SQL Left Join
- Join operation in SQL is used to combine multiple tables together into a single table.
- If we use left join to combine two different tables, then we will get all the records from the left table. But we will get only those records from the right table, which have the corresponding key in the left table. Rest other records in the right table for which the common column value doesn't match with the common column value of the left table; then, it is displayed as NULL.
- Let us take a look at the syntax of writing a query to perform the left join operation in SQL.
-
SELECT TableName1.columnName1, TableName2.columnName2 FROM TableName1 LEFT JOIN TableName2 ON TableName1.ColumnName = TableName2.ColumnName;
Now let us see take a deeper dive into the left join in SQL with the help of examples. All the queries in the examples will be written using the MySQL database.
Consider we have the following tables with the given data:
Table 1: employee
| EmployeeID | Employee_Name | Employee_Salary |
|---|---|---|
| 1 | Arun Tiwari | 50000 |
| 2 | Sachin Rathi | 64000 |
| 3 | Harshal Pathak | 48000 |
| 4 | Arjun Kuwar | 46000 |
| 5 | Sarthak Gada | 62000 |
| 6 | Saurabh Sheik | 53000 |
| 7 | Shubham Singh | 29000 |
| 8 | Shivam Dixit | 54000 |
| 9 | Vicky Gujral | 39000 |
| 10 | Vijay Bose | 28000 |
Table 2: department
| DepartmentID | Department_Name | Employee_ID |
|---|---|---|
| 1 | Production | 1 |
| 2 | Sales | 3 |
| 3 | Marketing | 4 |
| 4 | Accounts | 5 |
| 5 | Development | 7 |
| 6 | HR | 9 |
| 7 | Sales | 10 |
Table 3: Loan
| LoanID | Branch | Amount |
|---|---|---|
| 1 | B1 | 15000 |
| 2 | B2 | 10000 |
| 3 | B3 | 20000 |
| 4 | B4 | 100000 |
| 5 | B5 | 150000 |
| 6 | B6 | 50000 |
| 7 | B7 | 35000 |
| 8 | B8 | 85000 |
Table 4: Borrower
| CustID | CustName | LoanID |
|---|---|---|
| 1 | Sonakshi Dixit | 1 |
| 2 | Shital Garg | 4 |
| 3 | Swara Joshi | 5 |
| 4 | Isha Deshmukh | 2 |
| 5 | Swati Bose | 7 |
| 6 | Asha Kapoor | 10 |
| 7 | Nandini Shah | 9 |
Table 5: customer
| Customer_ID | Name | Age | Salary |
|---|---|---|---|
| 1 | Aryan Jain | 51 | 56000 |
| 2 | Arohi Dixit | 21 | 25000 |
| 3 | Vineet Garg | 24 | 31000 |
| 4 | Ajeet Singh | 23 | 32000 |
| 5 | Ravi Rathod | 23 | 42000 |
| 6 | Paras Aggrawal | 22 | 50000 |
| 7 | Sonakshi Kapadiya | 24 | 28000 |
| 8 | Sonali Kapoor | 28 | 82000 |
Table 6: orders
| Order_ID | Order_Date | Cutomer_ID | Amount |
|---|---|---|---|
| 1 | 2012-01-20 | 2 | 3000 |
| 2 | 2012-05-18 | 2 | 2000 |
| 3 | 2012-06-28 | 3 | 4000 |
| 4 | 2012-04-11 | 4 | 5000 |
| 5 | 2012-05-04 | 8 | 8000 |
Example 1:
Write a query to perform the left join operation considering the employee table as the left table and the department table as the right table.
Query:
We have used the SELECT command to retrieve EmployeeID, Employee_Name, Employee_Salary, DepartmentID, Department_Name present in the employee and department table. Then we have used the LEFT JOIN keyword to perform the left join operation on the employee and department table where 'e' and 'd' are aliases. These two tables are joined on the column EmployeeID which is present in both the tables.
You will get the following output:
| EmployeeID | Employee_Name | Employee_Salary | DepartmentID | Department_Name |
|---|---|---|---|---|
| 1 | Arun Tiwari | 50000 | 1 | Production |
| 2 | Sachin Rathi | 64000 | NULL | NULL |
| 3 | Harshal Pathak | 48000 | 2 | Sales |
| 4 | Arjun Kuwar | 46000 | 3 | Marketing |
| 5 | Sarthak Gada | 62000 | 4 | Accounts |
| 6 | Saurabh Sheik | 53000 | NULL | NULL |
| 7 | Shubham Singh | 29000 | 5 | Development |
| 8 | Shivam Dixit | 54000 | NULL | NULL |
| 9 | Vicky Gujral | 39000 | 6 | HR |
| 10 | Vijay Bose | 28000 | 7 | Sales |
EmployeeID, Employee_Name, Employee_Salary, DepartmentID, Department_Name are retrieved from employee and department tables. All the records from the employee table are retrieved. Only those records that have a corresponding EmployeeID in the employee table are retrieved from the department table. Rest other records in the department table for which an EmployeeID doesn't match with the EmployeeID of the employee table; then, it is displayed as NULL.
Example 2:
Write a query to perform the left join operation considering the loan table as the left table and the borrower table as the right table.
Query:
We have used the SELECT command to retrieve LoanID, Branch, Amount, CustID, CustName present in the loan and borrower table. Then we have used the LEFT JOIN keyword to perform the left join operation on the loan and borrower table where 'l' and 'b' are aliases. These two tables are joined on the column LoanID which is present in both the tables.
You will get the following output:
| LoanID | Branch | Amount | CustID | CustName |
|---|---|---|---|---|
| 1 | B1 | 15000 | 1 | Sonakshi Dixit |
| 2 | B2 | 10000 | 4 | Isha Deshmukh |
| 3 | B3 | 20000 | NULL | NULL |
| 4 | B4 | 100000 | 2 | Shital Garg |
| 5 | B5 | 150000 | 3 | Swara Joshi |
| 6 | B6 | 50000 | NULL | NULL |
| 7 | B7 | 35000 | 5 | Swati Bose |
| 8 | B8 | 85000 | NULL | NULL |
LoanID, Branch, Amount, CustID, CustName are retrieved from loan and borrower tables. All the records from the loan table are retrieved. Only those records that have a corresponding LoanID in the loan table are retrieved from the borrower table. Rest other records in the borrower table for which a LoanID doesn't match with the LoanID of the loan table; then, it is displayed as NULL.
Example 3:
Write a query to perform the left join operation considering the customer table as the left table and the orders table as the right table.
Query:
We have used the SELECT command to retrieve Customer_ID, Name, Age, Salary, Order_ID, Order_Date, Amount present in customer and orders table. Then we have used the LEFT JOIN keyword to perform left join operation on the customer and orders table where 'c' and 'o' are aliases. These two tables are joined on the column Customer_ID which is present in both the tables.
You will get the following output:
| Customer_ID | Name | Age | Salary | Order_ID | Order_Date | Amount |
|---|---|---|---|---|---|---|
| 1 | Aryan Jain | 51 | 56000 | NULL | NULL | NULL |
| 2 | Arohi Dixit | 21 | 25000 | 1 | 2012-01-20 | 3000 |
| 2 | Arohi Dixit | 21 | 25000 | 2 | 2012-05-18 | 2000 |
| 3 | Vineet Garg | 24 | 31000 | 3 | 2012-06-28 | 4000 |
| 4 | Ajeet Singh | 23 | 32000 | 4 | 2012-04-11 | 5000 |
| 5 | Ravi Rathod | 23 | 42000 | NULL | NULL | NULL |
| 6 | Paras Aggrawal | 22 | 50000 | NULL | NULL | NULL |
| 7 | Sonakshi Kapadiya | 24 | 28000 | NULL | NULL | NULL |
| 8 | Sonali Kapoor | 28 | 82000 | 5 | 2012-05-04 | 8000 |
Customer_ID, Name, Age, Salary, Order_ID, Order_Date, Amount are retrieved from customer and orders tables. All the records from the customer table are retrieved. Only those records that have a corresponding Customer_ID in the customer table are retrieved from the orders table.
