# SELECT

The SELECT statement is at the heart of most SQL queries. It defines what result set should be returned by the query, and is almost always used in conjunction with the FROM clause, which defines what part(s) of the database should be queried.

# Using the wildcard character to select all columns in a query.

Consider a database with the following two tables.

Employees table:

Id	FName	LName	DeptId
1	James	Smith	3
2	John	Johnson	4

Departments table:

Id	Name
1	Sales
2	Marketing
3	Finance
4	IT

# Simple select statement

* is the wildcard character used to select all available columns in a table.

When used as a substitute for explicit column names, it returns all columns in all tables that a query is selecting FROM. This effect applies to all tables the query accesses through its JOIN clauses.

Consider the following query:

SELECT * FROM Employees

It will return all fields of all rows of the Employees table:

Id	FName	LName	DeptId
1	James	Smith	3
2	John	Johnson	4

# Dot notation

To select all values from a specific table, the wildcard character can be applied to the table with dot notation.

Consider the following query:

SELECT 
    Employees.*, 
    Departments.Name
FROM 
    Employees
JOIN 
    Departments 
    ON Departments.Id = Employees.DeptId

This will return a data set with all fields on the Employee table, followed by just the Name field in the Departments table:

|Id|FName|LName|DeptId|Name |---|---|---|--- |1|James|Smith|3|Finance |2|John|Johnson|4|IT

Warnings Against Use

It is generally advised that using * is avoided in production code where possible, as it can cause a number of potential problems including:

Excess IO, network load, memory use, and so on, due to the database engine reading data that is not needed and transmitting it to the front-end code. This is particularly a concern where there might be large fields such as those used to store long notes or attached files.
Further excess IO load if the database needs to spool internal results to disk as part of the processing for a query more complex than SELECT <columns> FROM <table>.
Extra processing (and/or even more IO) if some of the unneeded columns are:
computed columns in databases that support them
in the case of selecting from a view, columns from a table/view that the query optimiser could otherwise optimise out
The potential for unexpected errors if columns are added to tables and views later that results ambiguous column names. For example SELECT * FROM orders JOIN people ON people.id = orders.personid ORDER BY displayname - if a column column called displayname is added to the orders table to allow users to give their orders meaningful names for future reference then the column name will appear twice in the output so the ORDER BY clause will be ambiguous which may cause errors ("ambiguous column name" in recent MS SQL Server versions), and if not in this example your application code might start displaying the order name where the person name is intended because the new column is the first of that name returned, and so on.

# When Can You Use `*`, Bearing The Above Warning In Mind?

While best avoided in production code, using * is fine as a shorthand when performing manual queries against the database for investigation or prototype work.

Sometimes design decisions in your application make it unavoidable (in such circumstances, prefer tablealias.* over just * where possible).

When using EXISTS, such as SELECT A.col1, A.Col2 FROM A WHERE EXISTS (SELECT * FROM B where A.ID = B.A_ID), we are not returning any data from B. Thus a join is unnecessary, and the engine knows no values from B are to be returned, thus no performance hit for using *. Similarly COUNT(*) is fine as it also doesn't actually return any of the columns, so only needs to read and process those that are used for filtering purposes.

# SELECT Using Column Aliases

Column aliases are used mainly to shorten code and make column names more readable.

Code becomes shorter as long table names and unnecessary identification of columns (e.g., there may be 2 IDs in the table, but only one is used in the statement) can be avoided. Along with table aliases (opens new window) this allows you to use longer descriptive names in your database structure while keeping queries upon that structure concise.

Furthermore they are sometimes required, for instance in views, in order to name computed outputs.

# All versions of SQL

Aliases can be created in all versions of SQL using double quotes (").

SELECT 
    FName AS "First Name", 
    MName AS "Middle Name",
    LName AS "Last Name"
FROM Employees

# Different Versions of SQL

You can use single quotes ('), double quotes (") and square brackets ([]) to create an alias in Microsoft SQL Server.

SELECT 
    FName AS "First Name", 
    MName AS 'Middle Name',
    LName AS [Last Name]
FROM Employees

Both will result in:

First Name	Middle Name	Last Name
James	John	Smith
John	James	Johnson
Michael	Marcus	Williams

This statement will return FName and LName columns with a given name (an alias). This is achieved using the AS operator followed by the alias, or simply writing alias directly after the column name. This means that the following query has the same outcome as the above.

SELECT 
    FName "First Name", 
    MName "Middle Name",
    LName "Last Name"
FROM Employees

First Name	Middle Name	Last Name
James	John	Smith
John	James	Johnson
Michael	Marcus	Williams

However, the explicit version (i.e., using the AS operator) is more readable.

If the alias has a single word that is not a reserved word, we can write it without single quotes, double quotes or brackets:

SELECT 
    FName AS FirstName, 
    LName AS LastName
FROM Employees

FirstName	LastName
James	Smith
John	Johnson
Michael	Williams

A further variation available in MS SQL Server amongst others is <alias> = <column-or-calculation>, for instance:

SELECT FullName = FirstName + ' ' + LastName, 
       Addr1    = FullStreetAddress,
       Addr2    = TownName
FROM CustomerDetails

which is equivalent to:

SELECT FirstName + ' ' + LastName As FullName
       FullStreetAddress          As Addr1,
       TownName                   As Addr2
FROM CustomerDetails

Both will result in:

FullName	Addr1	Addr2
James Smith	123 AnyStreet	TownVille
John Johnson	668 MyRoad	Anytown
Michael Williams	999 High End Dr	Williamsburgh

Some find using = instead of As easier to read, though many recommend against this format, mainly because it is not standard so not widely supported by all databases. It may cause confusion with other uses of the = character.

# All Versions of SQL

Also, if you need to use reserved words, you can use brackets or quotes to escape:

SELECT
    FName as "SELECT",
    MName as "FROM",
    LName as "WHERE"
FROM Employees

# Different Versions of SQL

Likewise, you can escape keywords in MSSQL with all different approaches:

SELECT 
    FName AS "SELECT", 
    MName AS 'FROM',
    LName AS [WHERE]
FROM Employees

SELECT	FROM	WHERE
James	John	Smith
John	James	Johnson
Michael	Marcus	Williams

Also, a column alias may be used any of the final clauses of the same query, such as an ORDER BY:

SELECT 
    FName AS FirstName, 
    LName AS LastName
FROM 
    Employees 
ORDER BY 
    LastName DESC

However, you may not use

SELECT
    FName AS SELECT,
    LName AS FROM
FROM 
    Employees
ORDER BY 
    LastName DESC

To create an alias from these reserved words (SELECT and FROM).

This will cause numerous errors on execution.

# Select Individual Columns

SELECT 
    PhoneNumber, 
    Email, 
    PreferredContact 
FROM Customers

This statement will return the columns PhoneNumber, Email, and PreferredContact from all rows of the Customers (opens new window) table. Also the columns will be returned in the sequence in which they appear in the SELECT clause.

The result will be:

PhoneNumber	Email	PreferredContact
3347927472	william.jones@example.com	PHONE
2137921892	dmiller@example.net	EMAIL
NULL	richard0123@example.com	EMAIL

If multiple tables are joined together, you can select columns from specific tables by specifying the table name before the column name: [table_name].[column_name]

SELECT 
    Customers.PhoneNumber, 
    Customers.Email, 
    Customers.PreferredContact,
    Orders.Id AS OrderId
FROM 
    Customers
LEFT JOIN 
    Orders ON Orders.CustomerId = Customers.Id

*AS OrderId means that the Id field of Orders table will be returned as a column named OrderId. See selecting with column alias (opens new window) for further information.

To avoid using long table names, you can use table aliases. This mitigates the pain of writing long table names for each field that you select in the joins. If you are performing a self join (a join between two instances of the same table), then you must use table aliases to distinguish your tables. We can write a table alias like Customers c or Customers AS c. Here c works as an alias for Customers and we can select let's say Email like this: c.Email.

SELECT 
    c.PhoneNumber, 
    c.Email, 
    c.PreferredContact,
    o.Id AS OrderId
FROM 
    Customers c
LEFT JOIN 
    Orders o ON o.CustomerId = c.Id

# Selecting specified number of records

The SQL 2008 standard (opens new window) defines the FETCH FIRST clause to limit the number of records returned.

SELECT Id, ProductName, UnitPrice, Package 
FROM Product 
ORDER BY UnitPrice DESC
FETCH FIRST 10 ROWS ONLY

This standard is only supported in recent versions of some RDMSs. Vendor-specific non-standard syntax is provided in other systems. Progress OpenEdge 11.x also supports the FETCH FIRST <n> ROWS ONLY syntax.

Additionally, OFFSET <m> ROWS before FETCH FIRST <n> ROWS ONLY allows skipping rows before fetching rows.

SELECT Id, ProductName, UnitPrice, Package 
FROM Product 
ORDER BY UnitPrice DESC
OFFSET 5 ROWS
FETCH FIRST 10 ROWS ONLY

The following query is supported in SQL Server (opens new window) and MS Access:

SELECT TOP 10 Id, ProductName, UnitPrice, Package
FROM Product
ORDER BY UnitPrice DESC

To do the same in MySQL (opens new window) or PostgreSQL the LIMIT keyword must be used:

SELECT Id, ProductName, UnitPrice, Package
FROM Product
ORDER BY UnitPrice DESC
LIMIT 10

In Oracle the same can be done with ROWNUM:

SELECT Id, ProductName, UnitPrice, Package
FROM Product
WHERE ROWNUM <= 10
ORDER BY UnitPrice DESC

Results: 10 records.

Id    ProductName               UnitPrice             Package
38    Côte de Blaye             263.50                12 - 75 cl bottles
29    Thüringer Rostbratwurst   123.79                50 bags x 30 sausgs.
9    Mishi Kobe Niku            97.00                 18 - 500 g pkgs.
20    Sir Rodney's Marmalade    81.00                 30 gift boxes
18    Carnarvon Tigers          62.50                 16 kg pkg.
59    Raclette Courdavault      55.00                 5 kg pkg.
51    Manjimup Dried Apples     53.00                 50 - 300 g pkgs.
62    Tarte au sucre            49.30                 48 pies
43    Ipoh Coffee               46.00                 16 - 500 g tins
28    Rössle Sauerkraut         45.60                 25 - 825 g cans

Vendor Nuances:

It is important to note that the TOP in Microsoft SQL operates after the WHERE clause and will return the specified number of results if they exist anywhere in the table, while ROWNUM works as part of the WHERE clause so if other conditions do not exist in the specified number of rows at the beginning of the table, you will get zero results when there could be others to be found.

# Selecting with Condition

The basic syntax of SELECT with WHERE clause is:

SELECT column1, column2, columnN
FROM table_name
WHERE [condition]

The [condition] can be any SQL expression, specified using comparison or logical operators like >, <, =, <>, >=, <=, LIKE, NOT, IN, BETWEEN etc.

The following statement returns all columns from the table 'Cars' where the status column is 'READY':

SELECT * FROM Cars WHERE status = 'READY'

See WHERE and HAVING (opens new window) for more examples.

# Selecting with CASE

When results need to have some logic applied 'on the fly' one can use CASE statement to implement it.

SELECT CASE WHEN Col1 < 50 THEN 'under' ELSE 'over' END threshold
FROM TableName

also can be chained

SELECT 
    CASE WHEN Col1 < 50 THEN 'under' 
         WHEN Col1 > 50 AND Col1 <100 THEN 'between' 
         ELSE 'over' 
    END threshold
FROM TableName

one also can have CASE inside another CASE statement

SELECT 
    CASE WHEN Col1 < 50 THEN 'under' 
         ELSE 
            CASE WHEN Col1 > 50 AND Col1 <100 THEN Col1 
            ELSE 'over' END 
    END threshold
FROM TableName

# Select columns which are named after reserved keywords

When a column name matches a reserved keyword, standard SQL requires that you enclose it in double quotation marks:

SELECT 
    "ORDER",
    ID 
FROM ORDERS

Note that it makes the column name case-sensitive.

Some DBMSes have proprietary ways of quoting names. For example, SQL Server uses square brackets for this purpose:

SELECT 
    [Order],
    ID 
FROM ORDERS

while MySQL (and MariaDB) by default use backticks:

SELECT 
    `Order`,
    id 
FROM orders

# Selecting with table alias

SELECT e.Fname, e.LName 
FROM Employees e

The Employees table is given the alias 'e' directly after the table name. This helps remove ambiguity in scenarios where multiple tables have the same field name and you need to be specific as to which table you want to return data from.

SELECT e.Fname, e.LName, m.Fname AS ManagerFirstName 
FROM Employees e 
    JOIN Managers m ON e.ManagerId = m.Id

Note that once you define an alias, you can't use the canonical table name anymore. i.e.,

SELECT e.Fname, Employees.LName, m.Fname AS ManagerFirstName 
FROM Employees e 
JOIN Managers m ON e.ManagerId = m.Id

would throw an error.

It is worth noting table aliases -- more formally 'range variables' -- were introduced into the SQL language to solve the problem of duplicate columns caused by INNER JOIN. The 1992 SQL standard corrected this earlier design flaw by introducing NATURAL JOIN (implemented in mySQL, PostgreSQL and Oracle but not yet in SQL Server), the result of which never has duplicate column names. The above example is interesting in that the tables are joined on columns with different names (Id and ManagerId) but are not supposed to be joined on the columns with the same name (LName, FName), requiring the renaming of the columns to be performed before the join:

SELECT Fname, LName, ManagerFirstName 
FROM Employees
     NATURAL JOIN
     ( SELECT Id AS ManagerId, Fname AS ManagerFirstName
       FROM Managers ) m;

Note that although an alias/range variable must be declared for the dervied table (otherwise SQL will throw an error), it never makes sense to actually use it in the query.

# Selection with sorted Results

SELECT * FROM Employees ORDER BY LName

This statement will return all the columns from the table Employees (opens new window).

Id	FName	LName	PhoneNumber
2	John	Johnson	2468101214
1	James	Smith	1234567890
3	Michael	Williams	1357911131

SELECT * FROM Employees ORDER BY LName DESC


SELECT * FROM Employees ORDER BY LName ASC

This statement changes the sorting direction.

One may also specify multiple sorting columns. For example:

SELECT * FROM Employees ORDER BY LName ASC, FName ASC

This example will sort the results first by LName and then, for records that have the same LName, sort by FName. This will give you a result similar to what you would find in a telephone book.

In order to save retyping the column name in the ORDER BY clause, it is possible to use instead the column's number. Note that column numbers start from 1.

SELECT Id, FName, LName, PhoneNumber FROM Employees ORDER BY 3

You may also embed a CASE statement in the ORDER BY clause.

SELECT Id, FName, LName, PhoneNumber FROM Employees ORDER BY CASE WHEN LName='Jones` THEN 0 ELSE 1 END ASC

This will sort your results to have all records with the LName of "Jones" at the top.

# Selecting with Aggregate functions

# Average

SELECT AVG(Salary) FROM Employees

SELECT AVG(Salary) FROM Employees where DepartmentId = 1

If employee is categorized with multiple department and we want to find avg salary for every department then we can use following query.

SELECT AVG(Salary) FROM Employees GROUP BY DepartmentId

# Minimum

SELECT MIN(Salary) FROM Employees

# Maximum

SELECT MAX(Salary) FROM Employees

# Count

SELECT Count(*) FROM Employees

SELECT Count(*) FROM Employees where ManagerId IS NOT NULL

Select Count(ManagerId) from Employees

Select Count(DISTINCT DepartmentId) from Employees

# Sum

SELECT SUM(Salary) FROM Employees

# Selecting without Locking the table

Sometimes when tables are used mostly (or only) for reads, indexing does not help anymore and every little bit counts, one might use selects without LOCK to improve performance.

SQL Server

SELECT * FROM TableName WITH (nolock)

MySQL

SET SESSION TRANSACTION ISOLATION LEVEL READ UNCOMMITTED;
SELECT * FROM TableName;
SET SESSION TRANSACTION ISOLATION LEVEL REPEATABLE READ;

Oracle

SET TRANSACTION ISOLATION LEVEL READ UNCOMMITTED;
SELECT * FROM TableName;

DB2

SELECT * FROM TableName WITH UR;

where UR stands for "uncommitted read".

If used on table that has record modifications going on might have unpredictable results.

# Select with condition of multiple values from column

SELECT * FROM Cars  WHERE status IN ( 'Waiting', 'Working' )

This is semantically equivalent to

SELECT * FROM Cars  WHERE ( status = 'Waiting' OR status = 'Working' )

i.e. value IN ( <value list> ) is a shorthand for disjunction (logical OR).

# Get aggregated result for row groups

Counting rows based on a specific column value:

SELECT category, COUNT(*) AS item_count
FROM item
GROUP BY category;

Getting average income by department:

SELECT department, AVG(income)
FROM employees
GROUP BY department;

The important thing is to select only columns specified in the GROUP BY (opens new window) clause or used with aggregate functions (opens new window).

There WHERE clause can also be used with GROUP BY, but WHERE filters out records before any grouping is done:

SELECT department, AVG(income)
FROM employees
WHERE department <> 'ACCOUNTING'
GROUP BY department;

If you need to filter the results after the grouping has been done, e.g, to see only departments whose average income is larger than 1000, you need to use the HAVING (opens new window) clause:

SELECT department, AVG(income)
FROM employees
WHERE department <> 'ACCOUNTING'
GROUP BY department
HAVING avg(income) > 1000;

# Selecting with more than 1 condition.

The AND keyword is used to add more conditions to the query.

Name	Age	Gender
Sam	18	M
John	21	M
Bob	22	M
Mary	23	F

SELECT name FROM persons WHERE gender = 'M' AND age > 20;

This will return:

Name
John
Bob

using OR keyword

SELECT name FROM persons WHERE gender = 'M' OR age < 20;

This will return:

name
Sam
John
Bob

These keywords can be combined to allow for more complex criteria combinations:

SELECT name
FROM persons
WHERE (gender = 'M' AND age < 20)
   OR (gender = 'F' AND age > 20);

This will return:

name
Sam
Mary

# Select rows from multiple tables

SELECT *
FROM
    table1,
    table2

SELECT
    table1.column1,
    table1.column2,
    table2.column1
FROM
    table1,
    table2

This is called cross product in SQL it is same as cross product in sets

These statements return the selected columns from multiple tables in one query.

There is no specific relationship between the columns returned from each table.

# Selecting with null

SELECT Name FROM Customers WHERE PhoneNumber IS NULL

Selection with nulls take a different syntax. Don't use =, use IS NULL or IS NOT NULL instead.

# Select distinct (unique values only)

SELECT DISTINCT ContinentCode
FROM Countries;

This query will return all DISTINCT (unique, different) values from ContinentCode column from Countries (opens new window) table

ContinentCode
OC
EU
AS
NA
AF

SQLFiddle Demo (opens new window)

# Syntax

SELECT [DISTINCT] [column1] [, [column2] ... ]
FROM [table]
[ WHERE condition ]
[ GROUP BY [column1] [, [column2] ... ]

[ HAVING [column1] [, [column2] ... ] [ ORDER BY ASC | DESC ]

# Remarks

SELECT determines which columns' data to return and in which order FROM a given table (given that they match the other requirements in your query specifically - where and having filters and joins).

SELECT Name, SerialNumber
FROM ArmyInfo

will only return results from the Name and Serial Number columns, but not from the column called Rank, for example

SELECT *
FROM ArmyInfo

indicates that all columns will be returned. However, please note that it is poor practice to SELECT * as you are literally returning all columns of a table.

← Example Databases and Tables GROUP BY →

# SELECT

# Using the wildcard character to select all columns in a query.

# Simple select statement

# Dot notation

# When Can You Use *, Bearing The Above Warning In Mind?

# SELECT Using Column Aliases

# All versions of SQL

# Different Versions of SQL

# All Versions of SQL

# Different Versions of SQL

# Select Individual Columns

# Selecting specified number of records

# Selecting with Condition

# Selecting with CASE

# Select columns which are named after reserved keywords

# Selecting with table alias

# Selection with sorted Results

# Selecting with Aggregate functions

# Average

# Minimum

# Maximum

# Count

# Sum

# Selecting without Locking the table

# Select with condition of multiple values from column

# Get aggregated result for row groups

# Selecting with more than 1 condition.

# Select rows from multiple tables

# Selecting with null

# Select distinct (unique values only)

# Syntax

# Remarks

# When Can You Use `*`, Bearing The Above Warning In Mind?