The SQL CASE Statement

The SQL CASE statement is a conditional statement that helps us to make decisions based on a set of conditions. It evaluates the set of conditions and returns the respective values when a condition is satisfied.

The CASE statement works like a simplified IF-THEN-ELSE statement and allows for multiple conditions to be tested.

This starts with the keyword CASE followed by multiple conditionals statements. Each conditional statement consists of at least one pair of WHEN and THEN statements. Where WHEN specifies conditional statements and THEN specifies the actions to be taken.

It is often used to create a new column with values based on the value of an existing column.

Let us look at a simple scenario to understand this statement.

For e.g. when the credit limit of a customer is above ”10,000”, then the customer will be recognized as a ”High value customer when the credit limit is above ”5000”, then the customer will be recognized as a ”Mid value customer otherwise the customer will be recognized as the ”Low value customer” as shown in the table below −

Syntax

Following is the syntax of SQL CASE statement −

CASE
   WHEN condition1 THEN statement1,
   WHEN condition2 THEN statement2,
   WHEN condition THEN statementN
   ELSE result
END;

Where, condition1, condition2, etc. Are the conditional statements and statement1, statement2, etc.. are the actions to be taken when the condition is true.

Once the condition is met, the CASE statement will stop verifying further and it will return the result.

• If none of the conditions are met (TRUE), then it returns the value mentioned in the ELSE clause.

• It returns NULL if the ELSE part is not mentioned and none of the conditions are TRUE.

Example

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

In the following query, we are using multiple WHEN and THEN conditions to the CASE statement along with the ELSE clause.

If the AGE of the customer is greater than 30, it returns Gen X otherwise moves to the further WHEN and THEN conditions. If none of the conditions is matched with the CUSTOMERS table, CASE returns the ”Gen Alpha” value as mentioned in the ELSE part of the query −

SELECT NAME, AGE,
CASE
WHEN AGE > 30 THEN ''Gen X''
WHEN AGE > 25 THEN ''Gen Y''
WHEN AGE > 22 THEN ''Gen Z''
ELSE ''Gen Alpha''
END AS Generation
FROM CUSTOMERS;

Output

The output produced is as follows −

Example

Let us take a look at another query where we want to provide a 25% increment to each customer if the amount is less than 4500 from the CUSTOMERS table previously created −

SELECT *, CASE
WHEN SALARY < 4500 THEN (SALARY + SALARY * 25/100)
END AS INCREMENT FROM CUSTOMERS;

Output

Here, the SQL command checks if the salary is less than 4500. If this condition is satisfied, a new column ”INCREMENT” will contain the values that is equal to salary with 25% of increment.

Since the ELSE part is not mentioned in the above query and none of the conditions are true for few CUSTOMERS, NULL is returned, which shows that they didn”t get any increment.

CASE Statement with ORDER BY Clause

We can use CASE statement with ORDER BY clause. The ORDER BY clause in SQL sorts the result in ascending (default) or descending order.

Example

In this query, the CASE statement is used to sort the results based on either the ”NAME” column or the ”ADDRESS” column, depending on the value of the ”NAME” column. If the ”NAME” column starts with ”K”, the results are sorted by the ”NAME” column; otherwise, the results are sorted by the ”ADDRESS” column −

SELECT * FROM CUSTOMERS
ORDER BY
(CASE
    WHEN NAME LIKE ''k%'' THEN NAME
    ELSE ADDRESS
END);

Output

The result obtained by executing the above query is as shown below −

CASE Statement with GROUP BY Clause

We can also use the CASE statement with GROUP BY clause. The GROUP BY clause in SQL groups the rows that have same values within one or more columns where an aggregate function is applied to produce summaries.

Example

In the following query we are grouping the customers based on their salaries and calculate the sum of the salary for a specified range of customer data.

If the value in SALARY is less than or equal to 4000, the data will be grouped as ”Lowest paid”. If the value is greater than 4000 and less than or equal to 6500, it will be grouped as ”Average paid”. All other values will be grouped as ”Highest paid”. The SUM function is used to calculate the total of the SALARY for each group −

SELECT
   CASE
      WHEN SALARY <= 4000 THEN ''Lowest paid''
      WHEN SALARY > 4000 AND SALARY <= 6500 THEN ''Average paid''
   ELSE ''Highest paid''
      END AS SALARY_STATUS,
   SUM(SALARY) AS Total
   FROM CUSTOMERS
   GROUP BY
   CASE
      WHEN SALARY <= 4000 THEN ''Lowest paid''
      WHEN SALARY > 4000 AND SALARY <= 6500 THEN ''Average paid''
   ELSE ''Highest paid''
END;

Output

Following is the output of the above query −

CASE Statement with WHERE Clause

We can use the CASE statement with the WHERE clause as well. The WHERE clause is used to filter the rows in a table based on a specified condition.

Example

In the following query, the CASE statement is used to return the different designations of the CUSTOMERS based on their AGE. The WHERE clause is used to filter the rows based on the SALARY of the CUSTOMERS −

SELECT NAME, ADDRESS,
   CASE
      WHEN AGE < 25 THEN ''Intern''
      WHEN AGE >= 25 and AGE <= 27 THEN ''Associate Engineer''
      ELSE ''Senior Developer''
   END as Designation
FROM CUSTOMERS
WHERE SALARY >= 2000;

Output

Output of the above query is as follows −

CASE Statement with UPDATE

We can use CASE statement within the UPDATE statement to perform conditional updates on data in a table.

Example

In the following query we are updating the salary of all the customers based on their age.

If the age of the customer is equal to ”25”, their salary will be updated to ”17000”. If the age is equal to ”32”, it will be updated to ”25000”. For the customers with other ages, salaries will be updated to ”12000” −

UPDATE CUSTOMERS
SET SALARY=
CASE AGE
WHEN 25 THEN 17000
WHEN 32 THEN 25000
ELSE 12000
END;

Output

We get the following result. We can observe that the changes have been done in 7 rows −

Query OK, 7 rows affected (0.02 sec)
Rows matched: 7  Changed: 7  Warnings: 0

Verification

We can rectify the changes done in the CUSTOMERS table using the below query −

SELECT * FROM CUSTOMERS;

The table is displayed as follows −

As we can see in the above table, the SALARY of all the customers has been updated corresponding to their age.

CASE Statement with INSERT

We can also insert the data into MySQL tables with the help of the CASE statement. We need to provide the INSERT INTO statement with column names and VALUES for data insertion.

Example

Here, if the age of the customer is greater than or equal to 25, then the salary will be 23000; otherwise the salary will be 14000 −

INSERT INTO CUSTOMERS (ID, NAME, AGE, ADDRESS, SALARY)
VALUES (10, ''Viren'', 28, ''Varanasi'',
   CASE
      WHEN AGE >= 25 THEN 23000
      ELSE 14000
   END
);

Output

We get the following result. We can observe that the change has been done in 1 row −

Query OK, 1 row affected (0.01 sec)

Verification

We can rectify the changes done in the CUSTOMERS table using the below query −

SELECT * FROM CUSTOMERS;

The table is displayed as follows −

The SQL EXISTS Operator

The SQL EXISTS operator is used to verify whether a particular record exists in a MySQL table. While using this operator we need to specify the record (for which you have to check the existence) using a subquery.

The EXISTS operator is used in the WHERE clause of a SELECT statement to filter records based on the existence of related records in another table.

• It is a logical operator.

• It returns a Boolean value TRUE or FALSE.

• It returns TRUE if the subquery returns at least one record.

• If the EXISTS operator returns TRUE, the outer query will get executed; otherwise not.

• It can be used in SELECT, UPDATE, DELETE or INSERT statements.

The EXISTS operator is more efficient than other operators, such as IN, because it only needs to determine whether any rows are returned by the subquery, rather than actually returning the data.

The use of the EXISTS operator is an efficient way to filter data in many real-life scenarios, including filtering records based on the existence of related data, aggregating data based on the existence of related records, and optimizing queries.

Syntax

The basic syntax of the SQL EXISTS operator is as follows −

WHERE EXISTS (subquery);

Where, the subquery used is the SELECT statement. The EXISTS operator will evaluate to TRUE if the subquery returns at least one record in its result set; otherwise FALSE.

EXISTS Operator with SELECT Statement

The SELECT statement in SQL is used to retrieve data from one or more tables in a database. We can use the EXISTS operator with a SELECT statement to check for the existence of rows that meet a certain condition.

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 −

Let us create another table CARS, containing the details such as id of the customer, name and price of the car, using the following query −

create table CARS(
   ID INT NOT NULL,
   NAME VARCHAR(20) NOT NULL,
   PRICE INT NOT NULL,
   PRIMARY KEY(ID)
);

Using the INSERT statement, let us insert values into this table −

insert INTO CARS VALUES
(2, ''Maruti Swift'', 450000),
(4, ''VOLVO'', 2250000),
(7, ''Toyota'', 2400000);

The ”CARS” table obtained is as follows −

Now, we are retrieving the lists of the customers with the price of the car greater than 2,000,000 −

SELECT * FROM CUSTOMERS WHERE
EXISTS (
   SELECT PRICE FROM CARS
   WHERE CARS.ID = CUSTOMERS.ID AND PRICE > 2000000
);

Output

The result produced is as follows −

EXISTS Operator with UPDATE Statement

We can also use the SQL EXISTS operator with an UPDATE statement. It helps us to update rows in a table based on the existence of matching rows in another table.

Example

Suppose if we want to change the name of certain customers from the CUSTOMERS and CARS tables previously created, then this can be done using UPDATE statement. Here, we are modifying the name ”Kushal” of all the customers whose id is equal to the id of the CARS table, using the EXISTS operator, as follows −

UPDATE CUSTOMERS SET NAME = ''Kushal''
WHERE EXISTS (
   SELECT NAME FROM CARS WHERE CUSTOMERS.ID = CARS.ID
);

Output

We get the following result. We can observe that 3 rows have been modified −

Query OK, 3 rows affected (0.01 sec)
Rows matched: 3  Changed: 3  Warnings: 0

Verification

We can verify whether the changes are reflected in a table by retrieving its contents using the SELECT statement. Following is the query to display the records in the CUSTOMERS table −

SELECT * FROM CUSTOMERS;

The table is displayed as follows −

As we can see in the above table, the NAME of ”Khilan”, ”Chaitali” and ”Muffy” has been updated to ”Kushal”.

EXISTS Operator with DELETE Statement

The EXISTS operator can also be used with a DELETE statement to delete rows based on the existence of rows returned by a subquery.

Example

In here, we are deleting the row in the CUSTOMERS table whose id is equal to the id of the CARS table having price equal to ”2250000” −

DELETE FROM CUSTOMERS WHERE
EXISTS (
   SELECT * FROM CARS
   WHERE CARS.ID = CUSTOMERS.ID AND CARS.PRICE = 2250000
);

Output

We get the following result. We can observe that 1 row has been deleted −

Query OK, 1 row affected (0.01 sec)

Verification

We can rectify the changes done in the CUSTOMERS table using the following query −

SELECT * FROM CUSTOMERS;

The table is displayed as follows −

As we can see in the above table, the row with the NAME ”Chaitali” has been deleted since the id of Chaitali in CUSTOMERS table was ”4”, which is equal to the id of the CARS table having price equal to ”2250000”.

NOT Operator with EXISTS Operator

In SQL, the NOT EXISTS operator is used to select records from one table that do not exist in another table.

Syntax

Following is the basic syntax of NOT EXISTS operator in SQL −

WHERE NOT EXISTS (subquery);

Where, the subquery used is the SELECT statement.

Example

The below query gives the names of the customers who have not bought any car −

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

Output

Following output is obtained by executing the above query −

Usage of SQL EXISTS Operator

The EXISTS operator in SQL is widely used in real-life scenarios to filter records based on the existence of related data in another table. Some common use cases include −

• Checking for the existence of records in a many-to-many relationship − The EXISTS operator can be used to check whether a record exists in a join table for a many-to-many relationship, for example, finding all customers who have purchased a particular product.

• Filtering records based on the existence of related records − The EXISTS operator can be used to filter records based on the existence of related records in another table. For example, finding all orders that have associated order details.

• Aggregating data based on the existence of related records − The EXISTS operator can be used to aggregate data based on the existence of related records. For example, finding the number of customers who have placed an order.

• Optimizing queries − The EXISTS operator can be used to optimize queries by only returning the necessary data. For example, finding the first order for each customer without using a self-join.

These are just a few examples of how the EXISTS operator can be used in real-life scenarios. The specific use case will depend on the data and the requirements of the query.

The SQL ANY and ALL operators are used to perform a comparison between a single value and a range of values returned by the subquery.

The ANY and ALL operators must be preceded by a standard comparison operator i.e. >, >=, <, <=, =, <>, != and followed by a subquery. The main difference between ANY and ALL is that ANY returns true if any of the subquery values meet the condition whereas ALL returns true if all of the subquery values meet the condition.

The SQL ANY Operator

The ANY operator is used to verify if any single record of a query satisfies the required condition.

This operator returns a TRUE, if the given condition is satisfied for any of the values in the range. If none of the values in the specified range satisfy the given condition, this operator returns false. You can also use another query (subquery) along with this operator.

Syntax

The basic syntax of the SQL – ANY operator is as follows −

Column_name operator ANY (subquery);

Where,

• column_name is the name of a column in the main query.

• operator is a comparison operator such as =, <, >, <=, >=, or <>.

• subquery is a SELECT statement that returns a single column of values.

ANY with ”>” Operator

Typically, the ANY operator is used to compare a value with a set of values returned by a subquery, in such cases we can use it with the > (greater than) operator to verify if a particular column value is greater than column value of any of the records returned by the sub query.

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 −

Now, let us list out the details of all the CUSTOMERS whose SALARY is greater than the SALARY of any customer whose AGE is 32 i.e. Chaitali, Hardik, Komal and Muffy in this case −

SELECT * FROM CUSTOMERS
WHERE SALARY > ANY (SELECT SALARY FROM CUSTOMERS WHERE AGE = 32);

Output

The result obtained is as follows −

ANY with ”<” Operator

Similar to the ”>” operator, we can use the ”<” (less than) operator along with ANY to verify if a particular column value is less than column value of any of the records returned by the sub query.

Example

In here, we are finding the distinct/different age of customers having any salary less than the average salary of all the customers from the CUSTOMERS table previously created −

SELECT DISTINCT AGE FROM CUSTOMERS
WHERE SALARY < ANY (SELECT AVG(SALARY) FROM CUSTOMERS);

Output

We get the following output while executing the above query −

ANY with ”=” Operator

When we use the = (equal to) operator along with ANY, it verifies if a particular column value is equal to the column value of any of the records returned by the sub query.

Example

In the query given below, we are retrieving the details of all the customers whose age is equal to the age of any customer whose name starts with ”K” −

SELECT * FROM CUSTOMERS
WHERE AGE = ANY (SELECT AGE FROM CUSTOMERS WHERE NAME LIKE ''K%'');

Output

The result produced is as follows −

The SQL ALL Operator

The SQL ALL operator returns all the records of the SELECT statement.

• It returns TRUE if the given condition is satisfied for ALL the values in the range.

• It always returns a Boolean value.

• It is used with SELECT, WHERE and HAVING statements in SQL queries.

• The data type of the values returned from a subquery must be the same as the outer query expression data type.

Syntax

The basic syntax of the SQL ALL operator is as follows −

Column_name operator ALL (subquery);

Where,

• column_name − is the name of a column in the main query.

• operator − is a comparison operator such as =, <, >, <=, >=, or <>.

• subquery − is a SELECT statement that returns a single column of values.

ALL with WHERE Statement

When we use the ALL operator with a WHERE clause, it filters the results of the subquery based on the specified condition.

The WHERE clause in SQL is used to filter rows from a query based on specific conditions. It operates on individual rows in the table, and it allows you to specify conditions that must be met by each row in the data returned by the query.

Example

If we consider the CUSTOMERS table created above,the following query returns the details of all the customers whose salary is not equal to the salary of any customer whose age is 25 −

SELECT * FROM CUSTOMERS
WHERE SALARY <>
ALL (SELECT SALARY FROM CUSTOMERS WHERE AGE = 25);

Output

The output of the above query is as follows −

ALL with HAVING Clause

In SQL, the ALL operator can also be used with the HAVING clause to filter the results of a GROUP BY query based on a condition that applies to all the aggregated values in the group.

Example

The following SQL query is used to obtain the details of all the customers whose salary is less than the average salary −

SELECT NAME, AGE, ADDRESS, SALARY FROM CUSTOMERS
GROUP BY AGE, SALARY
HAVING SALARY < ALL (SELECT AVG(SALARY) FROM CUSTOMERS);

Output

Output of the above query is as follows −

The SQL IN Operator

The SQL IN Operator is used to specify multiple values or sub query in the WHERE clause. It returns all rows in which the specified column matches one of the values in the list. The list of values or sub query must be specified in the parenthesis e.g. IN (select query) or IN (Value1, Value2, Value3, …).

In some scenarios we may use multiple OR statements to include multiple conditions in SELECT, DELETE, UPDATE, or INSERT statements. Alternatively, we can use the IN operator instead of multiples OR statements.

The IN operator can be used with any data type in SQL. It is used to filter data from a database table based on specified values.

The IN operator is useful when you want to select all rows that match one of a specific set of values. While the OR operator is useful when you want to select all rows that match any one of multiple conditions.

Syntax

The basic syntax of the SQL IN operator to specify multiple values is as follows −

WHERE column_name IN (value1, value2, value3, ...);

Where,

• value1, value2, value3, … are the values in the list to be tested against the expression. The IN operator returns TRUE if any of these values is found in the list, and FALSE if it is not.

IN Operator with SELECT Statement

We can use the SQL IN operator to specify multiple values in a WHERE clause, and we can also use it in a SELECT statement to retrieve data that matches any of the specified values.

Here, we are using the IN operator to specify multiple values in SELECT statement.

Example

In this example, we are using the IN operator to specify multiple values in SELECT statement 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 −

Suppose based on the above table we want to display records with NAME equal to ”Khilan”, ”Hardik” and ”Muffy”(string values). This can be achieved using IN operator as follows −

SELECT * FROM CUSTOMERS
WHERE NAME IN (''Khilan'', ''Hardik'', ''Muffy'');

Output

The result obtained is as follows −

Example

The above query can also be done using OR operator. Following is an example −

SELECT * FROM CUSTOMERS
WHERE NAME = ''Khilan'' OR NAME = ''Hardik'' OR NAME = ''Muffy

Output

IN Operator with UPDATE Statement

We can also use the SQL IN operator in an UPDATE statement to update rows that match any of the specified values in a WHERE clause. The UPDATE statement is used to modify existing data in a database table.

Example

Here, we are using the IN operator to specify multiple values in the UPDATE statement and updating the CUSTOMERS table previously created. Here, we are changing the records of the customers with age ”25” or ”27” and updating the age value to ”30” −

UPDATE CUSTOMERS SET AGE = 30 WHERE AGE IN (25, 27);

Output

We get the following result. We can observe that the age of 3 customers has been modified −

Query OK, 3 rows affected (0.01 sec)
Rows matched: 3  Changed: 3  Warnings: 0

Verification

We can verify whether the changes are reflected in a table by retrieving its contents using the SELECT statement. Following is the query to display the records in the CUSTOMERS table −

SELECT * FROM CUSTOMERS;

The table is displayed as follows −

As we can see in the above table, the AGE of ”Khilan”, ”Chaitali” and ”Hardik” has been updated to ”30”.

IN Operator with NOT

To negate a condition, we use the NOT operator. The SQL IN operator can be used in combination with the NOT operator to exclude specific values in a WHERE clause. In other words, the absence of a list from an expression will be checked.

Syntax

Following is the basic syntax of NOT IN operator −

WHERE column_name NOT IN (value1, value2, ...);

Example

Now, we are displaying all the records from the CUSTOMERS table, where the AGE is NOT equal to ”25”, ”23” and ”22” −

SELECT * FROM CUSTOMERS WHERE AGE NOT IN (25, 23, 22);

Output

We obtain the result as given below −

IN Operator with Column Name

We can also use the SQL IN operator with a column name to compare the values of one column to another. It is used to select the rows in which a specific value exists for the given column.

Example

In the below query, we are selecting the rows with the value ”2000” in the SALARY column −

SELECT * FROM CUSTOMERS WHERE 2000 IN (SALARY);

Output

This would produce the following result −

Subquery with IN Operator

We can use the subquery with the IN operator that is used to return records from the single column. This means that more than one column in the SELECT column list cannot be included in the subquery.

Syntax

The basic syntax of the IN operator to specify a subquery is as follows −

WHERE column_name IN (subquery);

Where,

• Subquery − This is the SELECT statement that has a result set to be tested against the expression. The IN condition evaluates to true if any of these values match the expression.

Example

In the query given below, we are displaying all the records from the CUSTOMERS table where the NAME of the customer is obtained with SALARY greater than 2000 −

SELECT * FROM CUSTOMERS
WHERE NAME IN (SELECT NAME FROM CUSTOMERS WHERE SALARY > 2000);

Output

This will produce the following result −

The SQL LIKE Operator

The SQL LIKE operator is used to retrieve the data in a column of a table, based on a specified pattern.

It is used along with the WHERE clause of the UPDATE, DELETE and SELECT statements, to filter the rows based on the given pattern. These patterns are specified using Wildcards.

Suppose we need to submit the list of all the students whose name starts with ”K”. We can obtain this with the help of the LIKE operator as follows −

WHERE student_name LIKE ''K%

Here, the % is a wild card which represents zero, one or multiple characters. And the expression K% specifies that it will display the list of all the students whose name starts with ”k”.

The LIKE operator can be used with strings, numbers, or date values. However, using the string values is recommended.

Syntax

The basic syntax of the SQL LIKE operator is as follows −

SELECT column1, column2, ...
FROM table_name
WHERE columnn LIKE specified_pattern;

What are wild cards?

SQL wildcards are special characters used in SQL queries to match patterns in the data. Following are the wildcards used in conjunction with the LIKE operator in MySQL database −

In the LIKE operator, the above wildcard characters can be used individually as well as in combinations with each other.

The table given below has a few examples showing the WHERE clause having different LIKE operators with ”%” and ”_” −

The ”%” Wildcard character

The % sign represents zero or multiple characters. The ”%” wildcard matches any length of a string which even includes the zero length.

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 −

Now, let us display all the records from the CUSTOMERS table, where the SALARY starts with 200 −

SELECT * FROM CUSTOMERS WHERE SALARY LIKE ''200%

Output

This would produce the following result −

Example

Below is the query that displays all the records from the CUSTOMERS table previously created with the NAME that has ”al” in any position. Here, we are using multiple ”%” wildcards in the LIKE condition −

SELECT * FROM CUSTOMERS WHERE NAME LIKE ''%al%

Output

The following result is produced −

The ”_” wildcard character

The underscore wild card represents a single number or character. A single ”_” looks for exactly one character similar to the ”%” wildcard.

Example

Following is the query which would display all the records from the CUSTOMERS table previously created, where the Name starts with K and is at least 4 characters in length −

SELECT * FROM CUSTOMERS WHERE NAME LIKE ''K___%

Output

The result obtained is given below −

Example

Following is the query to display all the records from the CUSTOMERS table, where the NAME has ”m” in the third position −

SELECT * FROM CUSTOMERS WHERE NAME LIKE ''__m%

Output

We get the following result on executing the above query −

LIKE operator with OR

We can also use the LIKE operator with multiple string patterns for selecting rows by using the AND or OR operators.

Syntax

Following is the basic syntax of using LIKE operator with OR operator −

SELECT column1, column2, ...
FROM table_name
WHERE column1 LIKE pattern1 OR column2 LIKE pattern2 OR ...;

Example

Here, the SQL query retrieves the records of the customers whose name starts with C and ends with i, or customers whose name ends with k −

SELECT * FROM CUSTOMERS WHERE NAME LIKE ''C%i'' OR NAME LIKE ''%k

Output

This will produce the following result −

NOT operator with the LIKE condition

We use the NOT operator with LIKE to extract the rows which does not contain a particular string provided in the search pattern.

Syntax

Following is the basic syntax of NOT LIKE operator in SQL −

SELECT column1, column2, ...
FROM table_name
WHERE column1 NOT LIKE pattern;

Example

In the query given below, we are fetching all the customers whose name does not start with K −

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

Output

This will produce the following result −

Escape characters with LIKE operator

The escape character in SQL is used to exclude certain wildcard characters from the expression of the LIKE operator. By doing so, we can use these characters in their general sense.

Using the escape character, we can also avoid using the characters that are reserved in SQL syntax to denote specific commands, such as the single quote ”, % and _.

For example, if you need to search for % as a literal in the LIKE condition, then it is done using Escape character.

An escape character is only defined as a single character. It is suggested to choose the character which is not present in our data.

Syntax

The syntax for using the LIKE operator with escape characters is as follows −

SELECT column1, column2, ...
FROM table_name
WHERE column1 LIKE ''pattern ESCAPE escape_character

Where,

• pattern is the pattern you want to match.

• ESCAPE is the keyword that indicates the escape character

• escape_character is the character that you want to use as the escape character.

Example

Let us create a new table EMPLOYEE using the query below −

CREATE TABLE EMPLOYEE (
   SALARY DECIMAL (18,2) NOT NULL,
   BONUS_PERCENT VARCHAR (20)
);

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

INSERT INTO EMPLOYEE VALUES
(67000.00, ''45.00''),
(54000.00, ''20.34%''),
(75000.00, ''51.00''),
(84000.00, ''56.82%'');

The Employee table consists of the salary of employees in an organization and the bonus percentage in their salary as shown below −

Now, we are displaying all the records from the EMPLOYEE table, where the BONUS_PERCENT contains the % literal −

SELECT * FROM EMPLOYEE
WHERE BONUS_PERCENT LIKE''%!%%'' ESCAPE ''!

Output

This will produce the following result −

Example

In here, we are retrieving the BONUS_PERCENT that starts with 2 and contains the % literal −

SELECT * FROM EMPLOYEE
WHERE BONUS_PERCENT LIKE''2%!%%'' ESCAPE ''!

Output

Following result is obtained −

Uses of LIKE Operator in SQL

The few uses of LIKE operators are given below −

• It helps us to extract data that matches with the required pattern.

• It helps us in performing complex regex-based queries on our data.

• It simplifies the complex queries.

A Boolean is a universal data type which stores true or false values. It is used when we define a variable in a column of the table.

For instance, a customer wants a list of all the red cars. So, we can find this using the BOOLEAN operator as given in the below table −

Here, IS_RED is the BOOLEAN column that returns either TRUE or FALSE values based on the color of the cars.

The databases like PostgreSQL and PL/SQL provides the Boolean data type which is abbreviated as BOOL. Whereas the databases like MySQL and oracle SQL does not have a Boolean data type. To represent Boolean values, they provide TINYINT and BIT data type respectively.

Boolean in MySQL

MySQL provides various options for handling Boolean data. You can use BOOL, BOOLEAN, or TINYINT to represent Boolean values.

When you use BOOL or BOOLEAN, MySQL internally converts them into TINYINT. Similar to many programming languages like PHP, C, and C++, MySQL represents the TRUE literal as 1 and the FALSE literal as 0.

Example

Here, we are creating a table ”CARS” with column BOOLEAN. The query to create a table is as follows −

CREATE TABLE CARS (
   ID INT NOT NULL,
   Name VARCHAR(150),
   IsRed BOOLEAN
);

In the above example, a table is created with a BOOLEAN column IsRed. You can insert TRUE as 1 or FALSE as 0 in this column to represent the corresponding Boolean values.

Boolean in MS SQL Server

In MS SQL Server, there is no direct BOOLEAN data type. Instead, you can use the BIT data type to represent Boolean values, where 0 represents FALSE and 1 represents TRUE. The BIT data type can also accept NULL values.

Example

Following is an example to create a table with a BOOLEAN column in SQL Server −

CREATE TABLE CUSTOMERS (
   ID INT NOT NULL,
   Name VARCHAR(150),
   IsAvailable BIT
);

In the example above, a table named CUSTOMERS is created with a BOOLEAN column IsAvailable represented as a BIT data type. You can insert 0 for FALSE, 1 for TRUE, or NULL for an unknown value in this column.

Now that you understand how Boolean data types are implemented in SQL Server and MySQL, let us explore how to handle Boolean data in SQL, including filtering and querying based on Boolean columns.

Filtering Boolean Data

You can filter data based on Boolean columns in SQL. For example, in MySQL, to find all the red cars, you can use the BOOLEAN column ”IsRed” to filter for TRUE values as shown below −

SELECT * FROM CARS WHERE IsRed = TRUE;

In SQL Server, to find cars that are red, you can filter for TRUE values (IsRed = 1) as follows −

SELECT * FROM CARS WHERE IsRed = 1;

Negating Boolean Conditions

You can also negate Boolean conditions to find records that are NOT TRUE. For example, to find cars that are not red, use the following query in MySQL −

SELECT * FROM CARS WHERE IsRed = 0;

Following is the query in SQL Server −

SELECT * FROM CARS WHERE IsRed = FALSE;

Working with NULL Values

You can handle NULL values of Boolean data in SQL as well. As mentioned earlier, the BIT data type in SQL Server and the BOOL/BOOLEAN data types in MySQL can accept NULL values, which can represent unknown or unspecified conditions.

To filter records with NULL values in a Boolean column, you can use the IS NULL or IS NOT NULL condition in both MySQL and SQL Server −

-- Finding cars with unspecified availability
SELECT * FROM CARS WHERE IsAvailable IS NULL;

-- Finding cars with specified availability
SELECT * FROM CARS WHERE IsAvailable IS NOT NULL;

In the queries above, we filter cars based on whether their IsAvailable column is NULL or not NULL.

Updating Boolean Values

You can also update Boolean values in your SQL tables. To change the value of a Boolean column in MySQL, you can use the UPDATE statement as shown below −

-- Changing IsRed to TRUE for car with ID 123
UPDATE CARS SET IsRed = TRUE WHERE ID = 123;

In the above example, we updated the IsRed column for a specific car with the ID of 123, setting it to TRUE.

To update Boolean values in SQL Server, use the following query −

-- Changing IsRed to TRUE for car with ID 123
UPDATE CARS SET IsRed = 1 WHERE ID = 123;

Operators are reserved words primarily used in SQL to perform various operations on data, like addition (+), subtraction (-), or comparison (==).

Conjunctive operators, specifically used in boolean logic, combines two conditions in an SQL statement. The most common conjunctive operators are: AND (&&), which returns true if both conditions are true, and OR (||), which returns true if at least one condition is true.

The SQL AND Operator

The SQL AND returns true or 1, if both its operands evaluates to true. We can use it to combine two conditions in the WHERE clause of an SQL statement.

Syntax

The basic syntax of the SQL AND operator with a WHERE clause is as follows −

WHERE [condition1] AND [condition2];

Where, condition1, condition2 are the conditions we want to apply to the query.

You can combine N number of conditions using the AND operator. For an action to be taken by the SQL statement, whether it be a transaction or a query, all the specified conditions (separated by the AND operator) must be TRUE.

Example

Assume we have created a table with name CUSTOMERS in MySQL database using the 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 table obtained is as shown below −

Following is an example which would fetch the ID, NAME and SALARY fields from the CUSTOMERS table, where the salary is greater than 2000 and the age is less than 25 years −

SELECT ID, NAME, SALARY FROM CUSTOMERS
WHERE SALARY > 2000 AND AGE < 25;

Output

This would produce the following result −

Multiple AND Operators

You can also use multiple ”AND” operators in an SQL query to combine multiple conditions (or, expressions) together. Conditions combined with the ”AND” operators are evaluated from left to right. If any of the condition evaluate to false, the entire compound condition will be false and the record will not be included in the result set.

Syntax

Following is the syntax −

WHERE [condition1] AND [condition2]...AND [conditionN];

Example

In the following query, we are selecting all records from the CUSTOMERS table where the name of the customer starts with ”K”, the age of the customer is greater than or equal to 22, and their salary is less than 3742 −

SELECT * FROM CUSTOMERS
WHERE NAME LIKE ''k%'' AND AGE >= 22 AND SALARY < 3742;

Output

Following is the result produced −

AND with Other Logical Operators

The “AND” operator can be used in combination with other logical operators to filter records from a database table.

When using multiple logical operators in SQL, the order of operations is important. Parentheses can be used to control the order of operations and ensure that the conditions are evaluated in the correct order.

Additionally, using too many logical operators or complex expressions can negatively impact query performance, so it”s important to carefully consider the design of the WHERE clause when working with large datasets.

Example

In here, we are combining the AND operator with the NOT operator to create a NAND operation. The ”NAND” operation returns true if at least one of the input conditions is false, and false if both input conditions are true.

In the following query, we are selecting all records from the CUSTOMERS table where the condition (salary is greater than 4500 and the age is less than 26) is false. The “NOT” operator negates the entire condition, and the “AND” operator combines two conditions −

SELECT * FROM CUSTOMERS
WHERE NOT (SALARY > 4500 AND AGE < 26);

Output

Following is the output of the above query −

AND with UPDATE Statement

We can use the AND operator in the WHERE clause of the UPDATE statement to modify the rows in a table that meet certain criteria.

Syntax

Following is the syntax of using the AND operator with the UPDATE statement −

UPDATE table_name
SET column1 = value1, column2 = value2, ...
WHERE condition1 AND condition2 AND ...;

Where, table_name is the name of the table we want to update, column1, column2, etc. are the columns we want to modify, and value1, value2, etc. are the new values we want to set for those columns.

Example

In the following query, we are updating the salary of all the customers whose age is greater than 27 and updating it to ”55000” using UPDATE statement −

UPDATE CUSTOMERS SET SALARY = 55000 WHERE AGE > 27;

Output

We get the following result. We can observe that the salary of 1 customer has been modified −

Query OK, 1 row affected (0.02 sec)
Rows matched: 1  Changed: 1  Warnings: 0

Verification

To verify if the changes are reflected in the tables, we can use SELECT statement to print the tables. Following is the query to display the records in the CUSTOMERS table −

SELECT * FROM CUSTOMERS;

The table is displayed as follows −

As we can see in the above table, the salary of ”Ramesh” has been updated to ”55000” because his age is 32 i.e. greater than 27.

The SQL OR Operator

The OR operator returns true if at least one its operands evaluates to true, and false otherwise. We can combine two conditions in an SQL statement”s WHERE clause using the OR operator.

Syntax

The basic syntax of the OR operator with a WHERE clause is as follows −

WHERE [condition1] OR [condition2];

Where, condition1, condition2 are the conditions we want to apply to the query. Each condition is separated by the OR operator.

You can combine N number of conditions using the OR operator. For an action to be taken by the SQL statement, whether it be a transaction or query, at least of the conditions separated by the OR operator must be TRUE.

Example

The following query fetches the ID, NAME and SALARY fields from the CUSTOMERS table, where the salary is greater than 2000 OR the age is less than 25 years −

SELECT ID, NAME, SALARY FROM CUSTOMERS
WHERE SALARY > 2000 OR AGE < 25;

Output

This would produce the following result −

Multiple OR Operators

In SQL, it is common to use multiple OR operators to combine multiple conditions or expressions together. While using multiple OR operators, any rows that meet at least one of the conditions will be included in the result-set.

Example

In the following query, we are selecting all records from the CUSTOMERS table where either the name of the customer ends with ”l”, or the salary of the customer is greater than 10560, or their age is less than 25 −

SELECT * FROM CUSTOMERS
WHERE NAME LIKE ''%l'' OR SALARY > 10560 OR AGE < 25;

Output

Following is the result obtained −

OR with AND Operator

We can also use AND and OR operators together in SQL to combine multiple conditions in a WHERE clause to filter rows that meets the specified criteria.

Syntax

Following is the syntax for using the AND and OR operators together −

WHERE (condition1 OR condition2) AND condition3;

Where, condition1, condition2, and condition3 represent the conditions that we want to combine with the AND and OR operators. The parentheses group the first two conditions and combine them with the OR operator. The result of that operation is combined with the third condition using the AND operator.

Example

In the following query, we are retrieving all rows from the “CUSTOMERS” table where the age of the customer is equal to 25 or the salary is less than 4500 and the name is either Komal or Kaushik. The parentheses control the order of evaluation so that the OR operator is applied first, followed by the AND operator −

SELECT * FROM CUSTOMERS
WHERE (AGE = 25 OR SALARY < 4500)
AND (NAME = ''Komal'' OR NAME = ''Kaushik'');

Output

This would produce the following result −

OR with DELETE Statement

We can also use the OR operator with the DELETE statement to delete rows that meet any one of the (multiple) conditions.

Syntax

Following is the syntax of using OR operator with DELETE statement −

DELETE FROM table_name
WHERE column1 = ''value1'' OR column2 = ''value2

Example

In the following query, we are deleting the records from the CUSTOMERS table where either the age of the customer equals 25 or their salary is less than 2000 −

DELETE FROM CUSTOMERS WHERE AGE = 25 OR SALARY < 2000;

Output

We get the following result −

Query OK, 2 rows affected (0.01 sec)

Verification

To verify if the changes are reflected in the tables, we can use SELECT statement to print the tables. Following is the query to display the records in the CUSTOMERS table −

SELECT * FROM CUSTOMERS;

The table is displayed as follows −

The SQL HAVING Clause

The SQL HAVING clause is similar to the WHERE clause; both are used to filter rows in a table based on specified criteria. However, the HAVING clause is used to filter grouped rows instead of single rows. These rows are grouped together by the GROUP BY clause, so, the HAVING clause must always be followed by the GROUP BY clause.

Moreover, the HAVING clause can be used with aggregate functions such as COUNT(), SUM(), AVG(), etc., whereas the WHERE clause cannot be used with them.

Syntax

Following is the basic syntax of the SQL HAVING clause −

SELECT column1, column2, aggregate_function(column)
FROM table_name
GROUP BY column1, column2
HAVING condition;

The following code block shows the position of the HAVING Clause in a query −

SELECT
FROM
WHERE
GROUP BY
HAVING
ORDER BY

HAVING with GROUP BY Clause

We can use the HAVING clause with the GROUP BY clause to filter groups of rows that meet certain conditions. It is used to apply a filter to the result set after the aggregation has been performed.

Example

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 created is as shown below −

Now, we are grouping the records of the CUSTOMERS table based on the columns ADDRESS and AGE and filtering the groups where the AGE value is less than 25.

SELECT ADDRESS, AGE, MIN(SALARY) AS MIN_SUM
FROM CUSTOMERS
GROUP BY ADDRESS, AGE HAVING AGE > 25;

Output

The result produced is as follows −

HAVING with ORDER BY Clause

The ORDER BY clause is used to arrange/sort the records of the result of a SELECT query based on a specific column (either in ascending order or in descending order). If we use the ORDER BY clause with the HAVING clause we can sort the filtered groups in the desired order.

Example

Following query groups the records of the CUSTOMERS table based on the columns AGE and ADDRESS, filters the groups where the SALARY value is less than 5000 and, arranges the remaining groups in descending order based the total salaries of each group.

SELECT ADDRESS, AGE, SUM(SALARY) AS TOTAL_SALARY
FROM CUSTOMERS
GROUP BY ADDRESS, AGE HAVING TOTAL_SALARY >=5000
ORDER BY TOTAL_SALARY DESC;

Output

The result produced is as follows −

HAVING Clause with COUNT() Function

The HAVING clause can be used with the COUNT() function to filter groups based on the number of rows they contain.

Example

Following query groups the records of the CUSTOMERS table based on the AGE column and, retrieves the details of the group that has more than two entities −

SELECT AGE, COUNT(AGE)
FROM CUSTOMERS GROUP BY AGE HAVING COUNT(age) > 2;

Output

This would produce the following result −

Query OK, 0 rows affected (0.02 sec)

HAVING Clause with AVG() Function

The HAVING clause can also be used with the AVG() function to filter groups based on the average value of a specified column.

Example

Now, we are retrieving the city of the customers whose average salary is greater than 5240 −

SELECT ADDRESS, AVG(SALARY) as AVG_SALARY
FROM CUSTOMERS
GROUP BY ADDRESS HAVING AVG(SALARY) > 5240;

Output

Following is the output of the above query −

HAVING Clause with MAX() Function

We can also use the HAVING clause with MAX() function to filter groups based on the maximum value of a specified column.

Example

Now, we are retrieving the city of the customers whose maximum salary is greater than 5240 −

SELECT ADDRESS, MAX(SALARY) as MAX_SALARY
FROM CUSTOMERS
GROUP BY ADDRESS HAVING MAX(SALARY) > 5240;

Output

The result obtained is as follows −

The SQL DISTINCT Keyword

The SQL DISTINCT keyword is used in conjunction with the SELECT statement to fetch unique records from a table.

We use DISTINCT keyword with the SELECT statetment when there is a need to avoid duplicate values present in any specific columns/tables. When we use DISTINCT keyword, SELECT statement returns only the unique records available in the table.

The SQL DISTINCT Keyword can be associated with SELECT statement to fetch unique records from single or multiple columns/tables.

Syntax

The basic syntax of SQL DISTINCT keyword is as follows −

SELECT DISTINCT column1, column2,.....columnN
FROM table_name;

Where, column1, column2, etc. are the columns we want to retrieve the unique or distinct values from; and table_name represents the name of the table containing the data.

DISTINCT Keyword on Single Columns

We can use the DISTINCT keyword on a single column to retrieve all unique values in that column, i.e. with duplicates removed. This is often used to get a summary of the distinct values in a particular column or to eliminate redundant data.

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 table obtained is as shown below −

First, let us retrieve the SALARY values from the CUSTOMERS table using the SELECT query −

SELECT SALARY FROM CUSTOMERS ORDER BY SALARY;

This would produce the following result. Here, you can observe that the salary value 2000 is appearing twice −

Now, let us use the DISTINCT keyword with the above SELECT query and then see the result −

SELECT DISTINCT SALARY FROM CUSTOMERS ORDER BY SALARY;

Output

This would produce the following result where we do not have any duplicate entry −

DISTINCT Keyword on Multiple Columns

We can also use the DISTINCT keyword on multiple columns to retrieve all unique combinations of values across those columns. This is often used to get a summary of distinct values in multiple columns, or to eliminate redundant data.

Example

In the following query, we are retrieving a list of all unique combinations of customer”s age and salary using the DISTINCT keyword −

SELECT DISTINCT AGE, SALARY FROM CUSTOMERS ORDER BY AGE;

Output

Though the AGE column have the value “25” in two records, each combination of “25” with it”s specific ”salary” is unique, so both rows are included in the result set −

DISTINCT Keyword with COUNT() Function

The COUNT() function is used to get the number of records retuned by the SELECT query. We need to pass an expression to this function so that the SELECT query returns the number of records that satisfy the specified expression.

If we pass the DISTINCT keyword to the COUNT() function as an expression, it returns the number of unique values in a column of a table.

Syntax

Following is the syntax for using the DISTINCT keyword with COUNT() function −

SELECT COUNT(DISTINCT column_name)
FROM table_name WHERE condition;

Where, column_name is the name of the column for which we want to count the unique values; and table_name is the name of the table that contains the data.

Example

In the following query, we are retrieving the count of distinct age of the customers −

SELECT COUNT(DISTINCT AGE) as UniqueAge  FROM CUSTOMERS;

Output

Following is the result produced −

DISTINCT Keyword with NULL Values

In SQL, when there are NULL values in the column, DISTINCT treats them as unique values and includes them in the result set.

Example

First of all let us update two records of the CUSTOMERS table and modify their salary values to NULL

UPDATE CUSTOMERS SET SALARY = NULL WHERE ID IN(6,4);

The resultant CUSTOMERS table would be −

Now, we are retrieving the distinct salary of the customers using the following query −

SELECT DISTINCT SALARY FROM CUSTOMERS ORDER BY SALARY;

Output

Following is the output of the above query −

The SQL GROUP BY Clause

The SQL GROUP BY clause is used in conjunction with the SELECT statement to arrange identical data into groups. This clause follows the WHERE clause in a SELECT statement and precedes the ORDER BY and HAVING clauses (if they exist).

The main purpose of grouping the records of a table based on particular columns is to perform calculations on these groups. Therefore, The GROUP BY clause is typically used with aggregate functions such as SUM(), COUNT(), AVG(), MAX(), or MIN() etc.

For example, if you have a table named SALES_DATA containing the sales data with the columns YEAR, PRODUCT, and SALES. To calculate the total sales in an year, the GROUP BY clause can be used to group the records in this table based on the year and calculate the sum of sales in each group using the SUM() function.

Syntax

Following is the basic syntax of the SQL GROUP BY clause −

SELECT column_name(s)
FROM table_name
GROUP BY column_name(s);

Where, column_name(s) refers to the name of one or more columns in the table that we want to group the data by and the table_name refers to the name of the table that we want to retrieve data from.

GROUP BY Clause with Aggregate Functions

Typically, we group the record of a table to perform calculations on them. Therefore, the SQL GROUP BY clause is often used with the aggregate functions such as SUM(), AVG(), MIN(), MAX(), COUNT(), etc.

Example

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 created is as shown below −

The following SQL query groups the CUSTOMERS table based on AGE and counts the number of records in each group −

SELECT AGE, COUNT(Name) FROM CUSTOMERS GROUP BY AGE;

Output

Following is the result produced −

Example

In the following query, we are finding the highest salary for each age −

SELECT AGE, MAX(salary) AS MAX_SALARY
FROM CUSTOMERS GROUP BY AGE;

Output

Following is the output of the above query −

Similarly we can group the records of the CUSTOMERS table based on the AGE column and calculate the maximum salary, average and sum of the SALARY values in each group using the MIN(), AVG() and SUM() functions respectively.

GROUP BY Clause on Single Columns

When we use the GROUP BY clause with a single column, all the rows in the table that have the same value in that particular column will be merged into a single record.

Example

In the following example we are grouping the above created CUSTOMERS table by the ADDRESS column and calculating the average salary of the customer from each city −

SELECT ADDRESS, AVG(SALARY) as AVG_SALARY
FROM CUSTOMERS GROUP BY ADDRESS;

Output

This would produce the following result −

GROUP BY Clause with Multiple Columns

When we use the GROUP BY clause with multiple columns, all the rows in the table that have the same values in all of the specified columns will be merged into a single group.

Example

In the following query we are grouping the records of the CUSTOMERS table based on the columns ADDRESS and AGE and −

SELECT ADDRESS, AGE, SUM(SALARY) AS TOTAL_SALARY
FROM CUSTOMERS GROUP BY ADDRESS, AGE;

Output

This would produce the following result −

GROUP BY with ORDER BY Clause

We can use the ORDER BY clause with GROUP BY in SQL to sort the grouped data by one or more columns.

Syntax

Following is the syntax for using ORDER BY clause with GROUP BY clause in SQL −

SELECT column1, column2, ..., aggregate_function(columnX) AS alias
FROM table
GROUP BY column1, column2, ...
ORDER BY column1 [ASC | DESC], column2 [ASC | DESC], ...;

Example

In here, we are finding the highest salary for each age, sorted by high to low −

SELECT AGE, MIN(SALARY) AS MIN_SALARY
FROM CUSTOMERS
GROUP BY AGE ORDER BY MIN_SALARY DESC;

Output

Following is the result produced −

GROUP BY with HAVING Clause

We can also use the GROUP BY clause with the HAVING clause filter the grouped data in a table based on specific criteria.

Syntax

Following is the syntax for using ORDER BY clause with HAVING clause in SQL −

SELECT column1, column2, aggregate_function(column)
FROM table_name
GROUP BY column1, column2
HAVING condition;

Example

In the following query, we are grouping the customers by their age and calculating the minimum salary for each group. Using the HAVING clause we are filtering the groups where the age is greater than 24 −

SELECT ADDRESS, AGE, MIN(SALARY) AS MIN_SUM
FROM CUSTOMERS
GROUP BY ADDRESS, AGE HAVING AGE>24;

Output

The result produced is as follows −