DbSchema Tutorial | SQL HAVING CLAUSE

Publish on DbSchema Blog >>>

Structured Query Language (SQL) is a potent tool for handling relational databases. One of its vital features is the HAVING clause, which allows us to filter results after performing an aggregate function. This article delves deep into the world of the HAVING clause, distinguishing it from WHERE, and showcasing its applications with various aggregate functions.

1. Introduction to SQL HAVING CLAUSE

The HAVING clause is used in SQL to filter the results of aggregate functions like SUM, AVG, MAX, etc. Unlike the WHERE clause, which filters rows before aggregation, HAVING filters after the aggregation is completed.

Syntax:

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

2. Differentiate between SQL HAVING vs WHERE

Attribute	SQL HAVING	SQL WHERE
Purpose	Filters aggregated data	Filters individual rows
Use with	Typically with GROUP BY	Used without GROUP BY (though can be used with)
Position in SQL	Comes after GROUP BY	Comes before GROUP BY

3. Using Aggregate Functions with HAVING

a. Using SUM Function

Example: Let’s consider a sample table Orders:

OrderID	ProductName	Quantity
1	Apples	50
2	Bananas	30
3	Apples	20

If we want to find products that have a total quantity greater than 40:

SELECT ProductName, SUM(Quantity) as TotalQuantity
FROM Orders
GROUP BY ProductName
HAVING SUM(Quantity) > 40;

Result:

ProductName	TotalQuantity
Apples	70

b. Using MIN Function

Finding products with the minimum order quantity less than 25:

SELECT ProductName, MIN(Quantity) as MinimumQuantity
FROM Orders
GROUP BY ProductName
HAVING MIN(Quantity) < 25;

Result:

ProductName	MinimumQuantity
(No results matching the criteria)

c. Using AVG Function

Finding products with an average quantity below 30:

SELECT ProductName, AVG(Quantity) as AverageQuantity
FROM Orders
GROUP BY ProductName
HAVING AVG(Quantity) < 30;

Result:

ProductName	AverageQuantity
Bananas	30

d. Using MAX Function

Finding products with a maximum order quantity greater than 60:

SELECT ProductName, MAX(Quantity) as MaximumQuantity
FROM Orders
GROUP BY ProductName
HAVING MAX(Quantity) > 60;

Result:

ProductName	MaximumQuantity
(No results matching the criteria)

4. HAVING with GROUP BY and ORDER BY Clauses

a. Filtering Rows Using WHERE and HAVING

Filtering products with a total quantity greater than 20 and grouping those with a total quantity greater than 40:

SELECT ProductName, SUM(Quantity) as TotalQuantity
FROM Orders
WHERE Quantity > 20
GROUP BY ProductName
HAVING SUM(Quantity) > 40;

b. Filtering Rows on Multiple Values Using HAVING

Finding products with a total quantity between 30 and 70:

SELECT ProductName, SUM(Quantity) as TotalQuantity
FROM Orders
GROUP BY ProductName
HAVING SUM(Quantity) BETWEEN 30 AND 70;

Result:

ProductName	TotalQuantity
Apples	70
Bananas	30

c. HAVING with GROUP BY Clause

Grouping by product name and filtering products with a total quantity greater than 40:

SELECT ProductName, SUM(Quantity) as TotalQuantity
FROM Orders
GROUP BY ProductName
HAVING SUM(Quantity) > 40;

Result:

ProductName	TotalQuantity
Apples	70

d. HAVING with ORDER BY Clause

Ordering the grouped results by total quantity in descending order:

SELECT ProductName, SUM(Quantity) as TotalQuantity
FROM Orders
GROUP BY ProductName
HAVING SUM(Quantity) > 40
ORDER BY TotalQuantity DESC;

Result:

ProductName	TotalQuantity
Apples	70

e. HAVING Clause with COUNT() Function

Finding products that have been ordered more than once:

SELECT ProductName, COUNT(OrderID) as NumberOfOrders
FROM Orders
GROUP BY ProductName
HAVING COUNT(OrderID) > 1;

Result:

ProductName	NumberOfOrders
Apples	2

5. Common Mistakes & FAQs

Mistakes

1. Using HAVING without GROUP BY:

   • The HAVING clause is typically used to filter aggregated results. Without the GROUP BY clause, there’s often little reason to use HAVING. While some databases might allow this, it’s a misuse of the clause’s intent.

2. Confusing the order of SQL operations:

   • It’s crucial to remember the sequence: FROM -> WHERE -> GROUP BY -> HAVING -> SELECT -> ORDER BY. Trying to filter aggregated results using WHERE instead of HAVING will throw an error.

3. Using non-aggregated columns in the HAVING clause without them being in the GROUP BY clause:

   • This is a common error. If you’re trying to use a column in the HAVING clause that’s not part of an aggregate function, it must also appear in the GROUP BY clause.

4. Over-relying on HAVING:

   • While HAVING is powerful, it shouldn’t replace WHERE for basic row-level filtering. Use WHERE wherever possible to reduce the size of the result set early in the processing.

FAQs

1. Can we use WHERE and HAVING together?

   • Yes, and it’s common to do so. WHERE filters rows before aggregation, while HAVING filters after aggregation.

2. Why is my HAVING clause not recognizing a column that’s in my SELECT statement?

   • This typically occurs when trying to filter on a column that’s not a part of an aggregate function or the GROUP BY clause. If you’re grouping results, every column in the SELECT that’s not part of an aggregate function needs to be included in the GROUP BY clause.

3. Can I use aggregate functions in the WHERE clause instead of HAVING?

   • No, aggregate functions cannot be used in the WHERE clause. If you need to filter based on the result of an aggregate function, you should use the HAVING clause.

4. Is HAVING exclusive to SQL?

   • While the concept of filtering on aggregated data is not unique to SQL, the HAVING clause, as described in this article, is SQL-specific.

5. Can I use HAVING without any aggregate functions?

   • Technically, yes, some databases might allow this, but it’s not standard practice. The purpose of HAVING is to filter aggregated results, so using it without aggregations can be confusing and misrepresents its intent.

6. Practice Questions

1. Write a SQL statement to find products that have an average quantity below 30.
2. Find the minimum order quantity for each product, but only display products with a minimum order of more than 20.
3. How would you list products that have been ordered more than 3 times, based on the Orders table?

---

By integrating comprehensive explanations with practical examples, we aim to offer an in-depth understanding of the SQL HAVING clause. Remember, practice is key. Experiment with different scenarios and datasets to refine your SQL skills.

Happy Querying