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Supabase Backend as a Service · Lección

Consultas SQL y joins avanzados

Domine consultas SQL complejas, incluidos distintos tipos de joins, subconsultas y funciones de ventana, para recuperar conjuntos de datos sofisticados.

Consultas SQL y joins avanzados es una lección gratuita de Supabase Backend as a Service en CoddyKit. Esta es la lección 1 de 3. Puedes leer la lección completa abajo gratuitamente — luego la practicas en el navegador con un editor de código integrado y un tutor de IA 24/7. Forma parte de la ruta de aprendizaje de Supabase Backend as a Service, y tu progreso se sincroniza en la web y la app de CoddyKit. El curso de Supabase Backend as a Service incluye 3 lecciones en total.

Partes de esta lección aún no han sido traducidas y se muestran en inglés.

Beyond Basic Queries

Welcome to Advanced SQL Queries! So far, you've learned to select, filter, and sort data. But real-world applications often need to combine data from multiple sources or perform complex calculations.

This lesson will equip you with powerful techniques to retrieve sophisticated datasets, making your Supabase applications even smarter.

Joins Recap: Inner Join

Let's quickly refresh our memory on joins. A JOIN combines rows from two or more tables based on a related column between them.

An INNER JOIN returns only the rows where there is a match in both tables. If a row in one table doesn't have a match in the other, it's excluded.

Try running this example to set up our tables and see an INNER JOIN:

CREATE TABLE departments (
  department_id INT PRIMARY KEY,
  department_name VARCHAR(50) NOT NULL
);

CREATE TABLE employees (
  employee_id INT PRIMARY KEY,
  first_name VARCHAR(50) NOT NULL,
  last_name VARCHAR(50) NOT NULL,
  department_id INT REFERENCES departments(department_id)
);

INSERT INTO departments (department_id, department_name) VALUES
(1, 'Sales'),
(2, 'Marketing'),
(3, 'Engineering'),
(4, 'HR');

INSERT INTO employees (employee_id, first_name, last_name, department_id) VALUES
(101, 'Alice', 'Smith', 1),
(102, 'Bob', 'Johnson', 2),
(103, 'Charlie', 'Brown', 1),
(104, 'Diana', 'Prince', 3),
(105, 'Eve', 'Adams', NULL);

SELECT
  e.first_name,
  e.last_name,
  d.department_name
FROM
  employees e
INNER JOIN
  departments d ON e.department_id = d.department_id;

Left Join: All from the Left

What if you want to see all employees, even those not assigned to a department yet? That's where LEFT JOIN (or LEFT OUTER JOIN) comes in handy.

A LEFT JOIN returns all rows from the 'left' table (the first one mentioned) and the matching rows from the 'right' table. If there's no match on the right, NULL values are returned for the right table's columns.

Run this to see employee Eve Adams, who has no department:

SELECT
  e.first_name,
  e.last_name,
  d.department_name
FROM
  employees e
LEFT JOIN
  departments d ON e.department_id = d.department_id;

Right Join: All from the Right

The opposite of a LEFT JOIN is a RIGHT JOIN (or RIGHT OUTER JOIN). It returns all rows from the 'right' table and matching rows from the 'left' table.

If there's no match on the left, NULL values are returned for the left table's columns. This is less common, as you can often rewrite it as a LEFT JOIN by swapping table order.

Let's find all departments, including 'HR' which currently has no employees:

SELECT
  e.first_name,
  e.last_name,
  d.department_name
FROM
  employees e
RIGHT JOIN
  departments d ON e.department_id = d.department_id;

Full Outer Join: Everything!

Want to see everything? A FULL OUTER JOIN (or just FULL JOIN) returns all rows when there is a match in either the left or the right table.

If a row doesn't have a match in the other table, the columns from the non-matching side will have NULL values. It's like combining a LEFT and a RIGHT join.

Observe how both Eve (no department) and HR (no employees) appear:

SELECT
  e.first_name,
  e.last_name,
  d.department_name
FROM
  employees e
FULL OUTER JOIN
  departments d ON e.department_id = d.department_id;

Self Join: Table to Itself

Sometimes, you need to join a table to itself. This is called a SELF JOIN and is useful for finding relationships within the same table, like 'employees and their managers'.

To do this, you use table aliases to treat the same table as two separate entities in your query.

Let's add a manager column and find out who manages whom:

ALTER TABLE employees
ADD COLUMN manager_id INT REFERENCES employees(employee_id);

UPDATE employees SET manager_id = 101 WHERE employee_id = 102;
UPDATE employees SET manager_id = 101 WHERE employee_id = 103;
UPDATE employees SET manager_id = 104 WHERE employee_id = 105;

SELECT
  E.first_name AS employee_name,
  M.first_name AS manager_name
FROM
  employees E
INNER JOIN
  employees M ON E.manager_id = M.employee_id;

Introducing Subqueries

Beyond joins, subqueries (also called inner queries or nested queries) are another powerful tool. A subquery is simply a SQL query nested inside a larger query.

They can be used to:

  • Filter data in a WHERE clause.
  • Define columns in a SELECT clause.
  • Create derived tables in a FROM clause.

Subqueries execute first, and their result is then used by the outer query.

Subqueries in WHERE Clause

A common use for subqueries is in the WHERE clause to filter results dynamically. You can use operators like IN, EXISTS, =, <, > with subqueries.

For example, let's find all employees who work in the 'Sales' department without knowing the department_id beforehand:

SELECT
  first_name, last_name
FROM
  employees
WHERE
  department_id IN (
    SELECT department_id
    FROM departments
    WHERE department_name = 'Sales'
  );

Scalar Subqueries in SELECT

A scalar subquery is a subquery that returns a single value (one row, one column). These are often used in the SELECT clause to add a calculated value to each row of the main query.

Let's find each employee's name and also show the total number of employees in their department. This demonstrates how a subquery can compute a value for each row.

SELECT
  e.first_name,
  e.last_name,
  d.department_name,
  (SELECT COUNT(*)
   FROM employees
   WHERE department_id = e.department_id) AS dept_employee_count
FROM
  employees e
LEFT JOIN
  departments d ON e.department_id = d.department_id;

Advanced Queries Challenge

Consider a scenario where you want to list all departments, and for each department, show the names of employees working there. If a department has no employees, it should still appear in the list with NULL for employee names.

Which SQL JOIN type is most appropriate for this task?

Recap: Your SQL Superpowers

You've gained some serious SQL superpowers today!

  • Joins: Beyond INNER JOIN, you learned about LEFT, RIGHT, and FULL OUTER JOINs to handle different data inclusion needs.
  • Self Join: How to join a table to itself for hierarchical data.
  • Subqueries: Nesting queries to filter data (WHERE clause) or compute scalar values (SELECT clause).

These techniques are fundamental for building powerful and flexible data retrieval logic in your Supabase projects. Keep practicing!

Preguntas frecuentes

¿La lección «Consultas SQL y joins avanzados» es gratis?

Sí — el texto completo de «Consultas SQL y joins avanzados» es gratis para leer aquí en la web. Para practicarla de forma interactiva (editor de código integrado y tutor de IA 24/7) y desbloquear el resto del curso de Supabase Backend as a Service, actualiza a CoddyKit PRO. El curso de Supabase Backend as a Service incluye 3 lecciones en total.

¿Qué aprenderé en «Consultas SQL y joins avanzados»?

Domine consultas SQL complejas, incluidos distintos tipos de joins, subconsultas y funciones de ventana, para recuperar conjuntos de datos sofisticados. Practicas Supabase Backend as a Service con código real que ejecutas directamente en el navegador, y un tutor de IA 24/7 responde tus preguntas mientras trabajas en la lección.

¿Necesito experiencia previa para empezar Supabase Backend as a Service?

No se requiere experiencia previa. Supabase Backend as a Service en CoddyKit está estructurado para principiantes hasta estudiantes avanzados, así que puedes empezar aquí o desde el inicio y avanzar a tu ritmo. Esta es la lección 1 de 3.

¿Cuánto tiempo toma la lección «Consultas SQL y joins avanzados»?

La mayoría de las lecciones de CoddyKit toman alrededor de 5–10 minutos. Cada una es compacta e interactiva, así que avanzas constantemente y retomas exactamente por donde dejaste en la web y la app.

¿Puedo escribir y ejecutar código en esta lección de Supabase Backend as a Service?

Sí. Cada lección de Supabase Backend as a Service incluye un editor de código integrado, así que escribes y ejecutas código real directamente en tu navegador y obtienes retroalimentación instantánea de IA — sin configuración local necesaria.

Todas las lecciones de este curso

  1. Consultas SQL y joins avanzados
  2. Indexación de bases de datos para mejorar el rendimiento
  3. Funciones y triggers de la base de datos
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