SQL, or Structured Query Language,is a language to talk to databases. It allows you to select specific data and to build complex reports. Today, SQL is a universal language of data. It is used in practically all technologies that process data.
id | name | population | area |
---|---|---|---|
1 | France | 66600000 | 640680 |
2 | Germany | 80700000 | 357000 |
id | name | country_id | population | rating |
---|---|---|---|---|
1 | Paris | 1 | 2243000 | 5 |
2 | Berlin | 2 | 3460000 | 3 |
Fetch all columns from the country table:
SELECT *
FROM country;
Fetch id and name columns from the city table:
SELECT id, name
FROM city;
Fetch city names sorted by the rating column in the default ASCending order:
SELECT name
FROM city
ORDER BY rating [ASC];
Fetch city names sorted by the rating column in the DESCending order:
SELECT name
FROM city
ORDER BY rating DESC;
SELECT name AS city_name
FROM city;
SELECT co.name, ci.name
FROM city As ci
JOIN countrv AS co
ON ci.country_id = co.id;
Fetch names of cities that have a rating above 3:
SELECT name
FROM city
WHERE rating > 3;
Fetch names of cities that are neither Berlin nor Madrid:
SELECT name
FROM city
WHERE name != 'Berlin'
AND name != 'Madrid';
Fetch names of cities that start with a 'P' or end with an 's':
SELECT name
FROM city
WHERE name LIKE 'P%'
OR name LIKE "%s';
Fetch names of cities that start with any letter followed by 'ublin' (like Dublin in Ireland or Lublin in Poland):
SELECT name
FROM city
WHERE name LIKE '_ublin';
Fetch names of cities that have a population between 500K and 5M:
SELECT name
FROM citv
WHERE population BETWEEN 500000 AND 5000000;
Fetch names of cities that don't miss a rating value:
SELECT name
FROM citv
WHERE rating IS NOT NULL;
Fetch names of cities that are in countries with IDs 1, 4, 7, or 8:
SELECT name
FROM city
WHERE country_id IN (1, 4, 7, 8);
JOIN (or explicitly INNER JOIN) returns rows that have matching values in both tables.
SELECT city.name, country.name
FROM city
[INNER] JOIN country;
CITY | COUNTRY | |||
---|---|---|---|---|
id | name | country_id | id | name |
1 | Paris | 1 | 1 | France |
2 | Berlin | 2 | 2 | Germany |
3 | Warsaw | 4 | NULL | NULL |
LEFT JOIN returns all rows from the left table with corresponding rows from the right table. If there's no matching row, NULLs are returned as values from the second table.
SELECT city.name, country.name
FROM city
LEFT JOIN country
ON city.country_id = country.id;
CITY | COUNTRY | |||
---|---|---|---|---|
id | name | country_id | id | name |
1 | Paris | 1 | 1 | France |
2 | Berlin | 2 | 2 | Germany |
3 | Warsaw | 4 | NULL | NULL |
RIGHT JOIN returns all rows from the right table with corresponding rows from the left table. If there's no matching row, NULLs are returned as values from the left table.
SELECT city.name, country.name
FROM citv
RIGHT JOIN country
ON city.country_id = country.id;
CITY | COUNTRY | |||
---|---|---|---|---|
id | name | country_id | id | name |
1 | Paris | 1 | 1 | France |
2 | Berlin | 2 | 2 | Germany |
NULL | NULL | NULL | 3 | Iceland |
FULL JOIN (or explicitly FULL OUTER JOIN) returns all rows from both tables - if there's no matching row in the second table Nulls are returned.
SELECT city.name, country.name
FROM city
FULL [OUTER] JOIN country
ON city.country_id = country.id;
CITY | COUNTRY | |||
---|---|---|---|---|
id | name | country_id | id | name |
1 | Paris | 1 | 1 | France |
2 | Berlin | 2 | 2 | Germany |
3 | Warsaw | 4 | NULL | NULL |
NULL | NULL | NULL | 3 | Iceland |
CROSS JOIN returns all possible combinations of rows from both tables. There are two syntaxes avallable.
SELECT city.name, country.name
FROM city
CROSS JOIN country;
SELECT city.name, country.name
FROM city, country;
CITY | COUNTRY | |||
---|---|---|---|---|
id | name | country_id | id | name |
1 | Paris | 1 | 1 | France |
1 | Paris | 1 | 2 | Germany |
2 | Berlin | 2 | 1 | France |
2 | Berlin | 2 | 2 | Germany |
NATURAL JOIN will join tables by all columns with the same name.
SELECT city.name, country.name
FROM city
NATURAL JOIN country;
CITY | COUNTRY | |||
---|---|---|---|---|
country_id | id | name | name | id |
6 | 6 | San Marino | San Marino | 6 |
7 | 7 | Vatican City | Vatican City | 7 |
5 | 9 | Greece | Greece | 9 |
10 | 11 | Monaco | Monaco | 10 |
NATURAL JOIN used these columns to match rows city.id, city.name, country.id, country.name. NATURAL JOIN is very rarely used in practice.
GROUP BY groups together rows that have the same values in specified columns. It computes summaries (aggregates) for each unique combination of values.
Find out the number of cities:
SELECT COUNT(*)
FROM city;
Find out the number of cities with non-null ratings:
SELECT COUNT(rating)
FROM city;
Find out the number of distinctive country values:
SELECT COUNT(DISTINCT country_id)
FROM city;
Find out the smallest and the greatest country populations:
SELECT MIN(population), MAX(population)
FROM country;
Find out the total population of cities in respective countries:
SELECT country_id, SUM(population)
FROM city
GROUP BY country_id;
Find out the average rating for cities in respective countries if the average is above 3.0:
SELECT country_id, AVG(rating)
FROM city
GROUP BY country_id
HAVING AVG(rating) > 3.0;
A subquery is a query that is nested inside another query, or inside another subquery. There are different types of subqueries.
The simplest subquery returns exactly one column and exactly one row. It can be used with comparison operators =, <, <=, >, or >=.
This query finds cities with the same rating as Paris:
SELECT name FROM city
WHERE rating = (
SELECT rating
FROM city
WHERE name = 'paris
);
A subquery can also return multiple columns or multiple rows. Such subqueries can be used with operators IN, EXISTS, ALL, or ANY.
This query finds cities in countries that have a population above 20M:
SELECT name FROM city
WHERE country_id IN (
SELECT country_id
FROM country
WHERE population > 20000000
);
A correlated subquery refers to the tables introduced in the outer query. A correlated subquery depends on the outer query. It cannot be run independently from the outer query.
This query finds cities with a population greater than the average population in the country:
SELECT *
FROM city main_city
WHERE population > (
SELECT AVG(population)
FROM city average_city
WHERE average_city.country_id = main_city.country_id
);
This query finds countries that have at least one city:
SELECT name
FROM country
WHERE EXISTS (
SELECT *
FROM city
WHERE country _id = country.id
);
Set operations are used to combine the results of two or more queries into a single result. The combined queries must return the same number of columns and compatible data types. The names of the corresponding columns can be different.
CYCLING | SKATING | ||||
---|---|---|---|---|---|
id | name | country | id | name | country |
1 | YK | DE | 1 | YK | DE |
2 | ZG | DE | 2 | DF | DE |
3 | WT | PL | 3 | AK | PL |
UNION combines the results of two result sets and remove duplicates. UNION ALL doesn't remove duplicate rows.
This query displays German cyclists together with German skaters:
SELECT name FROM cycling WHERE country = 'DE'
UNION / UNION ALL
SELECT name FROM skating WHERE country = 'DE';
INTERSECT returns only rows that appear in both result sets.
This query displays German cyclists who are also German skaters at the same time:
SELECT name FROM cycling WHERE country = 'DE'
INTERSECT
SELECT name FROM skating WHERE country = 'DE';
EXCEPT returns only the rows that appear in the first resulk set but do not appear
This query displays German cyclists unless they are also German skaters at the same time:
SELECT name FROM cycling WHERE country = 'DE'
EXCEPT / MINUS
SELECT name FROM skating WHERE country = 'DE';