Adventures in Machine Learning

Exploring the Power and Use Cases of Non-Equi JOINs in SQL

Non-Equi JOINs in SQL

If you’re interested in SQL data analytics or work for a real estate agency with a rental business, you’ve likely come across JOIN statements. Specifically, you may have heard of two types of JOINs: equi JOIN and non-equi JOIN.

While equi JOIN brings together matching columns from two different tables, non-equi JOIN has less stringent conditions for matching. Let’s dive deeper into what non-equi JOIN is, some use cases, and advanced scenarios.

Equi JOIN vs. Non-Equi JOIN

An equi JOIN matches values from two tables by comparing values in their respective columns.

Specifically, it compares equality, which can be expressed using the “=” operator. On the other hand, a non-equi JOIN compares values using operators like “>”, “<", ">=”, “<=" that express non-equality condition.

The result is joining rows that satisfy a given condition rather than a specific value. Non-equi JOIN is often used when we’re comparing difference across rows rather than between columns.

Getting to Know the Data

Imagine you are running a database for a real estate firm that specializes in rentals. Your company has been selling out properties in different regions, and you want to understand the most preferred district in each region based on bedrooms and rent.

You have two tables: one has information about customers and the other identifies preferred districts. By using non-equi JOIN, you’d be able to associate preference with your highly valued customers.

This process provides a fundamental way to segment customers based on their preferences in each region, bedroom selection and rent payment preference.

Use Cases for Non-Equi JOINs

Now that we have an understanding of non-equi JOIN’s wider comparison capabilities, let’s explore some of the most common use cases.

Listing All (Unique) Pairs of Items

If you are interested in understanding all unique pairs of items in two different tables, you can use non-equi JOIN to perform that task. Such a technique helps in building co-occurrence matrices and mining association rules.

In the rental business scenario, we can generate useful insights by observing how the market deals with the relationships between properties, sales, and customer preferences.

Identifying Duplicates

For identifying duplicates across two tables, non-equi JOIN helps to compare values between tables instead of simply comparing equality. For example, finding customers who could have mistakenly rented more than one house or identifying duplicate houses that customers might attempt to rent two or more times.

Joining Tables Using a Range of Values

Non-equi JOINs are especially useful for joining tables using a range of values. When you want to match data items from both tables based on an inequality condition, non-equi JOIN might do just that for you.

For example, pulling data by district based on rental prices and bedroom sizes, finding all the preferred districts within a region based on the conditions set, thereby giving recommendations on the most preferred districts.

Advanced Scenarios for Using Non-Equi JOINs

Sometimes, the standard use cases might not be enough for your specific needs. In this case, it’s better to explore advanced scenarios.

Optimizing Computing Running Totals

When performing cumulative computations, e.g., a running total of agent fees for completed deals, non-equi JOINs functionality takes computation to another level. It helps in giving you a reliable output as opposed to using an equi JOIN statement in the conventional way.

Solving Conflicts Between LEFT JOINs and WHERE

Equi JOIN and WHERE can lead to false positives. Suppose we have two tables, ‘houses’ and ‘matching deals,’ and we want to find all the houses listed up for a deal and all houses that have deals.

We will do this by taking only houses that have matching deals and all the houses listed if no one meets the conditions. Using WHERE filters identifies data that doesn’t meet conditions, which can lead to false results.

In this case, we can use non-equi JOINs to help distinguish the false positives using two consecutive conditions.

Writing Code and Interactive Exercises

If you are struggling to put your newfound theoretical knowledge into practice, interactive exercises can help you learn practically. They provide realistic scenarios that put your newly acquired knowledge to the test, giving you an edge over your peers.

For additional resources on learning JOINs and other SQL basics, consider taking an SQL JOINs course or a SQL basics course.


In conclusion, non-equi JOIN statements allow you to compare tables based on operators such as “<", ">“, “<=", ">=”, rather than ‘=’. This flexibility has practical uses such as joining tables based on larger inequality conditions, computing running totals and analysis of duplicates.

Practical exercises and joining an SQL JOINs course can put your learning into practice. Non-equi JOINs and equi JOINs are both crucial SQL tools used to match values from two tables.

The former uses operators that express non-equality matching conditions, while the latter uses an equal sign expression. When it comes to non-equi JOINs, use cases include identifying duplicates, listing all unique pairs of items, and joining tables using a range of values.

Advanced scenarios for using non-equi JOINs include computing running totals and solving conflicts between LEFT JOINs and WHERE. Ultimately, learning JOINs and using them practically through interactive exercises is beneficial, therefore it is important to take an SQL JOINs course or basics course.

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