• The HAVING clause is used to filter the result set based on the result of an aggregate function.
• It is typically located near or at the end of the SQL statement.
• HAVING is often coupled with the presence of the GROUP BY clause, although it is possible to have a HAVING clause without the GROUP BY clause.

Syntax:

SELECT ["column_name1"], "function type" ("column_name2")
FROM "table_name"
[GROUP BY "column_name1"]
HAVING (arithmetic function condition);

• The brackets around "column_name1" and GROUP BY "column_name1" means that they are optional.
• Note: We may select zero, one, or more columns in addition to the aggregate function. If we do select any column outside of the aggregate function, there is no need for the GROUP BY clause.

Example 1:

• We use the following table for our example.

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Table Store_Information

Store_Name	Sales	Txn_Date
Los Angeles	1500	Jan-05-1999
San Diego	250	Jan-07-1999
Los Angeles	300	Jan-08-1999
Boston	700	Jan-08-1999

• To see only the stores with sales over $1,500, we would type,

SELECT Store_Name, SUM(Sales)
FROM Store_Information
GROUP BY Store_Name
HAVING SUM(Sales) > 1500;

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Result:

Store_Name	SUM(Sales)
Los Angeles	1800

• Total sales for both San Diego and Boston are below $1,500, so the "HAVING SUM(Sales) > 1500" clause filters out these two stores.

Example 2:

• Consider the CUSTOMERS table having the following records.

ID	NAME	AGE	ADDRESS	SALARY
1	Ramesh	32	Ahmedabad	2000.00
2	Khilan	25	Delhi	1500.00
3	kaushik	23	Kota	2000.00
4	Chaitali	25	Mumbai	6500.00
5	Hardik	27	Bhopal	8500.00
6	Komal	22	MP	4500.00
7	Muffy	24	Indore	10000.00

• Following is an example, which would display a record for a similar age count that would be more than or equal to 2.

SQL > SELECT ID, NAME, AGE, ADDRESS, SALARY
FROM CUSTOMERS
GROUP BY age
HAVING COUNT(age) >= 2;

• This would produce the following result

ID	NAME	AGE	ADDRESS	SALARY
2	Khilan	25	Delhi	1500.00

SQL Having Example 1

SQL Having Example 2

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