (orders), 'cust_name' from table 'b' (customer),
-- 'cust_code' from table 'a' (orders), 'agent_code' from table 'c' (agents), and 'cust_city' from table 'b' (customer)
SELECT a.ord_num, b.cust_name, a.cust_code, c.agent_code, b.cust_city
-- Performing a Cartesian product (cross join) between tables 'agents' (aliased as 'c'), 'customer' (aliased as 'b'), and 'orders' (aliased as 'a') (implicit join)
FROM agents c, customer b, orders a
-- Defining join conditions in the WHERE clause where 'b.cust_city' equals 'c.working_area' to link 'customer' and 'agents', 
-- 'a.cust_code' equals 'b.cust_code' to link 'orders' and 'customer', and 'a.agent_code' equals 'c.agent_code' to link 'orders' and 'agents'
WHERE b.cust_city = c.working_area
AND a.cust_code = b.cust_code
AND a.agent_code = c.agent_code;

Explanation:

  • This SQL query retrieves data from three tables: 'agents', 'customer', and 'orders'.

  • It selects specific columns from these tables: 'ord_num' from 'orders', 'cust_name' and 'cust_city' from 'customer', 'cust_code' from 'orders', and 'agent_code' from 'agents'.

  • The query performs a Cartesian product (cross join) between the 'agents', 'customer', and 'orders' tables, implicitly joining every row from each table with every row from the other tables.

  • The join conditions are specified in the WHERE clause:

    • 'b.cust_city' (customer city) must equal 'c.working_area' (agent working area), linking the 'customer' and 'agents' tables based on the city.

    • 'a.cust_code' (customer code) must equal 'b.cust_code' (customer code), linking the 'orders' and 'customer' tables based on the customer code.

    • 'a.agent_code' (agent code) must equal 'c.agent_code' (agent code), linking the 'orders' and 'agents' tables based on the agent code.

  • This query retrieves data about orders, including the order number, customer name, customer city, customer code, and agent code.

  • By joining these tables based on the specified conditions, the query retrieves information about orders along with the corresponding customer and agent details.

  • Cartesian product may result in a large intermediate result set, and hence, it's essential to ensure that the join conditions are correctly specified to avoid unnecessary rows in the output.

Output:

   ORD_NUM CUST_NAME                                CUST_CODE  AGENT_CODE CUST_CITY
---------- ---------------------------------------- ---------- ---------- -----------
    200114 Bolt                                     C00002     A008       New York
    200122 Martin                                   C00003     A004       Torento
    200118 Karl                                     C00023     A006       London
    200119 Ramanathan                               C00007     A010       Chennai
    200121 Karolina                                 C00008     A004       Torento
    200130 Ravindran                                C00025     A011       Bangalore
    200134 Winston                                  C00004     A005       Brisban
    200108 Karolina                                 C00008     A004       Torento
    200103 Jacks                                    C00021     A005       Brisban
    200105 Ravindran                                C00025     A011       Bangalore
    200109 Sundariya                                C00011     A010       Chennai
    200101 Micheal                                  C00001     A008       New York
    200111 Albert                                   C00020     A008       New York
    200104 Shilton                                  C00006     A004       Torento
    200106 Sasikant                                 C00005     A002       Mumbai
    200125 Fleming                                  C00018     A005       Brisban
    200117 Rangarappa                               C00014     A001       Bangalore
    200123 Avinash                                  C00022     A002       Mumbai
    200120 Ramesh                                   C00009     A002       Mumbai
    200116 Charles                                  C00010     A009       Hampshair
    200124 Srinivas                                 C00017     A007       Bangalore
    200126 Avinash                                  C00022     A002       Mumbai
	.............
	.............

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