The SQL EXCEPT Operator

The EXCEPT operator in SQL is used to retrieve all the unique records from the left operand (query), except the records that are present in the result set of the right operand (query).

In other words, this operator compares the distinct values of the left query with the result set of the right query. If a value from the left query is found in the result set of the right query, it is excluded from the final result.

For better understanding consider two tables with records as shown in the following image −

If we perform the EXCEPT operator on the above two tables to retrieve the names, it will display the distinct records only from the first table which are not in common with the records of the second table.

Here, “Dev” is common in both tables. So, the EXECPT operator will eliminate it and retrieves only “Sara” and “Jay” as output.

MySQL database does not support the EXCEPT operator. Instead of this, we can use the DISTINCT keyword along with the LEFT JOIN clause to retrieve distinct values from the left table.

Syntax

Following is the SQL syntax of the EXCEPT operator in Microsoft SQL server −

SELECT column1, column2,..., columnN
FROM table1, table2,..., tableN
[Conditions] //optional
EXCEPT
SELECT column1, column2,..., columnN
FROM table1, table2,..., tableN
[Conditions] //optional

The number and order of columns in both SELECT statements should be the same.

Example

First of all, let us create a table named STUDENTS using the following query −

CREATE TABLE STUDENTS(
   ID INT NOT NULL,
   NAME VARCHAR(20) NOT NULL,
   SUBJECT VARCHAR(20) NOT NULL,
   AGE INT NOT NULL,
   HOBBY VARCHAR(20) NOT NULL,
   PRIMARY KEY(ID)
);

Let”s insert some values into the table using the following query −

INSERT INTO STUDENTS VALUES
(1, ''Naina'', ''Maths'', 24, ''Cricket''),
(2, ''Varun'', ''Physics'', 26, ''Football''),
(3, ''Dev'', ''Maths'', 23, ''Cricket''),
(4, ''Priya'', ''Physics'', 25, ''Cricket''),
(5, ''Aditya'', ''Chemistry'', 21, ''Cricket''),
(6, ''Kalyan'', ''Maths'', 30, ''Football''),
(7, ''Aditya'', ''Chemistry'', 21, ''Cricket''),
(8, ''Kalyan'', ''Chemistry'', 32, ''Cricket'');

The table produced is as shown below −

Now, let us create another table named STUDENTS_HOBBY using the following query −

CREATE TABLE STUDENTS_HOBBY(
   ID INT NOT NULL,
   NAME VARCHAR(20) NOT NULL,
   HOBBY VARCHAR(20) NOT NULL,
   AGE INT NOT NULL,
   PRIMARY KEY(ID)
);

Once the table is created, let us insert some values to the table using the query below −

INSERT INTO STUDENTS_HOBBY VALUES
(1, ''Vijay'', ''Cricket'', 18),
(2, ''Varun'', ''Football'', 26),
(3, ''Surya'', ''Cricket'', 19),
(4, ''Karthik'', ''Cricket'', 25),
(5, ''Sunny'', ''Football'', 26),
(6, ''Dev'', ''Cricket'', 23);

The table created is as follows −

Now, let us perform the except operation on the above two tables −

SELECT NAME, HOBBY, AGE FROM STUDENTS
EXCEPT
SELECT NAME, HOBBY, AGE FROM STUDENTS_HOBBY;

Output

Output of the above query is as shown below −

EXCEPT with BETWEEN Operator

We can use the EXCEPT operator with the BETWEEN operator in SQL to exclude records that fall within a specified range.

Example

In the following SQL query, we are retrieving the records of students aged between 20 and 30 from the STUDENTS table, excluding those who are also aged between 20 and 30 from the STUDENTS_HOBBY table −

SELECT NAME, HOBBY, AGE
FROM STUDENTS
WHERE AGE BETWEEN 20 AND 30
EXCEPT
SELECT NAME, HOBBY, AGE
FROM STUDENTS_HOBBY
WHERE AGE BETWEEN 20 AND 30

Output

When we execute the program query, the output is obtained as follows −

Except with IN Operator

The IN operator is used to filter a result set based on a list of specified values. We can also use the EXCEPT operator with the IN operator in SQL to exclude records that matches values in the specified list.

Example

Here, we are retrieving the records of students with Cricket as a hobby, from the STUDENTS table, excluding those who also have Cricket as hobby from the STUDENTS_HOBBY table −

SELECT NAME, HOBBY, AGE FROM STUDENTS
WHERE HOBBY IN(''Cricket'')
EXCEPT
SELECT NAME, HOBBY, AGE FROM STUDENTS_HOBBY
WHERE HOBBY IN(''Cricket'')

Output

Following is the output of the above query −

EXCEPT with LIKE Operator

The LIKE operator is used to perform pattern matching on a string. The EXCEPT operator can also be used with the LIKE operator in SQL to exclude rows that matches with the specified pattern.

Example

In here, we are retrieving records from the STUDENTS table where the values in the HOBBY column starts with ”F”, while excluding similar rows from the STUDENTS_HOBBY table −

SELECT ID, NAME, HOBBY, AGE FROM STUDENTS
WHERE HOBBY LIKE ''F%''
EXCEPT
SELECT ID, NAME, HOBBY, AGE FROM STUDENTS_HOBBY
WHERE HOBBY LIKE ''F%

Output

The output for the above query is produced as given below −

In mathematical set theory, the intersection of two sets is a collection of values that are common to both sets.

In real-time scenarios, there will be a huge number of tables in a database that contains information. The user may find it challenging to gather common information from various tables. So we use the INTERSECT operator to accomplish that. It helps to retrieve the common data from various tables.

The SQL INTERSECT Operator

The INTERSECT operator in SQL is used to retrieve the records that are identical/common between the result sets of two or more tables.

Let us consider the below tables as an example to get a better understanding −

If we perform the intersection operation on both tables described above using the INTERSECT operator, it returns the common records which are Dev and Aarohi.

MySQL database does not support the INTERSECT operator. Instead of this, we can use the DISTINCT operator along with the INNER JOIN clause to retrieve common records from two or more tables.

Syntax

Following is the SQL syntax of INTERSECT operator in Microsoft SQL Server −

SELECT column1, column2,..., columnN
FROM table1, table2,..., tableN
INTERSECT
SELECT column1, column2,..., columnN
FROM table1, table2,..., tableN

There are some mandatory rules for INTERSECT operations such as the number of columns, data types, and other columns must be the same in both SELECT statements for the INTERSECT operator to work correctly.

Example

First of all, let us create a table named STUDENTS using the following query −

CREATE TABLE STUDENTS(
   ID INT NOT NULL,
   NAME VARCHAR(20) NOT NULL,
   SUBJECT VARCHAR(20) NOT NULL,
   AGE INT NOT NULL,
   HOBBY VARCHAR(20) NOT NULL,
   PRIMARY KEY(ID)
);

Let”s insert some values into the table using the following query −

INSERT INTO STUDENTS VALUES
(1, ''Naina'', ''Maths'', 24, ''Cricket''),
(2, ''Varun'', ''Physics'', 26, ''Football''),
(3, ''Dev'', ''Maths'', 23, ''Cricket''),
(4, ''Priya'', ''Physics'', 25, ''Cricket''),
(5, ''Aditya'', ''Chemistry'', 21, ''Cricket''),
(6, ''Kalyan'', ''Maths'', 30, ''Football'');

The table produced is as shown below −

Now, let us create another table named STUDENTS_HOBBY using the following query −

CREATE TABLE STUDENTS_HOBBY(
   ID INT NOT NULL,
   NAME VARCHAR(20) NOT NULL,
   HOBBY VARCHAR(20) NOT NULL,
   AGE INT NOT NULL,
   PRIMARY KEY(ID)
);

Once the table is created, let us insert some values to the table using the query below −

INSERT INTO STUDENTS_HOBBY VALUES
(1, ''Vijay'', ''Cricket'', 18),
(2, ''Varun'', ''Football'', 26),
(3, ''Surya'', ''Cricket'', 19),
(4, ''Karthik'', ''Cricket'', 25),
(5, ''Sunny'', ''Football'', 26),
(6, ''Dev'', ''Cricket'', 23);

The table created is as follows −

Now, we are retrieving the common records from both the tables using the following query −

SELECT NAME, AGE, HOBBY FROM STUDENTS_HOBBY
INTERSECT
SELECT NAME, AGE, HOBBY FROM STUDENTS;

Output

When we execute the above query, the output is obtained as follows −

INTERSECT with BETWEEN Operator

We can use the INTERSECT operator with the BETWEEN operator in SQL to find records that fall within a specified range.

Example

Now, let us retrieve the name, age, and hobby of students aged between 25 and 30 from both the ”STUDENTS” and ”STUDENTS_HOBBY” tables, returning only the common rows within the specified age range −

SELECT NAME, AGE, HOBBY FROM STUDENTS_HOBBY
WHERE AGE BETWEEN 25 AND 30
INTERSECT
SELECT NAME, AGE, HOBBY FROM STUDENTS
WHERE AGE BETWEEN 20 AND 30;

Output

The output for the above query is produced as given below −

INTERSECT with IN Operator

We can also use the INTERSECT operator with the IN operator in SQL to find the common records that exists in the specified list of values. The IN operator is used to filter a result set based on a list of specified values.

Example

The following SQL query returns the name, age, and hobby of students who have ”Cricket” as their hobby in both ”STUDENTS” and ”STUDENTS_HOBBY” tables −

SELECT NAME, AGE, HOBBY FROM STUDENTS_HOBBY
WHERE HOBBY IN(''Cricket'')
INTERSECT
SELECT NAME, AGE, HOBBY FROM STUDENTS
WHERE HOBBY IN(''Cricket'');

Output

When we execute the above query, the output is obtained as follows −

INTERSECT with LIKE Operator

The LIKE operator is used to perform pattern matching on a string. The INTERSECT operator can also be used with the LIKE operator in SQL to find the common rows that matches with the specified pattern.

Example

The query below retrieves the names that start with ”V” using the wildcard ”%” in the LIKE operator from the common names of both tables −

SELECT NAME, AGE, HOBBY FROM STUDENTS_HOBBY
WHERE NAME LIKE ''v%''
INTERSECT
SELECT NAME, AGE, HOBBY FROM STUDENTS
WHERE NAME LIKE ''v%

Output

The output for the above query is produced as given below −

UNION and UNION ALL operators are just the SQL implementation of algebraic set operators. Both of them are used to retrieve the rows from multiple tables and return them as one single table. The difference between these two operators is that UNION only returns distinct rows while UNION ALL returns all the rows present in the tables.

However, for these operators to work on these tables, they need to follow the conditions given below −

• The tables to be combined must have the same number of columns with the same datatype.
• The number of rows need not be the same.

Once these criterion are met, UNION or UNION ALL operator returns the rows from multiple tables as a resultant table.

Column names of first table will become column names of the resultant table, and contents of second table will be merged into resultant columns of same data type.

What is UNION?

UNION is a type of operator/clause in SQL, that works similar to the union operator in relational algebra. It just combines the information from multiple tables that are union compatible.

Only distinct rows from the tables are added to the resultant table, as UNION automatically eliminates all the duplicate records.

Syntax

Following is the syntax of UNION operator in SQL −

SELECT * FROM table1
UNION
SELECT * FROM table2;

Example

Let us first create two tables COURSES_PICKED and EXTRA_COURSES_PICKED with the same number of columns having the same data types.

Create table COURSES_PICKED using the following query −

CREATE TABLE COURSES_PICKED(
   STUDENT_ID INT NOT NULL,
   STUDENT_NAME VARCHAR(30) NOT NULL,
   COURSE_NAME VARCHAR(30) NOT NULL
);

Insert values into the COURSES_PICKED table with the help of the query given below −

INSERT INTO COURSES_PICKED VALUES
(1, ''JOHN'', ''ENGLISH''),
(2, ''ROBERT'', ''COMPUTER SCIENCE''),
(3, ''SASHA'', ''COMMUNICATIONS''),
(4, ''JULIAN'', ''MATHEMATICS'');

The table will be displayed as shown below −

Now, let us create another table EXTRA_COURSES_PICKED using the following query −

CREATE TABLE EXTRA_COURSES_PICKED(
   STUDENT_ID INT NOT NULL,
   STUDENT_NAME VARCHAR(30) NOT NULL,
   EXTRA_COURSE_NAME VARCHAR(30) NOT NULL
);

Following is the query to insert values into the “EXTRA_COURSES_PICKED” table −

INSERT INTO EXTRA_COURSES_PICKED VALUES
(1, ''JOHN'', ''PHYSICAL EDUCATION''),
(2, ''ROBERT'', ''GYM''),
(3, ''SASHA'', ''FILM''),
(4, ''JULIAN'', ''MATHEMATICS'');

The table will be created as shown below −

Now, let us combine both of these tables using the UNION query as follows −

SELECT * FROM COURSES_PICKED
UNION
SELECT * FROM EXTRA_COURSES_PICKED;

Output

The resultant table obtained after performing the UNION operation is as follows −

What is UNION ALL?

UNION ALL is also an operator/clause in SQL, that is used to combine multiple tables into one table. However, this operator also preserves the duplicate rows in the resultant tables.

Suppose there are two tables, one of which contains the number of games a player competed in internationally and the other contains the number of games a player played nationally.

As we can see in the tables above, Kohli played 234 matches internationally and 234 matches nationally. Even though the data in these columns is the same, they are all separate matches. There is a need to include both rows in the resultant table displaying the total matches played by a player. So, we use the UNION ALL operator in such cases.

Syntax

Following is the syntax of UNION ALL operator in SQL −

SELECT * FROM table1
UNION ALL
SELECT * FROM table2;

Example

In the following example, let us perform UNION ALL operation on the same sample tables given above: “COURSES_PICKED” and “EXTRA_COURSES_PICKED”, using the given query below −

SELECT * FROM COURSES_PICKED
UNION ALL
SELECT * FROM EXTRA_COURSES_PICKED;

Output

The resultant table is displayed as follows −

The SQL BETWEEN Operator

The BETWEEN operator is a logical operator in SQL, that is used to retrieve the data within a specified range. The retrieved values can be integers, characters, or dates.

You can use the BETWEEN operator to replace a combination of “greater than equal AND less than equal” conditions.

Let us understand it in a better way by using the below example table −

Suppose we want to list out the names from the above table who are aged BETWEEN 20 and 30. So, we will get “Varma(21)”, “Nikhil(25)”, and “Bhargav(29)” as a result.

Syntax

Following is the syntax of the BETWEEN operator in SQL −

SELECT column1, column2, column3,....columnN
FROM table_name
WHERE column BETWEEN value1 AND value2;

Here,

• value1 is the beginning value of the range.
• value2 is the ending value of the range (inclusive).

Example

First of all, let us create a table named CUSTOMERS 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)
);

Once the table is created, let us insert some values into the table using the following INSERT query −

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 created is as follows −

Now, we are using the BETWEEN operator to retrieve the details of the CUSTOMERS whose AGE (numeric data) is between 20 and 25 −

SELECT * FROM CUSTOMERS WHERE AGE BETWEEN 20 AND 25;

Output

When we execute the above query, the output is obtained as follows −

Example

Here, we are using the BETWEEN operator with characters. Let us retrieve the details of the customers whose names starts in between the alphabets “A” and “L” using the following query −

SELECT * FROM CUSTOMERS WHERE NAME BETWEEN ''A'' AND ''L

Output

Following is the output of the above query −

BETWEEN Operator with IN Operator

In SQL, we can combine the BETWEEN operator with the IN operator to select values that are within a specified range and also matches with values specified in the list of IN clause.

Example

In the following query, we are retrieving the details of all the customers whose salary is between 4000 and 10000. In addition, we are only retrieving the customers who lives in Hyderabad and Bhopal using the IN operator in SQL −

SELECT * FROM CUSTOMERS
WHERE SALARY BETWEEN 4000 AND 10000
  AND ADDRESS IN (''Hyderabad'', ''Bhopal'');

Output

On executing the above query, the output is displayed as follows −

BETWEEN Operator with UPDATE Statement

We can also use the BETWEEN operator with the UPDATE statement to update values within the specified range. The UPDATE statement is used to modify existing data in a database table.

Example

Let us update the salaries of the customers whose age lies between 25 to 30 using the following query −

UPDATE CUSTOMERS SET SALARY = 10000
WHERE AGE BETWEEN 25 AND 30;

Output

The output for the above query is as given below −

Query OK, 3 rows affected (0.02 sec)
Rows matched: 3  Changed: 3  Warnings: 0

Verification

Let us verify whether the salaries are updated or not using the following query −

SELECT * FROM CUSTOMERS;

The table for the above query produced as given below −

BETWEEN Operator with DELETE Statement

We can also use the BETWEEN operator with the DELETE statement to delete rows within a specified range.

Example

Now, let us delete the customers whose age is between 20 and 24 using the DELETE statement −

DELETE FROM CUSTOMERS
WHERE AGE BETWEEN 20 AND 24;

Output

If we compile and run the above query, the result is produced as follows −

Query OK, 3 rows affected (0.02 sec)

Verification

Let us verify whether the records with the specified age values are deleted or not, using the following query −

SELECT * FROM CUSTOMERS;

The table for the above query produced is as given below −

NOT BETWEEN Operator

The NOT BETWEEN operator in SQL works exactly opposite to BETWEEN operator. This is used to retrieve the data which is not present in the specified range.

Let us understand in a better way by using the below example table −

Suppose we want to list out the students from the above table who are aged not between 20 and 30. So, we will get “Prudhvi(45) and Ganesh(33)” as result.

Syntax

Following is the syntax of the NOT BETWEEN operator in SQL −

SELECT column_name1, column_name2, column_name3,......column_nameN
FROM table_name
WHERE column_name NOT BETWEEN value1 AND value2;

Example

Consider the previously created CUSTOMERS table and let us retrieve the details of customers whose age is not greater than or equal to 25 and less than or equal to 30 (numeric data) using the following query −

SELECT * FROM CUSTOMERS
WHERE AGE NOT BETWEEN 25 AND 30;

Output

When we execute the above query, the output is obtained as follows −

NOT BETWEEN Operator with IN

We can use the NOT BETWEEN operator in combination with the IN operator to select values that are outside a range and also do not match with the specified list of values.

Example

In the following query, we are selecting the customers whose salary is not between 1000 and 5000. In addition; we are not retrieving the customers who are living in Bhopal using the IN operator in SQL −

SELECT * FROM CUSTOMERS
WHERE SALARY NOT BETWEEN 1000 AND 5000
  AND ADDRESS NOT IN (''Bhopal'');

Output

On executing the above query, the output is displayed as follows −

In a table, columns can typically accept NULL values by default. However, if you want to ensure that a particular column does not contain NULL values, you need to add the NOT NULL constraint/condition on that column.

The SQL NOT NULL Constraint

The NOT NULL constraint in SQL is used to ensure that a column in a table doesn”t contain NULL (empty) values, and prevent any attempts to insert or update rows with NULL values.

Usually, if we don”t provide value to a particular column while inserting data into a table, by default it is considered as a NULL value. But, if we add the NOT NULL constraint on a column, it will enforce that a value must be provided for that column during the data insertion, and attempting to insert a NULL value will result in a constraint violation error.

Syntax

Following is the basic syntax of NOT NULL constraint while creating a table −

CREATE TABLE table_name (
   column1 datatype NOT NULL,
   column2 datatype,
   column3 datatype NOT NULL,
   ...
);

Creating NOT NULL Constraint On a Table

To add the NOT NULL constraint on a column of a table, we just need to add the keyword “NOT NULL” after the column”s data type in the column definition.

Example

First of all, let us create a table named CUSTOMERS 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 (20, 2),
   PRIMARY KEY (ID)
);

Let”s insert some values into the above created table using the following INSERT query −

INSERT INTO CUSTOMERS VALUES
(1, ''Ramesh'', ''32'', ''Ahmedabad'', 2000),
(2, ''Khilan'', ''25'', ''Delhi'', 1500),
(3, ''Kaushik'', ''23'', ''Kota'', 2500),
(4, ''Chaitali'', ''25'', ''Mumbai'', 6500),
(5, ''Hardik'',''27'', ''Bhopal'', 8500),
(6, ''Komal'', ''22'', ''Hyderabad'', 9000),
(7, ''Muffy'', ''24'', ''Indore'', 5500);

The table will be created as shown below −

Verification

To display the structure of a table in MySQL database, we use the DESCRIBE command. The DESCRIBE command provides a summary of the columns, data types, and various attributes of the table as shown below −

DESCRIBE CUSTOMERS;

As we can see in the output below, the table shows information about the column names of the table, their types, and whether they are nullable or not.

Removing a NOT NULL Constraint From the Table

In SQL, to remove a NOT NULL constraint of a column in an existing table, we need to use the ALTER TABLE statement. Using this statement, we can modify the definition of a column i,e you can change the name, data type or constraint of an existing column.

One of a way to remove the NOT NULL constraint on a column is to changing it to NULL.

Syntax

Following is the syntax to remove a not null constraint from the table in MySQL database −

ALTER TABLE table_name
MODIFY COLUMN column_name datatype NULL;

Were,

• table_name is the name of the table that contains the columns we want to modify.
• column_name is the name of the column that has the NOT NULL constraint you want to remove.
• datatype is the data type of the column.

Example

Following is the query to modify the constraint on the NAME column of the CUSTOMERS table to NULL in MySQL database −

ALTER TABLE CUSTOMERS MODIFY COLUMN NAME VARCHAR(20) NULL;

Output

On executing the above query, the output is displayed as follows −

Query OK, 0 rows affected (0.10 sec)
Records: 0  Duplicates: 0  Warnings: 0

Verification

Now, let us display the structure of the table named “CUSTOMERS” using the following query −

DESCRIBE CUSTOMERS;

As we can see in the table below, the column “NAME” is modified to nullable, which means NULL values are allowed in this column.

Adding a NOT NULL Constraint to the Existing Table

In the previous section, we have removed the NOT NULL constraint on a column by changing its definition using the ALTER TABLE statement. Similarly, we can add a NOT NULL constraint to a column in an existing table using the ALTER TABLE statement.

Syntax

Following is the SQL syntax to add the NOT NULL constraint to the existing column in MySQL database −

ALTER TABLE table_name
MODIFY COLUMN column_name datatype NOT NULL;

Example

Assume the previously created table CUSTOMERS and let us modify the ADDRESS column ensuring that it does not allow null values using the following query −

ALTER TABLE CUSTOMERS MODIFY COLUMN ADDRESS CHAR(25) NOT NULL;

Output

When we execute the above query, the output is obtained as follows −

Query OK, 0 rows affected (0.08 sec)
Records: 0  Duplicates: 0  Warnings: 0

Verification

We can display the structure of the CUSTOMERS table using the following query −

DESCRIBE CUSTOMERS;

As we can see in the output below, the column “ADDRESS” is modified, which means NULL values are NOT allowed in this column.

The SQL UNION Operator

The SQL UNION operator is used to combine data from multiple tables by eliminating duplicate rows (if any).

To use the UNION operator on multiple tables, all these tables must be union compatible. And they are said to be union compatible if and only if they meet the following criteria −

• The same number of columns selected with the same datatype.
• These columns must also be in the same order.
• They need not have same number of rows.

Once these criterion are met, the UNION operator returns the rows from multiple tables as a resultant table which is void of all duplicate values from these tables.

The column names in the final result set will be based on the column names selected in the first SELECT statement. If you want to use a different name for a column in the final result set, you can use an alias in the SELECT statement.

Syntax

The basic syntax of a UNION operator is as follows −

SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]
UNION
SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition];

Here, the given condition could be any given expression based on your requirement.

UNION on a Single Field

If we want to use UNION to combine the result sets of two or more SELECT statements on a single field, we can simply include that field in the SELECT statement of each query. The UNION operator will automatically remove any duplicate values in the final result set.

When using UNION on a single field, the column names in the result set will be determined by the column name in the first SELECT statement. Therefore, you may need to use an alias in the SELECT statement to ensure that the column name is meaningful for the final result set.

Example

Assume we have created a table with name CUSTOMERS in MySQL database using CREATE TABLE statement as shown below −

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)
);

Following query inserts values into this table using the INSERT statement −

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 CUSTOMERS table is as follows −

Now, creating the second table ORDERS using CREATE TABLE statement as shown below −

CREATE TABLE ORDERS (
   OID INT NOT NULL,
   DATE DATETIME NOT NULL,
   CUSTOMER_ID INT NOT NULL,
   AMOUNT INT NOT NULL,
   PRIMARY KEY (OID)
);

Following query inserts values into this table using the INSERT statement −

INSERT INTO ORDERS VALUES
(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);

The ORDERS table is as follows −

Using the following query, let us combine the SALARY and AMOUNT columns from CUSTOMERS and ORDERS table (since these columns have similar datatypes) −

SELECT SALARY FROM CUSTOMERS UNION SELECT AMOUNT FROM ORDERS;

Output

Output of the above query is as follows −

UNION on Multiple Fields

When we use UNION on multiple fields, the number and order of the fields in each SELECT statement must match. Also, the data types of the fields in each SELECT statement must be compatible for the UNION to work correctly. If the data types are not compatible, you may need to use conversion functions such as CAST or CONVERT to ensure that the data types match.

Example

As the CUSTOMERS and ORDERS tables are not union-compatible individually, let us first join these two tables into a bigger table using Left Join and Right Join. The joined tables retrieved will have same number of columns with same datatypes, becoming union compatible. Now, these tables are combined using UNION query shown below −

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

Output

This would produce the following result −

UNION with WHERE Clause

We can use the WHERE clause with UNION operator to filter the results of each SELECT statement before combining them.

Syntax

Following is the syntax for using the WHERE clause with UNION operator −

SELECT column1, column2, column3
FROM table1
WHERE column1 = ''value1''
UNION
SELECT column1, column2, column3
FROM table2
WHERE column1 = ''value2

Example

In the following query, we are retrieving the id”s of the customers where id is greater than 5 and 2 from the ”CUSTOMERS” and ”ORDERS” tables respectively −

SELECT ID, SALARY FROM CUSTOMERS WHERE ID > 5
UNION
SELECT CUSTOMER_ID, AMOUNT FROM ORDERS WHERE CUSTOMER_ID > 2;

Output

Following is the result produced −

UNION with ORDER BY Clause

When we use UNION with ORDER BY clause, it combines the sorted result sets of all SELECT statements and produces a single sorted result set.

Example

In here, we are retrieving the id”s of the customers where id is greater than 5 and 2 from the ”CUSTOMERS” and ”ORDERS” tables respectively, sorted low to high from their salary −

SELECT ID, SALARY FROM CUSTOMERS WHERE ID > 5
UNION
SELECT CUSTOMER_ID, AMOUNT FROM ORDERS WHERE CUSTOMER_ID > 2
ORDER BY SALARY;

Output

Following is the output of the above query −

The ORDER BY clause in a UNION statement applies to the entire result set, not just the last SELECT statement.

UNION with Aliases

We can use aliases in the SELECT statement of UNION operator to give a table or column a temporary name, which can be useful when working with multiple tables or columns with similar names.

When using UNION with aliases, it”s important to note that the column aliases are determined by the first SELECT statement. Therefore, if you want to use different aliases for the same column in different SELECT statements, you need to use column aliases in all SELECT statements to ensure consistent column names in the final result set.

Syntax

Following is the syntax for using Union with Aliases −

SELECT column1 AS alias1, column2 AS alias2
FROM table1
UNION
SELECT column3 AS alias1, column4 AS alias2
FROM table2;

Example

The following query retrieves all the id”s from both tables, along with an indication of whether each id is of the customer or the order made by them −

SELECT ID, ''customer'' AS type FROM CUSTOMERS
UNION
SELECT OID, ''order'' AS type FROM ORDERS;

Output

Following is the output produced −

There are two other operators which are like the UNION operator.

• SQL − This is used to combine two SELECT statements, but returns rows only from the first SELECT statement that are identical to a row in the second SELECT statement.

• SQL − This combines two SELECT statements and returns rows from the first SELECT statement that are not returned by the second SELECT statement.

A NULL value indicates a missing or unknown value. It appears to be blank and does not contain any data. It is very important to understand that a NULL value is different than a zero value or a field that contains spaces. For checking null values we can use two basic operators.

• IS NULL
• IS NOT NULL

The SQL IS NOT NULL Operator

The SQL IS NOT NULL operator is used to filter data by verifying whether a particular column has a not-null values. This operator can be used with SQL statements such as SELECT, UPDATE, and DELETE.

By using the IS NOT NULL operator, we can only fetch the records that contain valid data in a particular column.

Syntax

Following is the syntax of the SQL IS NOT NULL operator −

SELECT column_names
FROM table_name
WHERE column_name IS NOT NULL;

Example

Firstly, let us create a table named CUSTOMERS using the following query −

CREATE TABLE CUSTOMERS(
   ID INT NOT NULL,
   NAME VARCHAR(20),
   AGE INT,
   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'', NULL ),
(2, ''Khilan'', 25, NULL, 1500.00 ),
(3, ''Kaushik'', NULL, ''Kota'', 2000.00 ),
(4, ''Chaitali'', 25, ''Mumbai'', NULL ),
(5, ''Hardik'', 27, ''Bhopal'', 8500.00 ),
(6, ''Komal'', NULL, ''Hyderabad'', 4500.00 ),
(7, ''Muffy'', 24, NULL, 10000.00 );

The table will be created as follows −

Example

In the following query, we are going to return all the records from the CUSTOMERS table where the ADDRESS is not null −

SELECT * FROM CUSTOMERS WHERE ADDRESS IS NOT NULL;

Output

On executing the above query, it will generate the output as shown below −

IS NOT NULL with COUNT() Function

We can use the IS NOT NULL operator along with the SQL COUNT() function to count only the non-null values in a specific column.

Syntax

Following is the syntax of IS NOT NULL operator with the COUNT() function −

SELECT COUNT(column_name)
FROM table_name
WHERE condition IS NOT NULL;

Example

The following query returns the count of all rows in the CUSTOMERS table where the SALARY column is not null −

SELECT COUNT(*) FROM CUSTOMERS WHERE SALARY IS NOT NULL;

Output

The output produced is as shown below −

IS NOT NULL with DELETE Statement

In SQL, we can delete all rows that do not contain NULL values in a specific column using the DELETE statement with IS NOT NULL operator.

Syntax

Following is the syntax of the IS NOT NULL operator with the DELETE statement in SQL −

DELETE FROM table_name
WHERE columnname1, columnname2, ... IS NOT NULL;

Example

In the following query, we are deleting records which are not null in the SALARY column of the CUSTOMERS table −

DELETE FROM CUSTOMERS WHERE SALARY IS NOT NULL;

Output

We get the following result −

Query OK, 5 rows affected (0.02 sec)

Verification

Execute the SELECT query given below to check whether the table has been changed or not −

SELECT * FROM CUSTOMERS;

If we compile and run the program, the result is produced as follows −

IS NOT NULL with UPDATE Statement

We can use the UPDATE statement with the IS NOT NULL operator in SQL to update records with not-null records in a particular column.

Syntax

Following is the syntax of the IS NOT NULL operator with the UPDATE statement in SQL −

UPDATE table_name
SET column1 = value1, column2 = value2, ...
WHERE columnname1, columnname2, ... IS NOT NULL;

Example

Truncate the CUSTOMERS table and reinsert all the 7 records into it again. The following query, increments all the values in the SALARY column of the with 5000, where the salary value is not null −

UPDATE CUSTOMERS SET SALARY = SALARY+5000 WHERE SALARY IS NOT NULL;

Output

When we execute the program above, the output is obtained as follows −

Query OK, 5 rows affected (0.01 sec)
Rows matched: 5  Changed: 5  Warnings: 0

Verification

To check whether the table has been updated or not, execute the SELECT query below −

SELECT * FROM CUSTOMERS;

The table is displayed as follows −

Let”s assume a table with NULL values in some of its fields. These fields indicate that no values are present in them. SQL allows users to create new records or modify existing ones without specifying a value for a field. If no value is provided, the field is stored with a NULL value.

In SQL, it is not possible to check NULL values with comparison operators such as =, <, or <>. Instead, we use the IS NULL and IS NOT NULL (negation of NULL values) operators.

The SQL IS NULL Operator

The SQL IS NULL operator is used to check whether a value in a column is NULL. It returns true if the column value is NULL; otherwise false.

The NULL is a value that represents missing or unknown data, and the IS NULL operator allows us to filter for records that contain NULL values in a particular column.

Syntax

Following is the syntax of IS NULL operator −

SELECT column_name1, column_name2, column_name3, ... , column_nameN
FROM table_name
WHERE column_nameN IS NULL;

Example

Firstly, let us create a table named CUSTOMERS using the following query −

CREATE TABLE CUSTOMERS(
 ID INT NOT NULL,
 NAME VARCHAR(20),
 AGE INT,
 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'', NULL ),
(2, ''Khilan'', 25, NULL, 1500.00 ),
(3, ''Kaushik'', NULL, ''Kota'', 2000.00 ),
(4, ''Chaitali'', 25, ''Mumbai'', NULL ),
(5, ''Hardik'', 27, ''Bhopal'', 8500.00 ),
(6, ''Komal'', NULL, ''Hyderabad'', 4500.00 ),
(7, ''Muffy'', 24, NULL, 10000.00 );

The table will be created as follows −

IS NULL with SELECT Statement

We can use the IS NULL operator with a SELECT statement to filter the records with NULL values.

Example

In the following query, we are retrieving all the records from the CUSTOMERS table where the ADDRESS is null −

SELECT * FROM CUSTOMERS WHERE ADDRESS IS NULL;

Output

On executing the above query, it will generate the output as shown below −

IS NULL with COUNT() Function

We can also use the IS NULL operator with the COUNT() function in SQL to count the number of records with NULL values in a particular column.

Syntax

Following is the syntax of IS NULL operator with the COUNT() function −

SELECT COUNT(column_name)
FROM table_name
WHERE condition IS NULL;

Example

The following query returns the count of records have a blank field (NULL) in SALARY column of the CUSTOMERS table −

SELECT COUNT(*) FROM CUSTOMERS WHERE SALARY IS NULL;

Output

The output produced is as shown below −

IS NULL with UPDATE Statement

We can use the UPDATE statement with the “IS NULL” operator in SQL to update records with NULL values in a particular column.

Syntax

Following is the syntax of the IS NULL operator with the UPDATE statement in SQL −

UPDATE table_name
SET column1 = value1, column2 = value2, ...
WHERE columnname1, columnname2, ... IS NULL;

Example

In the following query, we are updating the blank (NULL) records of the AGE column to a value of 48 −

UPDATE CUSTOMERS SET AGE = 48 WHERE AGE IS NULL;

Output

When we execute the program above, the output is obtained as follows −

Query OK, 2 rows affected (0.01 sec)
Rows matched: 2  Changed: 2  Warnings: 0

Verification

To check whether the table has been updated or not, execute the SELECT query below −

SELECT * FROM CUSTOMERS;

The table is displayed as follows −

IS NULL with DELETE Statement

We can also use the DELETE statement with IS NULL operator to delete records with NULL values in a particular column.

Syntax

Following is the syntax of the IS NULL operator with the DELETE statement in SQL −

DELETE FROM table_name
WHERE columnname1, columnname2, ... IS NULL;

Example

In the following query, we are deleting the blank (NULL) records present in the SALARY column of CUSTOMERS table −

DELETE FROM CUSTOMERS WHERE SALARY IS NULL;

Output

We get the following result −

Query OK, 2 rows affected (0.01 sec)

Verification

Execute the SELECT query given below to check whether the table has been changed or not −

SELECT * FROM CUSTOMERS;

If we compile and run the program, the result is produced as follows −

The SQL NOT EQUAL Operator

The SQL NOT EQUAL operator is used to compare two values and return true if they are not equal. It is represented by “<>” and “!=”. The difference between these two is that <> follows the ISO standard, but != doesn”t. So, it is recommended to use the <> operator.

We can use the NOT EQUAL operator in WHERE clause to filter records based on a specific condition and in GROUP BY clause to group the results.

The comparison is case-sensitive by default, while using the NOT EQUAL operator with text values.

Syntax

Following is the syntax of the NOT EQUAL operator in SQL −

WHERE expression1 <> expression2;

Example

To understand it better let us consider the CUSTOMERS table which contains the personal details of customers including their name, age, address and salary etc. as shown below −

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 follows −

NOT EQUAL with Text

We can use the NOT EQUAL operator with text in SQL to compare two text values and return. We can use “<>” or “!=” in the WHERE clause of a SQL statement and exclude rows that match a specific text value.

Example

In the following query, we are retrieving all the records from the CUSTOMERS table whose NAME is not ”Ramesh” −

SELECT * FROM CUSTOMERS WHERE NAME <> ''Ramesh

Output

The output of the above code is as shown below −

NOT EQUAL with GROUP BY Clause

We can use the NOT EQUAL operator with the GROUP BY clause to group the results by the values that are not equal to the specified text value.

The aggregate functions such as COUNT(), MAX(), MIN(), SUM(), and AVG() are frequently used with the GROUP BY statement.

Example

Here, we are retrieving the number of records with distinct ages (excluding ”22”) in the ”CUSTOMERS” table and grouping them by age value −

SELECT COUNT(ID), AGE FROM CUSTOMERS
WHERE AGE <> ''22'' GROUP BY AGE;

Output

On executing the above query, it will generate the output as shown below −

NOT EQUAL with Multiple Conditions

The not equal operator can also be used with multiple conditions in a WHERE clause to filter out rows that match specific criteria.

Example

Now, we are retrieving all the customers whose salary is either “>2000” or “=2000“. At the same time, the customer must not be from “Bhopal” −

SELECT * FROM CUSTOMERS
WHERE ADDRESS <> ''Bhopal'' AND (SALARY>''2000'' OR SALARY=''2000'');

Output

Following is the output of the above code −

Negating a Condition Using NOT EQUAL

In SQL, the NOT EQUAL operator can also be combined with the NOT Operator to negate a condition. It filters out the rows that meet a specific condition.

Example

In the following query, we are retrieving all rows from the “CUSTOMERS” table where the “SALARY” is equal to ”2000” −

SELECT * FROM CUSTOMERS WHERE NOT SALARY != ''2000

Output

After executing the above code, we get the following output −

Most of the times, there is a need to use two or more conditions to filter required records from a table; but sometimes satisfying one of the conditions would be enough. There are also scenarios when you need to retrieve records that do not satisfy the conditions specified. SQL provides logical connectives for this purpose. They are listed below −

• AND − Operator

• OR − Operator

• NOT − Operator

With the help of these logical connectives, one can retrieve records that are required and also create exceptions for the records that are not needed to be retrieved.

The SQL NOT Operator

SQL NOT is a logical operator/connective used to negate a condition or Boolean expression in a WHERE clause. That is, TRUE becomes FALSE and vice versa.

The most common scenario where this operator can be used occurs when there is a specification of what NOT to include in the result table, instead of what to include.

For instance, in an Indian voting system, people younger than 18 years of age are NOT allowed to vote. Therefore, while retrieving the information of all people who are eligible to vote, using the NOT operator, we can create an exception to minors since it is the only specification.

The NOT operator is always used in a WHERE clause so its scope within the clause is not always clear. Hence, a safer option to exactly execute the query is by enclosing the Boolean expression or a subquery by parentheses.

Syntax

Following is the syntax for SQL NOT operator −

NOT [CONDITION or BOOLEAN EXPRESSION];

Example

In the following example, let us first create a table to demonstrate the usage of NOT operator.

Using the query below, 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 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 follows −

The SQL query below retrieves all rows from the ”CUSTOMERS” table where the ”SALARY” column is not greater than 2000.00 −

SELECT * FROM CUSTOMERS WHERE NOT (SALARY > 2000.00);

Output

Following is the output of the above query −

SQL NOT Operator with LIKE

The LIKE operator uses wildcards to perform pattern matching on the records of a table before extracting the matched records.

However, to negate this operation (to extract the unmatched records instead), we can use the NOT operator along with LIKE in the form of NOT LIKE keyword.

Example

Using the following query, we are retrieving all rows from the ”CUSTOMERS” table where the ”NAME” column does not start with the letter ”K” −

SELECT * FROM CUSTOMERS WHERE NAME NOT LIKE ''K%

Output

On executing the query above, the table will be displayed as follows −

SQL NOT Operator with IN

The IN operator returns TRUE if the values in a table column belong to a range of numbers specified in the WHERE clause.

To negate this operation, we can use the NOT IN operator instead. With this, the Boolean expression returns TRUE if the records are not present in the given range.

Example

The following SQL query selects all rows from the ”CUSTOMERS” table where the ”AGE” column does not have values 25, 26, or 32 −

SELECT * FROM CUSTOMERS WHERE AGE NOT IN (25, 26, 32);

Output

The result table is displayed as follows −

SQL NOT Operator with IS NULL

The IS NULL operator is used to check whether the records in a table are NULL. If a NULL value is encountered, it returns TRUE; and FALSE otherwise.

Using NOT operator with the IS NULL operator, we can extract all the records that does not contain NULL values.

Example

This SQL query retrieves all rows from the ”CUSTOMERS” table where the ”AGE” column is not null, i.e. it contains valid age values −

SELECT * FROM CUSTOMERS WHERE AGE IS NOT NULL;

Output

The result table is exactly as the original table as it contains no NULL values −

However, if the table contains any NULL values, the rows containing it will be omitted in the resultant table.

SQL NOT Operator with BETWEEN

BETWEEN operator is used to establish a range as a condition. When used with WHERE clause, this operator acts like a Boolean expression. That is, if values of a table column fall in the specified range, TRUE is returned; and FALSE otherwise.

Using NOT BETWEEN operator with WHERE clause will return its negation. That is, if values of a table column fall in the specified range, FALSE is returned; and TRUE otherwise.

Example

With the given query below, we are displaying records in the CUSTOMERS table whose salary does not fall between 1500.00 and 2500.00 −

SELECT * FROM CUSTOMERS
WHERE SALARY NOT BETWEEN 1500.00 AND 2500.00;

Output

The resultant table is as follows −

SQL NOT Operator with EXISTS

The EXISTS operator works similar to the IN operator; it compares the table records with the specified range in the WHERE clause. However, the IN operator cannot compare the NULL records with the range while EXISTS does.

The NOT EXISTS operator is used to negate this operation.

Example

In the following example, let us create another table Orders to help in demonstrating the usage of NOT operator with EXISTS operator −

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 −

Following query is used to print the IDs of customers in CUSTOMERS table that do not exist in the ORDERS table −

SELECT * FROM CUSTOMERS WHERE NOT EXISTS (
SELECT CUSTOMER_ID FROM ORDERS
WHERE ORDERS.CUSTOMER_ID = CUSTOMERS.ID);

Output

The output obtained after executing the query is as follows −