SQL Cheat Sheet

SQL (Structured Query Language) in one page (credit/original) nb not (originally) SQLite-specific.

Table of contents: Database Manipulation (CREATE, DROP DATABASE), Table Manipulation (CREATE, ALTER, DROP TABLE, Data Types), Index Manipulation (CREATE, DROP INDEX), Data Manipulation (INSERT, UPDATE, DELETE, TRUNCATE TABLE), Select (SELECT, FROM, WHERE, ORDER BY, GROUP BY, HAVING, Operators, Aggregate functions), Alias, JOIN, UNION, SELECT INTO/IN, CREATE VIEW.

Database Manipulation

CREATE DATABASE database_name

Create a database [nb: not SQLite, use sqlite3_open]

CREATE DATABASE My_First_Database

DROP DATABASE database_name

Delete a database [nb: not SQLite, use delete_file]

DROP DATABASE My_First_Database

Table Manipulation

CREATE TABLE " table_name"
(" column_1" " data_type_for_column_1",
" column_2" " data_type_for_column_2",
... )

Create a table in a database.

CREATE TABLE Person (LastName varchar, FirstName varchar, Address varchar, Age int)

Data Types (see also Datatypes In SQLite Version 3)
Data Type	Description
integer(size)	Hold integers only. The maximum number of digits are specified in parenthesis.
int(size)
smallint(size)
tinyint(size)
decimal(size,d)	Hold numbers with fractions. The maximum number of digits are specified in "size". The maximum number of digits to the right of the decimal is specified in "d".
numeric(size,d)
char(size)	Holds a fixed length string (can contain letters, numbers, and special characters). The fixed size is specified in parenthesis.
varchar(size)	Holds a variable length string (can contain letters, numbers, and special characters). The maximum size is specified in parenthesis.
date(yyyymmdd)	Holds a date

ALTER TABLE table_name ADD column_name datatype

Add columns in an existing table.

ALTER TABLE Person ADD Sex char(6)

ALTER TABLE table_name DROP column_name datatype

Delete columns in an existing table. [nb: SQLite does not implement DROP COLUMN.]

ALTER TABLE Person DROP Sex char(6)

DROP TABLE table_name

Delete a table.

DROP TABLE Person

Index Manipulation

CREATE INDEX index_name
ON table_name ( column_name_1, column_name_2, ...)

Create a simple index.

CREATE INDEX PersonIndex
ON Person (LastName, FirstName)

CREATE UNIQUE INDEX index_name
ON table_name ( column_name_1, column_name_2, ...)

Create a unique index.

CREATE UNIQUE INDEX PersonIndex
ON Person (LastName DESC)

DROP INDEX table_name.index_name

Delete an index.

DROP INDEX Person.PersonIndex

Data Manipulation

INSERT INTO table_name
VALUES ( value_1, value_2,....)

Insert new rows into a table.

INSERT INTO Persons
VALUES('Hussein', 'Saddam', 'White House')

INSERT INTO table_name ( column1, column2,...)
VALUES ( value_1, value_2,....)

INSERT INTO Persons (LastName, FirstName, Address)
VALUES('Hussein', 'Saddam', 'White House')

UPDATE table_name
SET column_name_1 = new_value_1, column_name_2 = new_value_2
WHERE column_name = some_value

Update one or several columns in rows.

UPDATE Person
SET Address = 'ups'
WHERE LastName = 'Hussein'

DELETE FROM table_name
WHERE column_name = some_value

Delete rows in a table.

DELETE FROM Person WHERE LastName = 'Hussein'

TRUNCATE TABLE table_name

Deletes the data inside the table. [nb: not SQLite (use "DELETE FROM table_name;")]

TRUNCATE TABLE Person

SELECT

SELECT column_name(s) FROM table_name

Select data from a table.

SELECT LastName, FirstName FROM Persons

SELECT * FROM table_name

Select all data from a table.

SELECT * FROM Persons

SELECT DISTINCT column_name(s) FROM table_name

Select only distinct (different) data from a table.

SELECT DISTINCT LastName, FirstName FROM Persons

SELECT column_name(s) FROM table_name
WHERE column operator value
      AND column operator value
      OR column operator value
      AND (... OR ...)
      ...

Select only certain data from a table.

SELECT * FROM Persons WHERE sex='female'

Operators
Operator	Description
=	Equal
<>	Not equal
>	Greater than
<	Less than
>=	Greater than or equal
<=	Less than or equal
BETWEEN	Between an inclusive range
LIKE	Search for a pattern. A "%" sign can be used to define wildcards (missing letters in the pattern) both before and after the pattern.

SELECT * FROM Persons WHERE Year>1970

SELECT * FROM Persons
WHERE FirstName='Saddam'
AND LastName='Hussein'

SELECT * FROM Persons
WHERE FirstName='Saddam'
OR LastName='Hussein'

SELECT * FROM Persons WHERE
(FirstName='Tove' OR FirstName='Stephen')
AND LastName='Svendson'

SELECT * FROM Persons WHERE FirstName LIKE 'O%'

SELECT * FROM Persons WHERE FirstName LIKE '%a'

SELECT * FROM Persons WHERE FirstName LIKE '%la%'

SELECT column_name(s) FROM table_name
WHERE column_name IN ( value1, value2, ...)

The IN operator may be used if you know the exact value you want to return for at least one of the columns.

SELECT * FROM Persons
WHERE LastName IN ('Hansen','Pettersen')

SELECT column_name(s) FROM table_name
ORDER BY row_1, row_2 DESC, row_3 ASC, ...

Select data from a table with sort the rows.

Note:
ASC (ascend) is a alphabetical and numerical order (optional)
DESC (descend) is a reverse alphabetical and numerical order

SELECT * FROM Persons
ORDER BY LastName

SELECT FirstName, LastName FROM Persons
ORDER BY LastName DESC

SELECT Company, OrderNumber FROM Orders
ORDER BY Company DESC, OrderNumber ASC

SELECT column_1, ..., SUM( group_column_name)
FROM table_name
GROUP BY group_column_name

GROUP BY... was added to SQL because aggregate functions (like SUM) return the aggregate of all column values every time they are called, and without the GROUP BY function it was impossible to find the sum for each individual group of column values.

SELECT Company, SUM(Amount)
FROM Sales
GROUP BY Company

Some aggregate functions
Function	Description
AVG(column)	Returns the average value of a column
COUNT(column)	Returns the number of rows (without a NULL value) of a column
MAX(column)	Returns the highest value of a column
MIN(column)	Returns the lowest value of a column
SUM(column)	Returns the total sum of a column

SELECT column_1, ..., SUM( group_column_name)
FROM table_name
GROUP BY group_column_name
HAVING SUM( group_column_name) condition value

HAVING... was added to SQL because the WHERE keyword could not be used against aggregate functions (like SUM), and without HAVING... it would be impossible to test for result conditions.

SELECT Company, SUM(Amount)
FROM Sales
GROUP BY Company
HAVING SUM(Amount)>10000

Alias

SELECT column_name AS column_alias FROM table_name

Column name alias

SELECT LastName AS Family, FirstName AS Name
FROM Persons

SELECT table_alias.column_name FROM table_name AS table_alias

Table name alias

SELECT LastName, FirstName
FROM Persons AS Employees

JOIN

SELECT column_1_name, column_2_name, ...
FROM first_table_name
INNER JOIN second_table_name
ON first_table_name.keyfield = second_table_name.foreign_keyfield

The INNER JOIN returns all rows from both tables where there is a match. If there are rows in first table that do not have matches in second table, those rows will not be listed.

SELECT Employees.Name, Orders.Product
FROM Employees
INNER JOIN Orders
ON Employees.Employee_ID=Orders.Employee_ID

SELECT column_1_name, column_2_name, ...
FROM first_table_name
LEFT JOIN second_table_name
ON first_table_name.keyfield = second_table_name.foreign_keyfield

The LEFT JOIN returns all the rows from the first table, even if there are no matches in the second table. If there are rows in first table that do not have matches in second table, those rows also will be listed.

SELECT Employees.Name, Orders.Product
FROM Employees
LEFT JOIN Orders
ON Employees.Employee_ID=Orders.Employee_ID

SELECT column_1_name, column_2_name, ...
FROM first_table_name
RIGHT JOIN second_table_name
ON first_table_name.keyfield = second_table_name.foreign_keyfield

The RIGHT JOIN returns all the rows from the second table, even if there are no matches in the first table. If there had been any rows in second table that did not have matches in first table, those rows also would have been listed.
[nb: SQLite does not implement RIGHT OUTER JOIN or FULL OUTER JOIN.]

SELECT Employees.Name, Orders.Product
FROM Employees
RIGHT JOIN Orders
ON Employees.Employee_ID=Orders.Employee_ID

UNION

SQL_Statement_1
UNION
SQL_Statement_2

Select all different values from SQL_Statement_1 and SQL_Statement_2

SELECT E_Name FROM Employees_Norway
UNION
SELECT E_Name FROM Employees_USA

SQL_Statement_1
UNION ALL
SQL_Statement_2

Select all values from SQL_Statement_1 and SQL_Statement_2

SELECT E_Name FROM Employees_Norway
UNION
SELECT E_Name FROM Employees_USA

SELECT INTO/IN

SELECT column_name(s)
INTO new_table_name
FROM source_table_name
WHERE query

Select data from table(S) and insert it into another table.

SELECT * INTO Persons_backup FROM Persons

SELECT column_name(s)
IN external_database_name
FROM source_table_name
WHERE query

Select data from table(S) and insert it in another database.

SELECT Persons.* INTO Persons IN 'Backup.db' FROM Persons WHERE City='Sandnes'

CREATE VIEW

CREATE VIEW view_name AS
SELECT column_name(s)
FROM table_name
WHERE condition

Create a virtual table based on the result-set of a SELECT statement.
[nb: SQLite views are read-only.]

CREATE VIEW [Current Product List] AS
SELECT ProductID, ProductName
FROM Products
WHERE Discontinued=No