What are projection and selection in SQL?

sql

best-practices

relational-algebra

database-performance

byAlex Kataev·Nov 26, 2024

Projection in SQL refers to choosing the columns:

SELECT column_name FROM table_name;

In contrast, selection refers to specifying rows based on certain conditions:

SELECT * FROM table_name WHERE condition;

These two operations are essential building blocks for shaping query results in a SQL database.

Delving into selection and projection

The purpose of projection

In the context of SQL, projection is a process whereby columns from your table are specifically chosen to be included in your results. In other words, projection dictates what columns your result set will have. The following code block demonstrates what a projection in SQL might look like:

SELECT employee_id, employee_name FROM employees; // "Whoops! Just ID and names here!"

Selection: A brief explanation

Selection in SQL refers to the act of filtering out rows that satisfy a certain condition. This is where you specify what rows you want to include in your result set. Selection is done using the WHERE clause.

SELECT * FROM employee WHERE department = 'Marketing'; // So you're looking for Marketeers, huh?

Making SQL work efficiently

By mastering the use of projection and selection, you can not only make your SQL queries accurate but significantly more efficient. How so? Well, the tighter you make your selection, the fewer rows you fetch. Similarly, the narrower you make your projection, the fewer columns you fetch. It's like playing 'Hide and Seek' with your database; the better you are, the faster you find what you're looking for!

The backbone of relational algebra

At its core, the projection and selection operations are fundamentally a part of a broader concept known as relational algebra. This forms the theoretical foundation of relational databases, giving us a structured way to manage and manipulate our data.

Harnessing the power of projection and selection

Projection and selection are like Batman and Robin, always better together. By leveraging the characteristics of both, you can perform surgical strikes on your database to extract exactly what you need.

Practical examples

Let's say you want to extract employee_id and employee_name for all employees in the 'Sales' department. Here is how you can do it:

SELECT employee_id, employee_name FROM employees WHERE department = 'Sales'; //Sorry interns, sales only!

Here, the projection is on the employee_id and employee_name columns. The selection, on the other hand, applies the condition department = 'Sales'.

Caveats and tips to remember

While working with selection and projection, keep the following in mind:

Avoid selecting more columns than necessary 🏋️‍♀️. This is like carrying unnecessary baggage — it slows you down.
Precision is key to selection. A faulty WHERE clause can lead to data leakage or incorrect results. It's like a super-exclusive party — only invite the guests you want.
For large datasets, indexing columns in the WHERE clause can significantly improve selection speed. It's like "Google Maps" for your database.