SQL – Left Join


SQL – Left Join


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Joins are used to retrieve records from two or more tables based on a logical relation between them. This relation is defined using a join condition. As we discussed in the previous chapters, there are two types of Joins −

Left Join is a type of outer join that retrieves all the records from the first table and matches them to the records in second table. First of all, let us understand what is outer join.

What is Outer Join?

Outer Join is used to join multiple database tables into a combined result-set, that includes all the records, even if they don”t satisfy the join condition. NULL values are displayed against these records where the join condition is not met.

This scenario only occurs if the left table (or the first table) has more records than the right table (or the second table), or vice versa.

There are three types of outer joins, namely −

  • Left (Outer) Join: Retrieves all the records from the first table, Matching records from the second table and NULL values in the unmatched rows.
  • Right (Outer) Join: Retrieves all the records from the second table, Matching records from the first table and NULL values in the unmatched rows.
  • Full (Outer) Join: Retrieves records from both the tables and fills the unmatched values with NULL.

Following diagram illustrates various outer joins between two tables namely, EmpDetails and MaritalStatus. Here, the join operation is presumed based on the join-predicate EmpDetails.EmpID = MaritalStatus.EmpID.

Right Join

The SQL Left Join

Left Join or Left Outer Join in SQL combines two or more tables, where the first table is returned wholly; but, only the matching record(s) are retrieved from the consequent tables. If zero (0) records are matched in the consequent tables, the join will still return a row in the result, but with NULL in each column from the right table.

Left Join

If the number of rows in first table is less than the number of rows in second table, the rows in second table that do not have any counterparts in the first table will be discarded from the result.

Syntax

Following is the basic syntax of Left Join in SQL −

SELECT column_name(s)
FROM table1
LEFT JOIN table2
ON table1.column_name = table2.column_name;

Example

To understand this query better, let us create some tables in an existing database and join them using Left Join or Left Outer Join.

Assume we have created a table named CUSTOMERS, which contains the personal details of customers including their name, age, address and salary, using the following query.

CREATE TABLE CUSTOMERS (
   ID INT NOT NULL,
   NAME VARCHAR (20) NOT NULL,
   AGE INT NOT NULL,
   ADDRESS CHAR (25),
   SALARY DECIMAL (18, 2),       
   PRIMARY KEY (ID)
);

Now insert values into this table using the INSERT statement as follows −

INSERT INTO CUSTOMERS VALUES
(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, ''Hyderabad'', 4500.00 ),
(7, ''Muffy'', 24, ''Indore'', 10000.00 );

The table will be created as −

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 Hyderabad 4500.00
7 Muffy 24 Indore 10000.00

Let us create another table ORDERS, containing the details of orders made and the date they are made on.

CREATE TABLE ORDERS (
   OID INT NOT NULL,
   DATE VARCHAR (20) NOT NULL,
   CUSTOMER_ID INT NOT NULL,
   AMOUNT DECIMAL (18, 2)
);

Using the INSERT statement, insert values into this table as follows −

INSERT INTO ORDERS VALUES 
(102, ''2009-10-08 00:00:00'', 3, 3000.00),
(100, ''2009-10-08 00:00:00'', 3, 1500.00),
(101, ''2009-11-20 00:00:00'', 2, 1560.00),
(103, ''2008-05-20 00:00:00'', 4, 2060.00);

The table is displayed as follows −

OID DATE CUSTOMER_ID AMOUNT
102 2009-10-08 00:00:00 3 3000.00
100 2009-10-08 00:00:00 3 1500.00
101 2009-11-20 00:00:00 2 1560.00
103 2008-05-20 00:00:00 4 2060.00

Following left join query, retrieves the details of customers who made an order at the specified date and who did not. If there is no match found, the query below will return NULL in that record.

SELECT ID, NAME, AMOUNT, DATE
FROM CUSTOMERS
LEFT JOIN ORDERS
ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;

Output

The resultant table is obtained as −

ID NAME AMOUNT DATE
1 Ramesh NULL NULL
2 Khilan 1560.00 2009-11-20 00:00:00
3 Kaushik 1500.00 2009-10-08 00:00:00
3 Kaushik 3000.00 2009-10-08 00:00:00
4 Chaitali 2060.00 2008-05-20 00:00:00
5 Hardik NULL NULL
6 Komal NULL NULL
7 Muffy NULL NULL

As we can see in the table above, only Khilan, Kaushik and Chaitali made purchases on the mentioned dates in ORDERS table; hence, the records are matched. The other customers in CUSTOMERS table did not make purchases on the specified dates, so the records are returned as NULL.

Joining Multiple Tables with Left Join

Similar to the Inner Join query, Left Join also joins multiple tables where the first table is returned as it is and the remaining tables are matched with the rows in the first table. If the records are not matched, NULL is returned.

The syntax to join multiple tables using Left Join is given below −

SELECT column1, column2, column3... 
FROM table1
LEFT JOIN table2
ON condition_1
LEFT JOIN table3
ON condition_2
....
....
LEFT JOIN tableN
ON condition_N;

Example

To demonstrate Left Join with multiple tables, let us consider the previously created tables CUSTOMERS and ORDERS. In addition to these we will create the EMPLOYEE table using the following query −

CREATE TABLE EMPLOYEE (
   EID INT NOT NULL,
   EMPLOYEE_NAME VARCHAR (30) NOT NULL,
   SALES_MADE DECIMAL (20)
);

Now, we can insert values into this empty tables using the INSERT statement as follows −

INSERT INTO EMPLOYEE VALUES
(102, ''SARIKA'', 4500),
(100, ''ALEKHYA'', 3623),
(101, ''REVATHI'', 1291),
(103, ''VIVEK'', 3426);

The EMPLOYEE table consists of the details of employees in an organization and sales made by them.

EID EMPLOYEE_NAME SALES_MADE
102 SARIKA 4500
100 ALEKHYA 3623
101 REVATHI 1291
103 VIVEK 3426

Following query joins the CUSTOMERS, ORDERS and EMPLOYEE tables using the left join −

SELECT CUSTOMERS.ID, CUSTOMERS.NAME, 
ORDERS.DATE, EMPLOYEE.EMPLOYEE_NAME
FROM CUSTOMERS
LEFT JOIN ORDERS
ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID
LEFT JOIN EMPLOYEE
ON ORDERS.OID = EMPLOYEE.EID;

Through this query, we will display the id, name of the customer along with the date on which the orders are made and the name of the employee who sold the item.

Output

The resultant table is obtained as follows −

ID NAME DATE EMPLOYEE_NAME
1 Ramesh NULL NULL
2 Khilan 2009-11-20 00:00:00 REVATHI
3 Kaushik 2009-10-08 00:00:00 ALEKHYA
3 Kaushik 2009-10-08 00:00:00 SARIKA
4 Chaitali 2008-05-20 00:00:00 VIVEK
5 Hardik NULL NULL
6 Komal NULL NULL
7 Muffy NULL NULL

As we can see in the table above, the customer Kaushik made three orders, in which two are sold by employee Alekhya and one is sold by Sarika. Khilan and Chaitali made one order each, that are sold by Revathi and Vivek respectively. The dates on which these orders are made will also be displayed. If the orders are not made on the specific dates, NULL is returned.

Left Join with WHERE Clause

Along with the ON clause, a WHERE clause can also be applied on the obtained result-set after Left Join is implemented. Doing this will filter the data further.

Syntax

The syntax of Left Join when used with WHERE clause is given below −

SELECT column_name(s)
FROM table1
LEFT JOIN table2
ON table1.column_name = table2.column_name
WHERE condition;

Example

Records in the combined database tables can be filtered using the WHERE clause. Consider the previous two tables CUSTOMERS and ORDERS; and join them using the left join query by applying some constraints using the WHERE clause.

SELECT ID, NAME, DATE, AMOUNT FROM CUSTOMERS
LEFT JOIN ORDERS
ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID
WHERE ORDERS.AMOUNT > 2000.00;

Output

The resultant table after applying the where clause with left join contains the rows that has amount values greater than 2000.00 −

ID NAME DATE AMOUNT
3 Kaushik 2009-10-08 00:00:00 3000.00
4 Chaitali 2008-05-20 00:00:00 2060.00

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