Practical Tutorial about the PostgreSQL Database

POSTGRESQL TUTORIAL
PostgreSQL is an advanced relational database system.
PostgreSQL supports both relational (SQL) and non-relational (JSON)
queries.
PostgreSQL is free and open-source.
PostgreSQL, also known as Postgres, is a free and open-source
relational database management system emphasizing extensibility
and SQL compliance. PostgreSQL supports both relational (SQL) and
non-relational (JSON) queries.
PostgreSQL supports the most important programming languages:
• Python
• Java
• C/C++
• C#
• Node.js
• Go
• Ruby
• Perl
• Tcl
PostgreSQL supports basically all features that other database
management systems support.
PostgreSQL History
PostgreSQL was invented at the Berkeley Computer
Science Department, University of California.
It started as a project in 1986 with the goal of
creating a database system with the minimal features
needed to support multiple data types.
In the beginning, PostgreSQL ran on UNIX platforms,
but now it can run on various platforms, including
Windows and MacOS.
Connect to the Database
If you have followed the steps from the Install
PostgreSQL page, you now have a PostgreSQL database
on you computer.
There are several ways to connect to the database, we
will look at two ways in this tutorial:
• SQL Shell (psql)
• pgAdmin 4
Both of them comes with the installation of PostgreSQL

Note: Always end SQL statements with a
semicolon ;
Once you are connected through pgAdmin4, you
are ready to write SQL statements!
The ALTER TABLE Statement
To add a column to an existing table, we have to use the ALTER TABLE statement.
To change the data type, or the size of a table column we have to use the ALTER TABLE
statement.
The ALTER TABLE statement is used to add, delete, or modify columns in an existing table.
The ALTER TABLE statement is also used to add and drop various constraints on an
existing table.
ALTER COLUMN
We want to change the data type of the year
column of the cars table from INT to
VARCHAR(4).
To modify a column, use the ALTER COLUMN
statement and the TYPE keyword followed by
the new data type:
Example
Change the year column from INT to
VARCHAR(4):
ALTER TABLE cars
ALTER COLUMN year TYPE VARCHAR(4);
Note: Some data types cannot be converted if the column
has value. E.g. numbers can always be converted to text,
but text cannot always be converted to numbers.
DROP COLUMN
We want to remove the column named color from the
cars table.
To remove a column, use the DROP COLUMN statement:
Example
Remove the color column:
ALTER TABLE cars DROP COLUMN color;

The DELETE Statement
The DELETE statement is used to delete existing records in a table.
Note: Be careful when deleting records in a table! Notice the WHERE
clause in the DELETE statement.
The WHERE clause specifies which record(s) should be deleted.
If you omit the WHERE clause, all records in the table will be deleted!.
The TRUNCATE TABLE Statement
The TRUNCATE TABLE statement is used to delete ALL records in a
table.
The DROP TABLE Statement
The DROP TABLE statement is used to drop an existing table in a
database.
Note: Be careful before dropping a table. Deleting a table will result in
loss of all information stored in the table!

= Equal to
< Less than
> Greater than
<= Less than or equal to
>= Greater than or equal to
<> Not equal to
!= Not equal to
LIKE Check if a value matches a pattern (case sensitive)
ILIKE Check if a value matches a pattern (case insensitive)
AND Logical AND
OR Logical OR
IN Check if a value is between a range of values
BETWEE
N
Check if a value is between a range of values
IS NULL Check if a value is NULL
NOT
Makes a negative result e.g. NOT LIKE, NOT IN, NOT
BETWEEN
Operators in the WHERE clause
We can operate with different operators in the WHERE clause:
LIKE
The LIKE operator is used when you want to return all records where a
column is equal to a specified pattern.
The pattern can be an absolute value like 'Volvo', or with a wildcard that
has a special meaning.
There are two wildcards often used in conjunction with the LIKE operator:
• The percent sign % , represents zero, one, or multiple characters.
• The underscore sign _ , represents one single character.
ILIKE
Same as the LIKE operator, but ILIKE is case insensitive.
IN
The IN operator is used when a column's value matches any of the values in a list:
Example
Return all records where the brand is present in this list: ('Volvo', 'Mercedes', 'Ford'):
SELECT * FROM cars
WHERE brand IN ('Volvo', 'Mercedes', 'Ford’);
NOT
The NOT operator can be used together with LIKE, ILIKE, IN, BETWEEN, and NULL
operators to reverse the truth of the operator.
Example: NOT LIKE : Return all records where the brand does NOT start with a
capital 'B' (case sensitive):
SELECT * FROM cars WHERE brand NOT LIKE 'B%';

THE OFFSET CLAUSE
The OFFSET clause is used to specify where to
start selecting the records to return.
If you want to return 20 records, but start at
number 40, you can use both LIMIT and OFFSET.
Note: The first record is number 0, so when you
specify OFFSET 40 it means starting at record
number 41.
Example
Return 20 records, starting from the 41th record:
SELECT * FROM customers LIMIT 20 OFFSET 40;
IN (SELECT)
You can also us a SELECT statement inside the parenthesis
to return all records that are in the result of the SELECT
statement.
Example: Return all customers that have an order in the
orders table:
SELECT * FROM customers
WHERE customer_id IN (SELECT customer_id FROM orders);
NOT IN (SELECT)
The result in the example above returned 89 records, that
means that there are 2 customers that haven't placed any
orders.
Let us check if that is correct, by using the NOT IN operator.
Example
Return all customers that have NOT placed any orders in
the orders table:
SELECT * FROM customers
WHERE customer_id NOT IN (SELECT customer_id FROM
orders);

BETWEEN
The BETWEEN operator selects values within a given range. The
values can be numbers, text, or dates.
The BETWEEN operator is inclusive: begin and end values are
included.
Example
Select all products with a price between 10 and 15:
SELECT * FROM Products
WHERE Price BETWEEN 10 AND 15;
BETWEEN Text Values
The BETWEEN operator can also be used on text values.
The result returns all records that are alphabetically between the
specified values.
SELECT * FROM Products
WHERE product_name BETWEEN 'Pavlova' AND 'Tofu'
ORDER BY product_name;
BETWEEN Date Values
The BETWEEN operator can also be used on date values.
Example : Select all orders between 12. of April 2023 and 5. of
May 2023:
SELECT * FROM orders
Concatenate Columns
The AS keyword is often used when two or more fields are
concatenated into one.
To concatenate two fields use ||.
Example
Concatenate two fields and call them product:
SELECT product_name || unit AS product FROM products;
Note: In the result of the example above we are missing a
space between product_name and unit. To add a space
when concatenating, use || ' ' ||.
Using Aliases With a Space Character
If you want your alias to contain one or more spaces, like
"My Great Products", surround your alias with double
quotes.
Example
Surround your alias with double quotes:
SELECT product_name AS “My Great Products” FROM
products;

JOIN OPERATIONS IN POSTGRESQL
In PostgreSQL, the JOIN clause is used to combine rows from two or
more tables based on a related column or condition. It specifies how
the tables should be joined and on which columns the join should be
performed.
There are several types of joins available in PostgreSQL:
1: INNER JOIN
2: LEFT JOIN
3: RIGHT JOIN
4: FULL JOIN
5: CROSS JOIN / CARTESIAN JOIN
6: NATURAL JOIN
7: SELF JOIN
Note: JOIN and INNER JOIN will give the same result.
INNER is the default join type for JOIN, so when you write JOIN the
parser actually writes INNER JOIN.
Note: LEFT JOIN and LEFT OUTER JOIN will give the same result.
OUTER is the default join type for LEFT JOIN, so when you write LEFT
JOIN the parser actually writes LEFT OUTER JOIN.
Note: RIGHT JOIN and RIGHT OUTER JOIN will give the same result.
OUTER is the default join type for RIGHT JOIN, so when you write
RIGHT JOIN the parser actually writes RIGHT OUTER JOIN.
Note: FULL JOIN and FULL OUTER JOIN will give the same result.
OUTER is the default join type for FULL JOIN, so when you write FULL
JOIN the parser actually writes FULL OUTER JOIN.

CROSS JOIN
The CROSS JOIN keyword matches ALL records from the "left" table
with EACH record from the "right" table.
That means that all records from the "right" table will be returned for
each record in the "left" table.
This way of joining can potentially return very large table, and you
should not use it if you do not have to.
UNION
The UNION operator is used to combine the result-set of two or more
queries.
The queries in the union must follow these rules:
1. They must have the same number of columns
2. The columns must have the same data types
3. The columns must be in the same order
UNION vs UNION ALL
With the UNION operator, if some rows in the two queries returns the
exact same result, only one row will be listed, because UNION selects
only distinct values.
Use UNION ALL to return duplicate values.
GROUP BY
The GROUP BY clause groups rows that have the
same values into summary rows, like "find the
number of customers in each country".
The GROUP BY clause is often used with aggregate
functions like COUNT(), MAX(), MIN(), SUM(), AVG()
to group the result-set by one or more columns.
HAVING
The HAVING clause was added to SQL because the
WHERE clause cannot be used with aggregate
functions.
Aggregate functions are often used with GROUP BY
clauses, and by adding HAVING we can write condition
like we do with WHERE clauses.
SELECT customers.customer_name, SUM(products.price)
FROM order_details
LEFT JOIN products ON order_details.product_id =
products.product_id
LEFT JOIN orders ON order_details.order_id = orders.order_id
LEFT JOIN customers ON orders.customer_id =
customers.customer_id
GROUP BY customer_name
HAVING SUM(products.price) > 1000.00;
Lists customers that have ordered for 1000$ or
more:

EXISTS
The EXISTS operator is used to test for the existence of any record in a sub
query.
The EXISTS operator returns TRUE if the sub query returns one or more
records.
Example
Return all customers that is represented in the orders table:
SELECT customers.customer_name
FROM customers
WHERE EXISTS (
SELECT order_id FROM orders WHERE customer_id =
);
The result in example above showed that 89 customers had at least one
order in the orders table.
NOT EXISTS
To check which customers that do not have any orders, we can use the
NOT operator together with the EXISTS operator :
Example
Return all customers that is NOT represented in the orders table:
SELECT customers.customer_name
FROM customers
WHERE NOT EXISTS (
SELECT order_id FROM orders WHERE customer_id =

ANY
The ANY operator allows you to perform a
comparison between a single column value and
a range of other values.
The ANY operator:
Returns a Boolean value as a result returns
TRUE if ANY of the sub query values meet the
condition
ANY means that the condition will be true if the
operation is true for any of the values in the
range.
Example
List products that have ANY records in the
order_details table with a quantity larger than
120:
SELECT product_name
FROM products
WHERE product_id = ANY (
SELECT product_id
FROM order_details
WHERE quantity > 120
);
ALL
The ALL operator:
• returns a Boolean value as a result
• returns TRUE if ALL of the sub query values meet the condition
• is used with SELECT, WHERE and HAVING statements
ALL means that the condition will be true only if the operation is true
for all values in the range.
Example
List the products if ALL the records in the order_details with quantity
larger than 10.
Note: This will of course return FALSE because the quantity column has
many different values (not only the value of 10):
SELECT product_name
FROM products
WHERE product_id = ALL (
SELECT product_id
FROM order_details
WHERE quantity > 10
);

CASE
The CASE expression goes through conditions and returns a value
when the first condition is met (like an if-then-else statement).
Once a condition is true, it will stop reading and return the result. If no
conditions are true, it returns the value in the ELSE clause.
If there is no ELSE part and no conditions are true, it returns NULL.
Example
Return specific values if the price meets a specific condition:
SELECT product_name,
CASE
WHEN price < 10 THEN 'Low price product'
WHEN price > 50 THEN 'High price product'
ELSE
'Normal product'
END
FROM products;

Las 10 mejores herramientas para monitorear bases de datos PostgreSQL
1. pgAdmin
•Descripción: Herramienta oficial para administración de PostgreSQL.
•Características: Visualización de estadísticas, monitoreo básico y
consultas en tiempo real.
2. pg_stat_statements
•Descripción: Extensión nativa para analizar y optimizar consultas
SQL.
•Características: Métricas de rendimiento por consulta, identificación
de consultas lentas.
3. Prometheus + Grafana
•Descripción: Herramientas de monitoreo y visualización en tiempo
real.
•Características: Dashboards personalizados y alertas; usa
postgres_exporter para métricas de PostgreSQL.
4. pganalyze
•Descripción: Plataforma avanzada de análisis y monitoreo.
•Características: Optimización de consultas, métricas avanzadas,
recomendaciones automatizadas.
5. Zabbix
•Descripción: Herramienta de monitoreo general con soporte para
PostgreSQL.
•Características: Monitoreo de conexiones, bloqueos, rendimiento y
alertas personalizables.
6. Datadog
•Descripción: Plataforma de monitoreo en la nube que incluye
soporte para PostgreSQL.
•Características: Visualización avanzada, integración con múltiples
servicios y alertas automatizadas.
7. Nagios
•Descripción: Sistema de monitoreo de infraestructura con módulos
para bases de datos.
•Características: Monitoreo de rendimiento, conexiones,
disponibilidad y alertas.
8. Percona Monitoring and Management (PMM)
•Descripción: Herramienta enfocada en bases de datos, incluyendo
PostgreSQL.
•Características: Análisis de consultas, métricas de rendimiento y
optimización.
9. New Relic
•Descripción: Plataforma de monitoreo para aplicaciones y bases de
datos.
•Características: Análisis de rendimiento en tiempo real, optimización
y visualización de datos históricos.
10. pgCluu
•Descripción: Herramienta de monitoreo y auditoría específica para
PostgreSQL.
•Características: Informes detallados sobre uso de recursos,
consultas y rendimiento.

Practical Tutorial about the PostgreSQL Database

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