SQLite - ALIAS Syntax

The SQLite ALIAS statement is used to provide a temporary name to a column of a table, aggregate function column or a table itself. A alias name exists for only for the duration of the query. It facilitates easy to understand names and hence increases readability of a query.

Syntax

The syntax for using ALIAS statement in SQLite is given below:

/* Using ALIAS with a column of a table */
SELECT column_name AS alias_name
FROM table_name;

/* Using ALIAS with an aggregate function */
SELECT SUM(column_name) AS alias_name
FROM table_name
WHERE condition(s);

/* Using ALIAS with a table */
SELECT alias_name_1.column1, alias_name_2.column1, ...
FROM table1 AS alias_name_1
INNER JOIN table2 AS alias_name_2
ON alias_name_1.matching_column = alias_name_2.matching_column;

Example:

Consider a database containing tables called Employee and Contact_Info with the following records:

Table 1: Employee table

Table 2: Contact_Info table

• ALIAS with a column: The below statement is used to create a aliases of columns - name and City of the Employee table.

  SELECT Name AS [Employee Name], Age AS [Employee Age], City 
  FROM Employee;
  

  
  

  This will produce the result as shown below:

  Employee Name	Employee Age	City
  John	25	London
  Marry	24	New York
  Jo	27	Paris
  Kim	30	Amsterdam
  Ramesh	28	New Delhi
  Huang	28	Beijing

• ALIAS with an aggregate function: The below query is used to fetch the number of employees whose age is greater than 27.

  SELECT COUNT(Name) AS [Number of Employees]
  FROM Employee
  WHERE Age > 27;
  

  
  

  This will bring the following result:

  Number of Employees
  3

• ALIAS with a table: To inner join Employee and Contact_Info tables based on matching column EmpID, the statement is given below. While performing inner join of two tables, aliases of tables are used.

  SELECT A.Name, A.Age, B.Address 
  FROM Employee AS A
  INNER JOIN Contact_Info AS B
  ON A.EmpID = B.EmpID;
  

  
  

  The result of above query will be:

  Name	Age	Address
  Marry	24	Brooklyn, New York, USA
  Jo	27	Grenelle, Paris, France
  Kim	30	Geuzenveld, Amsterdam, Netherlands
  Huang	28	Yizhuangzhen, Beijing, China