- SQL Tutorial
- SQL - Home
- SQL - Overview
- SQL - RDBMS Concepts
- SQL - Databases
- SQL - Syntax
- SQL - Data Types
- SQL - Operators
- SQL - Expressions
- SQL Database
- SQL - Create Database
- SQL - Drop Database
- SQL - Select Database
- SQL - Rename Database
- SQL - Show Database
- SQL - Backup Database
- SQL Table
- SQL - Create Table
- SQL - Show Tables
- SQL - Rename Table
- SQL - Truncate Table
- SQL - Clone Tables
- SQL - Temporary Tables
- SQL - Alter Tables
- SQL - Drop Table
- SQL - Delete Table
- SQL - Constraints
- SQL Queries
- SQL - Insert Query
- SQL - Select Query
- SQL - Select Into
- SQL - Insert Into Select
- SQL - Update Query
- SQL - Delete Query
- SQL - Sorting Results
- SQL Views
- SQL - Create Views
- SQL - Update Views
- SQL - Drop Views
- SQL - Rename Views
- SQL Operators and Clauses
- SQL - Where Clause
- SQL - Top Clause
- SQL - Distinct Clause
- SQL - Order By Clause
- SQL - Group By Clause
- SQL - Having Clause
- SQL - AND & OR
- SQL - BOOLEAN (BIT) Operator
- SQL - LIKE Operator
- SQL - IN Operator
- SQL - ANY, ALL Operators
- SQL - EXISTS Operator
- SQL - CASE
- SQL - NOT Operator
- SQL - NOT EQUAL
- SQL - IS NULL
- SQL - IS NOT NULL
- SQL - NOT NULL
- SQL - BETWEEN Operator
- SQL - UNION Operator
- SQL - UNION vs UNION ALL
- SQL - INTERSECT Operator
- SQL - EXCEPT Operator
- SQL - Aliases
- SQL Joins
- SQL - Using Joins
- SQL - Inner Join
- SQL - Left Join
- SQL - Right Join
- SQL - Cross Join
- SQL - Full Join
- SQL - Self Join
- SQL - Delete Join
- SQL - Update Join
- SQL - Left Join vs Right Join
- SQL - Union vs Join
- SQL Keys
- SQL - Unique Key
- SQL - Primary Key
- SQL - Foreign Key
- SQL - Composite Key
- SQL - Alternate Key
- SQL Indexes
- SQL - Indexes
- SQL - Create Index
- SQL - Drop Index
- SQL - Show Indexes
- SQL - Unique Index
- SQL - Clustered Index
- SQL - Non-Clustered Index
- Advanced SQL
- SQL - Wildcards
- SQL - Comments
- SQL - Injection
- SQL - Hosting
- SQL - Min & Max
- SQL - Null Functions
- SQL - Check Constraint
- SQL - Default Constraint
- SQL - Stored Procedures
- SQL - NULL Values
- SQL - Transactions
- SQL - Sub Queries
- SQL - Handling Duplicates
- SQL - Using Sequences
- SQL - Auto Increment
- SQL - Date & Time
- SQL - Cursors
- SQL - Common Table Expression
- SQL - Group By vs Order By
- SQL - IN vs EXISTS
- SQL - Database Tuning
- SQL Function Reference
- SQL - Date Functions
- SQL - String Functions
- SQL - Aggregate Functions
- SQL - Numeric Functions
- SQL - Text & Image Functions
- SQL - Statistical Functions
- SQL - Logical Functions
- SQL - Cursor Functions
- SQL - JSON Functions
- SQL - Conversion Functions
- SQL - Datatype Functions
- SQL Useful Resources
- SQL - Questions and Answers
- SQL - Quick Guide
- SQL - Useful Functions
- SQL - Useful Resources
- SQL - Discussion
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
SQL - Right Join
Joins are used to retrieve records from multiple tables based on a given condition. A Join includes the records that satisfy the given condition and outer join results a table that contains both matched and unmatched rows.
Left Outer Join, as discussed in the previous chapter, is used to find the union of two tables with respect to the left table. In this chapter, let us discuss more about the Right outer join.
Right Join in SQL
The Right Join or Right Outer Join query in SQL 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 a NULL value in each column of the left table.
In short, 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.
Note that the resultant table displayed after implementing the Right Join is not stored anywhere in the database.
Syntax
Following is the basic syntax of Right Join in SQL −
SELECT table1.column1, table2.column2... FROM table1 RIGHT JOIN table2 ON table1.common_field = table2.common_field;
Example
The tables we are using in this example are named “Customers” and “Orders”.
Assume we are creating a table named Customers, which contains the personal details of customers including their name, age, address and salary etc.
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 (ID,NAME,AGE,ADDRESS,SALARY) VALUES (1, 'Ramesh', 32, 'Ahmedabad', 2000.00 ); INSERT INTO CUSTOMERS (ID,NAME,AGE,ADDRESS,SALARY) VALUES (2, 'Khilan', 25, 'Delhi', 1500.00 ); INSERT INTO CUSTOMERS (ID,NAME,AGE,ADDRESS,SALARY) VALUES (3, 'kaushik', 23, 'Kota', 2000.00 ); INSERT INTO CUSTOMERS (ID,NAME,AGE,ADDRESS,SALARY) VALUES (4, 'Chaitali', 25, 'Mumbai', 6500.00 ); INSERT INTO CUSTOMERS (ID,NAME,AGE,ADDRESS,SALARY) VALUES (5, 'Hardik', 27, 'Bhopal', 8500.00 ); INSERT INTO CUSTOMERS (ID,NAME,AGE,ADDRESS,SALARY) VALUES (6, 'Komal', 22, 'MP', 4500.00 ); INSERT INTO CUSTOMERS (ID,NAME,AGE,ADDRESS,SALARY) VALUES (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 | MP | 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 (OID, DATE, CUSTOMER_ID, AMOUNT) VALUES (102, '2009-10-08 00:00:00', 3, 3000.00); INSERT INTO ORDERS (OID, DATE, CUSTOMER_ID, AMOUNT) VALUES (100, '2009-10-08 00:00:00', 3, 1500.00); INSERT INTO ORDERS (OID, DATE, CUSTOMER_ID, AMOUNT) VALUES (101, '2009-11-20 00:00:00', 2, 1560.00); INSERT INTO ORDERS (OID, DATE, CUSTOMER_ID, AMOUNT) VALUES (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 | +-----+---------------------+-------------+---------+
Right join Query
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;
Output
This would produce the following result −
+------+----------+---------+---------------------+ | ID | NAME | AMOUNT | DATE | +------+----------+---------+---------------------+ | 3 | Kaushik | 3000.00 | 2009-10-08 00:00:00 | | 3 | Kaushik | 1500.00 | 2009-10-08 00:00:00 | | 2 | Khilan | 1560.00 | 2009-11-20 00:00:00 | | 4 | Chaitali | 2060.00 | 2008-05-20 00:00:00 | +------+----------+---------+---------------------+
Joining Multiple Tables with Right Join
Like Left Join, Right Join also joins multiple tables. However, the contrast occurs where the second table is returned as a whole instead of the first.
In addition, the rows of first table are matched with the rows in second table. If the records are not matched and the number of records in the second table is greater than the first, NULL is returned as the values in first table.
Syntax
Following is the syntax to join multiple tables using Right Join −
SELECT column1, column2, column3… FROM table1 RIGHT JOIN table2 ON table1.column_name = table2.column_name LEFT JOIN table3 ON table2.column_name = table3.column_name . . .
Example
Here, let us consider the previously created tables “Customers” and “Orders”; along with the newly created table “Employee”.
We will try to create the Employee table using the query below −
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); INSERT INTO EMPLOYEE VALUES (100, 'ALEKHYA', 3623); INSERT INTO EMPLOYEE VALUES (101, 'REVATHI', 1291); INSERT INTO EMPLOYEE VALUES (103, 'VIVEK', 3426); INSERT INTO EMPLOYEE VALUES (100, 'ALEKHYA', 3456);
The details of Employee table can be seen below.
+-----+---------------+------------+ | EID | EMPLOYEE_NAME | SALES_MADE | +-----+---------------+------------+ | 102 | SARIKA | 4500 | | 100 | ALEKHYA | 3623 | | 101 | REVATHI | 1291 | | 103 | VIVEK | 3426 | | 100 | ALEKHYA | 3456 | +-----+---------------+------------+
Let us try to join these three tables using the Right Join query given below −
SELECT CUSTOMERS.ID, CUSTOMERS.NAME, ORDERS.DATE, EMPLOYEE.EMPLOYEE_NAME FROM CUSTOMERS RIGHT JOIN ORDERS ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID RIGHT JOIN EMPLOYEE ON ORDERS.OID = EMPLOYEE.EID;
Through this query, we are trying to display the records of Customer IDs, Customer names, Orders made on specific dates and names of the employees that sold them.
Output
The resultant table is obtained as follows −
+------+----------+---------------------+---------------+ | ID | NAME | DATE | EMPLOYEE_NAME | +------+----------+---------------------+---------------+ | 3 | Kaushik | 2009-10-08 00:00:00 | SARIKA | | 3 | Kaushik | 2009-10-08 00:00:00 | ALEKHYA | | 2 | Khilan | 2009-11-20 00:00:00 | REVATHI | | 4 | Chaitali | 2008-05-20 00:00:00 | VIVEK | | 3 | Kaushik | 2009-10-08 00:00:00 | ALEKHYA | +------+----------+---------------------+---------------+
Right Join with WHERE Clause
A WHERE Clause is used to filter out records that satisfy the condition specified by it. This clause can be used with the Right Join technique to apply certain constraint on the records fetched as a result.
Syntax
The syntax of Right Join when used with WHERE clause is given below −
SELECT column_name(s) FROM table_name1 RIGHT JOIN table_name2 ON table_name1.column_name = table_name2.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 try to join them using the right join query by applying some constraints using the WHERE clause.
SELECT ID, NAME, DATE, AMOUNT FROM CUSTOMERS RIGHT JOIN ORDERS ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID WHERE ORDERS.AMOUNT > 1000.00;
Output
The resultant table after applying the where clause with right join contains the rows that has amount values greater than 1000.00 −
+------+----------+---------------------+---------+ | ID | NAME | DATE | AMOUNT | +------+----------+---------------------+---------+ | 3 | Kaushik | 2009-10-08 00:00:00 | 3000.00 | | 3 | Kaushik | 2009-10-08 00:00:00 | 1500.00 | | 2 | Khilan | 2009-11-20 00:00:00 | 1560.00 | | 4 | Chaitali | 2008-05-20 00:00:00 | 2060.00 | +------+----------+---------------------+---------+