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What is a SQL Join? (INNER, LEFT, RIGHT, and FULL Join)

  • November 10, 2023
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Meet the Author : Mr. Bharani Kumar

Bharani Kumar Depuru is a well known IT personality from Hyderabad. He is the Founder and Director of Innodatatics Pvt Ltd and 360DigiTMG. Bharani Kumar is an IIT and ISB alumni with more than 17 years of experience, he held prominent positions in the IT elites like HSBC, ITC Infotech, Infosys, and Deloitte. He is a prevalent IT consultant specializing in Industrial Revolution 4.0 implementation, Data Analytics practice setup, Artificial Intelligence, Big Data Analytics, Industrial IoT, Business Intelligence and Business Management. Bharani Kumar is also the chief trainer at 360DigiTMG with more than Ten years of experience and has been making the IT transition journey easy for his students. 360DigiTMG is at the forefront of delivering quality education, thereby bridging the gap between academia and industry.

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What is SQL?

Structured Query Language, also known as SQL, was a programming language that is used to manage and modify relational databases. It is an ideal language for communicating with databases and obtaining data from them. SQL is essential for the processing of structured and ordered data. SQL is a flexible language with several applications in data administration and analysis, which is why it is extensively used in a variety of industries such as banking, healthcare, and e-commerce.

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What is a SQL Join?

A SQL join was a database operation which joins rows from more than one table based on a common column. This action retrieves data from many tables into a single result set, which makes it easier to analyse and deal with your data.

What is Joins?

A "join" is a mechanism used to integrate data from multiple tables in a database depending on a relevant column between them in the context of databases & SQL (Structured Query Language). A join's objective is to retrieve & show data from many tables with a meaningful and logical manner.

Why are Joins Important?

Joins are essential because they enable you to work with normalized data, which is distributed across several tables for various reasons, such as data organization and avoiding data redundancy. Without joins, you would need to manage and query each table separately, making data analysis cumbersome and inefficient.

Now, let's look at the various forms of joins:

Joins in SQL

Inner Join

An inner join retrieves records that have matching values in both tables. In other words, it only returns rows where there is a common value in the specified columns of both tables.

Syntax:

Joins in SQL

Example:

Consider two tables: personnel and departments. You'd like to get a list of personnel and their departments. Here's how you would use an inner join:

SELECT employees.name, departments.department_name FROM employees INNER JOIN departments ON employees.department_id = departments.department_id;

Use Cases:

  • Retrieving related data from multiple tables.
  • Finding common elements between two tables.

Left Join(Left Outer Join)

A left join provides all entries in the left table as well as the records that match from the right table. If no matches are found in the appropriate table, NULL values will be returned.

Syntax:

Joins in SQL

Example:

Let's continue with the previous example. If you want to retrieve all employees and their departments, including employees without assigned departments, you can use a left join:

SELECT employees.name, departments.department_name FROM employees LEFT JOIN departments ON employees.department_id = departments.department_id;

Use Cases:

  • Retrieving all records from one table and matching records from another.
  • Handling situations where not all records have matches.

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Right Join(Right Outer Join)

The opposite to a left join is a right join. It returns all records from the right table as well as the records that match from the left table. If no matches are found on the left table, Null values will be returned.

Syntax:

Joins in SQL

Example:

Continuing with our example, if you want to retrieve all departments and their assigned employees, including departments with no employees, you can use a right join:

SELECT employees.name, departments.department_name FROM employees RIGHT JOIN departments ON employees.department_id = departments.department_id;

Use Cases:

  • Retrieving all records from one table and matching records from another.
  • Handling situations where not all records have matches.

Full Join (Full Outer Join)

A full join returns all records when there is a match in either the left or the right table. It combines the results of both left and right joins, returning NULL values where there is no match.

Syntax:

Joins in SQL

Example:

Suppose you want to retrieve a list of employees and their departments, including employees without departments and departments without employees. You can use a full join like this:

SELECT employees.name, departments.department_name FROM employees FULL JOIN departments ON employees.department_id = departments.department_id;

Use Cases:

  • Retrieving all records from both tables.
  • Handling situations where records may exist in one table but not the other.

Cross Join (Cartesian Join)

This Cartesian product of both tables is returned by a cross join, also referred to as a Cartesian join. This indicates that each row from the left table connects with each row from the right table, yielding a big result set.

Syntax:

Joins in SQL

Example:

Suppose you have a table of products and a table of customers, and you want to generate a list of all possible product-customer combinations. You can use a cross join:

SELECT products.product_name, customers.customer_name FROM products CROSS JOIN customers;

Use Cases:

  • Generating combinations of records from two tables.
  • Use with caution, as it can result in a large number of rows.

Performance Considerations

While joins are useful, they can have an influence on query speed, particularly when dealing with huge datasets. Here are some things to think about while optimising join operations:

Indexing:Ensure that the columns used for joining are indexed. Indexes can significantly speed up the retrieval of matching rows.

Optimizing Joins:

  • Be mindful of the number of rows involved in the join. Cross joins, in particular, can lead to a massive result set.
  • Use appropriate join types based on your specific requirements. Avoid unnecessary full or cross joins if you only need matching records.

Additional Join Types

Apart from the commonly used join types mentioned earlier, some database systems support additional join types like self-joins, anti-joins, semi-joins, and natural joins. These join types cater to specific needs, and understanding when and how to use them can be valuable.

Self-Join: A self-join is a join where a table is joined with itself. This is often used when you want to compare rows within the same table.

Anti-Join: An anti-join returns rows from the first table where there is no match in the second table. It's useful for finding records that don't have a corresponding entry in another table.

Semi-Join: A semi-join returns rows from the first table where there is a match in the second table. It's often used for filtering records based on a condition in another table.

Natural Join: A natural join is one that matches columns having the same name in both tables automatically. While it can help to simplify queries, it is not suggested in practise since it might result in unexpected results if the schema changes.

Joining More Than Two Tables

In many real-world scenarios, you may need to join more than two tables to extract the desired data. To achieve this, you can use a combination of the join types discussed in this blog post. It's essential to pay attention to the order of joins and ensure that the join conditions are correctly specified.

Using Aliases

When working with multiple tables in a query, using table aliases can improve readability. Aliases provide a shorthand notation for table names, making your SQL code more concise and easier to understand.

Query Optimization

Optimizing your SQL queries is crucial for improving performance. This includes using indexes, limiting the result set with appropriate filtering conditions (WHERE clause), and avoiding unnecessary joins or subqueries.

Database Design

An efficient database design is the foundation for optimized query performance. Properly normalized databases reduce the need for complex joins and improve data integrity.

Practice and Learning Resources

To become proficient in SQL joins, practice is essential. Consider using sample databases and running various types of joins on them. Additionally, there are many online tutorials, courses, and SQL query practice platforms that can help you refine your skills.

Cross Apply and Outer Apply (SQL Server):

These are specific to SQL Server and are similar to joins but used with table-valued functions. They apply the function to each row in one table, and the result is joined with the other table.

Natural Join:

A natural join is a type of join where the columns with the same name in both tables are automatically matched without the need for specifying the join condition explicitly. This type of join is less common and can be error-prone, as it relies on column names and their compatibility.

Non-Equi Join:

Most joins are equi-joins, where the join condition involves an equality comparison. In some cases, non-equi joins are required, where the join condition uses operators like less than (<), greater than (>), or not equal (!=) to establish a relationship between the tables.

Self-Referencing Join:

This type of join is used when a table contains a foreign key that relates to itself, creating a hierarchical or recursive relationship. For example, in a table representing an organizational hierarchy, you can use a self-referencing join to retrieve information about an employee and their manager, who is also an employee.

Keep Learning:

SQL is a versatile and ever-evolving language. To master SQL joins and database management, continue learning about new features and best practices in the field. Keep up with the latest advances in relational database technology and SQL standards.

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Conclusion

In conclusion, joins are a basic concept in SQL that allows you to integrate data from several databases in order to obtain significant insights and do extensive data analysis. Understanding the various join types, such as inner, left, right, full, & cross joins, is essential for successful database administration and querying. You may use SQL joins to render your data-related activities more efficient & insightful by selecting the proper join type and optimising your queries. The type of join you employ is determined by your individual use case & the structure on your data. SQL joins give a powerful collection of capabilities for working with your data, whether you need to locate matching records, include mismatched items, or construct combinations.

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