PostgreSQL SQL Functions
A database function packages a value-producing operation under a defined signature. Volatility and privilege choices should describe its actual behavior.
How it works
The lab defines a pure helper that checks whether a proposed volume fits a capacity. It has no table access and handles NULL inputs through a stated expression. IMMUTABLE is appropriate for this particular calculation because the result depends only on its arguments, not on changing database state.
Run in a separate PostgreSQL lab
Use PostgreSQL 18; the reviewed server and client tools are 18.6. PostgreSQL is separate from XAMPP MySQL/MariaDB and Bhylu’s SQLite playground. No PostgreSQL browser runner is available. These lessons do not change PHP, Apache or your normal database services.
- On your own private learning instance, have its administrator create an empty bhylu_pg_lab database. This administrative step runs outside a transaction. Stop if the database already exists; do not replace it.
- Connect explicitly to that database with its lab host, port and role. Save this download as functions.sql. With the matching client run
psql -X -h 127.0.0.1 -p YOUR_LAB_PORT -U YOUR_LAB_ROLE -d bhylu_pg_lab -v ON_ERROR_STOP=1 -f functions.sql. Replace the two uppercase placeholders; never paste a password into the lesson or a committed command. - The complete SQL checks the database name, creates a fresh bhylu_lesson schema, sets UTC, ISO dates and bounded timeouts, and seeds all four tables. It refuses an existing schema instead of overwriting it. It then runs the lesson and rolls everything back. In pgAdmin, run the complete SQL through Query Tool; if a statement fails, issue ROLLBACK before retrying.
Download the complete functions.sql script. Each script is independent; do not import one lesson’s seed into another lesson’s transaction. Cost values are exact numeric fixtures; measurement totals are not claims about real water usage.
Example
-- Bhylu PostgreSQL 18.6 lab: SQL Functions
-- Use only your separate disposable database named bhylu_pg_lab.
-- Each example creates a fresh schema inside a transaction, then rolls back.
BEGIN ISOLATION LEVEL READ COMMITTED;
DO $$ BEGIN
IF current_database() <> 'bhylu_pg_lab' THEN
RAISE EXCEPTION 'Choose the disposable bhylu_pg_lab database';
END IF;
END $$;
CREATE SCHEMA bhylu_lesson;
SET LOCAL search_path = bhylu_lesson, pg_catalog;
SET LOCAL timezone = 'UTC';
SET LOCAL datestyle = 'ISO, YMD';
SET LOCAL statement_timeout = '10s';
SET LOCAL lock_timeout = '2s';
CREATE TABLE tanks (
id integer PRIMARY KEY,
label text NOT NULL UNIQUE,
capacity_l integer NOT NULL CHECK (capacity_l > 0),
zone text
);
CREATE TABLE readings (
id integer PRIMARY KEY,
tank_id integer NOT NULL REFERENCES tanks(id),
measured_at timestamptz NOT NULL,
litres integer NOT NULL CHECK (litres >= 0)
);
CREATE TABLE technicians (id integer PRIMARY KEY, name text NOT NULL);
CREATE TABLE inspections (
id integer PRIMARY KEY,
tank_id integer NOT NULL REFERENCES tanks(id),
technician_id integer REFERENCES technicians(id),
status text NOT NULL CHECK (status IN ('planned','pending','done')),
cost numeric(8,2) CHECK (cost >= 0)
);
INSERT INTO tanks VALUES
(1,'North roof',1000,'North'),
(2,'Library',600,'Central'),
(3,'Workshop',800,'North'),
(4,'Garden',400,NULL);
INSERT INTO readings VALUES
(1,1,'2026-01-10 06:00:00+00',300),
(2,1,'2026-01-11 06:00:00+00',450),
(3,2,'2026-01-10 06:00:00+00',200),
(4,3,'2026-01-10 06:00:00+00',0),
(5,2,'2026-01-11 06:00:00+00',350);
INSERT INTO technicians VALUES (1,'Mira'),(2,'Dev'),(3,'Noor');
INSERT INTO inspections VALUES
(11,1,1,'done',12.50),
(12,2,2,'pending',NULL),
(13,3,1,'done',20.00),
(14,1,NULL,'planned',0.00);
-- Lesson commands begin here.
CREATE FUNCTION fits_capacity(volume integer, capacity integer)
RETURNS boolean LANGUAGE sql IMMUTABLE
AS $$ SELECT volume IS NOT NULL AND capacity IS NOT NULL
AND volume >= 0 AND volume <= capacity $$;
SELECT fits_capacity(250,600),fits_capacity(700,600),fits_capacity(NULL,600);
-- No changes from this lesson are kept.
ROLLBACK;
Focus on the lesson query
This excerpt omits the guarded transaction, schema and dataset. Use the complete download to run it.
CREATE FUNCTION fits_capacity(volume integer, capacity integer)
RETURNS boolean LANGUAGE sql IMMUTABLE
AS $$ SELECT volume IS NOT NULL AND capacity IS NOT NULL
AND volume >= 0 AND volume <= capacity $$;
SELECT fits_capacity(250,600),fits_capacity(700,600),fits_capacity(NULL,600);
Expected result
t|f|f
Expected rows use a pipe between columns and <NULL> for a missing value. A normal client may display headings, spacing and NULL differently. Use the script’s explicit ORDER BY when comparing results.
The function accepts a valid volume and refuses overflow and missing input under its explicit policy. A stored function does not make an entire workflow atomic unless the caller uses an appropriate transaction. Use ordinary invoker privileges unless a reviewed design truly requires something stronger.