HSQLDB - Joins

Whenever there is a requirement to retrieve data from multiple tables using a single query, you can use JOINS from RDBMS. You can use multiple tables in your single SQL query. The act of joining in HSQLDB refers to smashing two or more tables into a single table.
Consider the following Customers and Orders tables.
Customer:
+----+----------+-----+-----------+----------+
| ID |   NAME   | AGE |  ADDRESS  |  SALARY  |
+----+----------+-----+-----------+----------+
| 1  |  Ramesh  | 32  | Ahmedabad |  2000.00 |
| 2  |  Khilan  | 25  |   Delhi   |  1500.00 |
| 3  |  kaushik | 23  |   Kota    |  2000.00 |
| 4  | Chaitali | 25  |   Mumbai  |  6500.00 |
| 5  |  Hardik  | 27  |   Bhopal  |  8500.00 |
| 6  |  Komal   | 22  |    MP     |  4500.00 |
| 7  |  Muffy   | 24  |   Indore  | 10000.00 |
+----+----------+-----+-----------+----------+
Orders:
+-----+---------------------+-------------+--------+
|OID  |         DATE        | CUSTOMER_ID | AMOUNT |
+-----+---------------------+-------------+--------+
| 102 | 2009-10-08 00:00:00 |      3      |  3000  |
| 100 | 2009-10-08 00:00:00 |      3      |  1500  |
| 101 | 2009-11-20 00:00:00 |      2      |  1560  |
| 103 | 2008-05-20 00:00:00 |      4      |  2060  |
+-----+---------------------+-------------+--------+

Now, let us try to retrieve the data of the customers and the order amount that the respective customer placed. This means we are retrieving the record data from both customers and orders table. We can achieve this by using the JOINS concept in HSQLDB. Following is the JOIN query for the same.
SELECT ID, NAME, AGE, AMOUNT FROM CUSTOMERS, ORDERS WHERE CUSTOMERS.ID =
ORDERS.CUSTOMER_ID;
After execution of the above query, you will receive the following output.
+----+----------+-----+--------+
| ID |   NAME   | AGE | AMOUNT |
+----+----------+-----+--------+
|  3 | kaushik  |  23 |  3000  |
|  3 | kaushik  |  23 |  1500  |
|  2 | Khilan   |  25 |  1560  |
|  4 | Chaitali |  25 |  2060  |
+----+----------+-----+--------+

There are different types of joins available in HSQLDB.
INNER JOIN − Returns the rows when there is a match in both tables.
INNER JOIN − Returns the rows when there is a match in both tables.
LEFT JOIN − Returns all rows from the left table, even if there are no matches in the right table.
LEFT JOIN − Returns all rows from the left table, even if there are no matches in the right table.
RIGHT JOIN − Returns all rows from the right table, even if there are no matches in the left table.
RIGHT JOIN − Returns all rows from the right table, even if there are no matches in the left table.
FULL JOIN − Returns the rows when there is a match in one of the tables.
FULL JOIN − Returns the rows when there is a match in one of the tables.
SELF JOIN − Used to join a table to itself as if the table were two tables, temporarily renaming at least one table in the SQL statement.
SELF JOIN − Used to join a table to itself as if the table were two tables, temporarily renaming at least one table in the SQL statement.
The most frequently used and important of the joins is the INNER JOIN. It is also referred to as an EQUIJOIN.
The INNER JOIN creates a new result table by combining the column values of two tables (table1 and table2) based upon the join-predicate. The query compares each row of table1 with each row of table2 to find all pairs of rows, which satisfy the join-predicate. When the join-predicate is satisfied, the column values for each matched pair of rows A and B are combined into a result row.
The basic syntax of INNER JOIN is as follows.
SELECT table1.column1, table2.column2...
FROM table1
INNER JOIN table2
ON table1.common_field = table2.common_field;
Consider the following two tables, one titled as CUSTOMERS table and another titled as ORDERS table as follows −
+----+----------+-----+-----------+----------+
| ID |   NAME   | AGE |  ADDRESS  | SALARY   |
+----+----------+-----+-----------+----------+
| 1  |  Ramesh  | 32  | Ahmedabad | 2000.00  |
| 2  |  Khilan  | 25  |   Delhi   | 1500.00  |
| 3  |  kaushik | 23  |   Kota    | 2000.00  |
| 4  | Chaitali | 25  |   Mumbai  | 6500.00  |
| 5  |  Hardik  | 27  |   Bhopal  | 8500.00  |
| 6  |  Komal   | 22  |     MP    | 4500.00  |
| 7  |  Muffy   | 24  |   Indore  | 10000.00 |
+----+----------+-----+-----------+----------+

+-----+---------------------+-------------+--------+
| OID |         DATE        | CUSTOMER_ID | AMOUNT |
+-----+---------------------+-------------+--------+
| 102 | 2009-10-08 00:00:00 |      3      | 3000   |
| 100 | 2009-10-08 00:00:00 |      3      | 1500   |
| 101 | 2009-11-20 00:00:00 |      2      | 1560   |
| 103 | 2008-05-20 00:00:00 |      4      | 2060   |
+-----+---------------------+-------------+--------+

Now, let us join these two tables using INNER JOIN query as follows −
SELECT ID, NAME, AMOUNT, DATE FROM CUSTOMERS
INNER JOIN ORDERS
ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;
After execution of the above query, you will receive the following output.
+----+----------+--------+---------------------+
| ID |   NAME   | AMOUNT |         DATE        |
+----+----------+--------+---------------------+
| 3  |  kaushik |  3000  | 2009-10-08 00:00:00 |
| 3  |  kaushik |  1500  | 2009-10-08 00:00:00 |
| 2  |  Khilan  |  1560  | 2009-11-20 00:00:00 |
| 4  | Chaitali |  2060  | 2008-05-20 00:00:00 |
+----+----------+--------+---------------------+

The HSQLDB LEFT JOIN returns all rows from the left table, even if there are no matches in the right table. This means that if the ON clause matches 0 (zero) records in the right table, the join will still return a row in the result, but with NULL in each column from the right table.
This means that a left join returns all the values from the left table, plus matched values from the right table or NULL in case of no matching join predicate.
The basic syntax of LEFT JOIN is as follows −
SELECT table1.column1, table2.column2...
FROM table1
LEFT JOIN table2
ON table1.common_field = table2.common_field;
Here the given condition could be any given expression based on your requirement.
Consider the following two tables, one titled as CUSTOMERS table and another titled as ORDERS table as follows −
+----+----------+-----+-----------+----------+
| ID |   NAME   | AGE |  ADDRESS  | SALARY   |
+----+----------+-----+-----------+----------+
| 1  |  Ramesh  | 32  | Ahmedabad | 2000.00  |
| 2  |  Khilan  | 25  |   Delhi   | 1500.00  |
| 3  |  kaushik | 23  |   Kota    | 2000.00  |
| 4  | Chaitali | 25  |   Mumbai  | 6500.00  |
| 5  |  Hardik  | 27  |   Bhopal  | 8500.00  |
| 6  |  Komal   | 22  |    MP     | 4500.00  |
| 7  |  Muffy   | 24  |  Indore   | 10000.00 |
+----+----------+-----+-----------+----------+

+-----+---------------------+-------------+--------+
| OID |        DATE         | CUSTOMER_ID | AMOUNT |
+-----+---------------------+-------------+--------+
| 102 | 2009-10-08 00:00:00 |     3       | 3000   |
| 100 | 2009-10-08 00:00:00 |     3       | 1500   |
| 101 | 2009-11-20 00:00:00 |     2       | 1560   |
| 103 | 2008-05-20 00:00:00 |     4       | 2060   |
+-----+---------------------+-------------+--------+

Now, let us join these two tables using the LEFT JOIN query as follows −
SELECT ID, NAME, AMOUNT, DATE FROM CUSTOMERS
LEFT JOIN ORDERS
ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;
After execution of the above query, you will receive the following output −
+----+----------+--------+---------------------+
| ID |   NAME   | AMOUNT |         DATE        |
+----+----------+--------+---------------------+
|  1 |  Ramesh  |  NULL  |        NULL         |
|  2 |  Khilan  |  1560  | 2009-11-20 00:00:00 |
|  3 |  kaushik |  3000  | 2009-10-08 00:00:00 |
|  3 |  kaushik |  1500  | 2009-10-08 00:00:00 |
|  4 | Chaitali |  2060  | 2008-05-20 00:00:00 |
|  5 |  Hardik  |  NULL  |        NULL         |
|  6 |  Komal   |  NULL  |        NULL         |
|  7 |  Muffy   |  NULL  |        NULL         |
+----+----------+--------+---------------------+

The HSQLDB RIGHT JOIN returns all rows from the right table, even if there are no matches in the left table. This means that if the ON clause matches 0 (zero) records in the left table, the join will still return a row in the result, but with NULL in each column from the left table.
This means that a right join returns all the values from the right table, plus matched values from the left table or NULL in case of no matching join predicate.
The basic syntax of RIGHT JOIN is as follows −
SELECT table1.column1, table2.column2...
FROM table1
RIGHT JOIN table2
ON table1.common_field = table2.common_field;
Consider the following two tables, one titled as CUSTOMERS table and another titled as ORDERS table as follows −
+----+----------+-----+-----------+----------+
| ID |   NAME   | AGE |  ADDRESS  |  SALARY  |
+----+----------+-----+-----------+----------+
| 1  |  Ramesh  | 32  | Ahmedabad |  2000.00 |
| 2  |  Khilan  | 25  |   Delhi   |  1500.00 |
| 3  |  kaushik | 23  |   Kota    |  2000.00 |
| 4  | Chaitali | 25  |   Mumbai  |  6500.00 |
| 5  |  Hardik  | 27  |   Bhopal  |  8500.00 |
| 6  |  Komal   | 22  |     MP    |  4500.00 |
| 7  |  Muffy   | 24  |   Indore  | 10000.00 |
+----+----------+-----+-----------+----------+

+-----+---------------------+-------------+--------+
| OID |       DATE          | CUSTOMER_ID | AMOUNT |
+-----+---------------------+-------------+--------+
| 102 | 2009-10-08 00:00:00 |      3      |  3000  |
| 100 | 2009-10-08 00:00:00 |      3      |  1500  |
| 101 | 2009-11-20 00:00:00 |      2      |  1560  |
| 103 | 2008-05-20 00:00:00 |      4      |  2060  |
+-----+---------------------+-------------+--------+

Now, let us join these two tables using the RIGHT JOIN query as follows −
SELECT ID, NAME, AMOUNT, DATE FROM CUSTOMERS
RIGHT JOIN ORDERS
ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;
After execution of the above query, you will receive the following result.
+------+----------+--------+---------------------+
|  ID  |   NAME   | AMOUNT |        DATE         |
+------+----------+--------+---------------------+
|  3   |  kaushik |  3000  | 2009-10-08 00:00:00 |
|  3   |  kaushik |  1500  | 2009-10-08 00:00:00 |
|  2   |  Khilan  |  1560  | 2009-11-20 00:00:00 |
|  4   | Chaitali |  2060  | 2008-05-20 00:00:00 |
+------+----------+--------+---------------------+

The HSQLDB FULL JOIN combines the results of both left and right outer joins.
The joined table will contain all records from both tables, and fill in NULLs for the missing matches on either side.
The basic syntax of FULL JOIN is as follows −
SELECT table1.column1, table2.column2...
FROM table1
FULL JOIN table2
ON table1.common_field = table2.common_field;

Here the given condition could be any given expression based on your requirement.
Consider the following two tables, one titled as CUSTOMERS table and another titled as
ORDERS table as follows −
+----+----------+-----+-----------+----------+
| ID |   NAME   | AGE |  ADDRESS  |  SALARY  |
+----+----------+-----+-----------+----------+
|  1 |  Ramesh  | 32  | Ahmedabad | 2000.00  |
|  2 |  Khilan  | 25  |   Delhi   | 1500.00  |
|  3 |  kaushik | 23  |   Kota    | 2000.00  |
|  4 | Chaitali | 25  |   Mumbai  | 6500.00  |
|  5 |  Hardik  | 27  |   Bhopal  | 8500.00  |
|  6 |  Komal   | 22  |   MP      | 4500.00  |
|  7 |  Muffy   | 24  |   Indore  | 10000.00 |
+----+----------+-----+-----------+----------+

+-----+---------------------+-------------+--------+
| OID |         DATE        | CUSTOMER_ID | AMOUNT |
+-----+---------------------+-------------+--------+
| 102 | 2009-10-08 00:00:00 |    3        | 3000   |
| 100 | 2009-10-08 00:00:00 |    3        | 1500   |
| 101 | 2009-11-20 00:00:00 |    2        | 1560   |
| 103 | 2008-05-20 00:00:00 |    4        | 2060   |
+-----+---------------------+-------------+--------+

Now, let us join these two tables using the FULL JOIN query as follows −
SELECT ID, NAME, AMOUNT, DATE FROM CUSTOMERS
FULL JOIN ORDERS
ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;
After execution of the above query, you will receive the following result.
+------+----------+--------+---------------------+
|  ID  |    NAME  | AMOUNT |        DATE         |
+------+----------+--------+---------------------+
|   1  |  Ramesh  |  NULL  |        NULL         |
|   2  |  Khilan  |  1560  | 2009-11-20 00:00:00 |
|   3  |  kaushik |  3000  | 2009-10-08 00:00:00 |
|   3  |  kaushik |  1500  | 2009-10-08 00:00:00 |
|   4  | Chaitali |  2060  | 2008-05-20 00:00:00 |
|   5  |  Hardik  |  NULL  |        NULL         |
|   6  |   Komal  |  NULL  |        NULL         |
|   7  |   Muffy  |  NULL  |        NULL         |
|   3  |  kaushik |  3000  | 2009-10-08 00:00:00 |
|   3  |  kaushik |  1500  | 2009-10-08 00:00:00 |
|   2  |  Khilan  |  1560  | 2009-11-20 00:00:00 |
|   4  | Chaitali |  2060  | 2008-05-20 00:00:00 |
+------+----------+--------+---------------------+

The SQL SELF JOIN is used to join a table to itself as if the table were two tables, temporarily renaming at least one table in the SQL statement.
The basic syntax of SELF JOIN is as follows −
SELECT a.column_name, b.column_name...
FROM table1 a, table1 b
WHERE a.common_field = b.common_field;
Here, the WHERE clause could be any given expression based on your requirement.
Consider the following two tables, one titled as CUSTOMERS table and another titled as ORDERS table as follows −
+----+----------+-----+-----------+----------+
| ID |    NAME  | AGE |   ADDRESS |   SALARY |
+----+----------+-----+-----------+----------+
|  1 |  Ramesh  |  32 | Ahmedabad | 2000.00  |
|  2 |  Khilan  |  25 |   Delhi   | 1500.00  |
|  3 |  kaushik |  23 |   Kota    | 2000.00  |
|  4 | Chaitali |  25 |   Mumbai  | 6500.00  |
|  5 |  Hardik  |  27 |   Bhopal  | 8500.00  |
|  6 |  Komal   |  22 |   MP      | 4500.00  |
|  7 |  Muffy   |  24 |   Indore  | 10000.00 |
+----+----------+-----+-----------+----------+

Now, let us join this table using the SELF JOIN query as follows −
SELECT a.ID, b.NAME, a.SALARY FROM CUSTOMERS a, CUSTOMERS b
WHERE a.SALARY > b.SALARY;

After execution of the above query, you will receive the following output −
+----+----------+---------+
| ID |   NAME   | SALARY  |
+----+----------+---------+
| 2  |  Ramesh  | 1500.00 |
| 2  |  kaushik | 1500.00 |
| 1  | Chaitali | 2000.00 |
| 2  | Chaitali | 1500.00 |
| 3  | Chaitali | 2000.00 |
| 6  | Chaitali | 4500.00 |
| 1  |  Hardik  | 2000.00 |
| 2  |  Hardik  | 1500.00 |
| 3  |  Hardik  | 2000.00 |
| 4  |  Hardik  | 6500.00 |
| 6  |  Hardik  | 4500.00 |
| 1  |  Komal   | 2000.00 |
| 2  |  Komal   | 1500.00 |
| 3  |  Komal   | 2000.00 |
| 1  |  Muffy   | 2000.00 |
| 2  |  Muffy   | 1500.00 |
| 3  |  Muffy   | 2000.00 |
| 4  |  Muffy   | 6500.00 |
| 5  |  Muffy   | 8500.00 |
| 6  |  Muffy   | 4500.00 |
+----+----------+---------+

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