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Applies to: 
SQL Server
Azure SQL Database
Azure SQL Managed Instance
Azure Synapse Analytics
SQL analytics endpoint in Microsoft Fabric
Warehouse in Microsoft Fabric
SQL database in Microsoft Fabric
Use the SELECT statement to retrieve rows from the database. SELECT lets you choose one or many rows or columns from one or many tables in the SQL Server Database Engine.
Because the full syntax SELECT statement is complex, detailed syntax elements and arguments are shown per clause. Refer to the Syntax section for how these clauses work together.
- WITH XMLNAMESPACES
- WITH common_table_expression
- SELECT clause
- INTO clause
- FROM clause (includes JOIN, APPLY, and PIVOT)
- WHERE clause
- GROUP BY clause
- HAVING clause
- QUALIFY clause (in Fabric Data Warehouse only)
- WINDOW clause
- ORDER BY clause
The UNION, EXCEPT, and INTERSECT operators can be used between queries to combine or compare their results into one result set.
Transact-SQL syntax conventions
Syntax
Syntax for SQL Server and Azure SQL Database:
Syntax for Azure Synapse Analytics and Microsoft Fabric:
[ WITH [ , ...n ] ]
SELECT
[ ; ]
::=
[ TOP ( top_expression ) ]
[ ALL | DISTINCT ]
{ * | column_name | expression } [ , ...n ]
[ FROM { table_source } [ , ...n ] ]
[ WHERE ]
[ GROUP BY ]
[ HAVING ]
[ QUALIFY ]
[ ORDER BY ]
[ OPTION ( [ , ...n ] ) ]
Remarks
The order of the clauses in the SELECT statement is significant. Any one of the optional clauses can be omitted, but when the optional clauses are used, they must appear in the appropriate order.
SELECT statements are permitted in user-defined functions only if the select lists of these statements contain expressions that assign values to variables that are local to the functions.
A four-part name constructed with the OPENDATASOURCE function as the server-name part can be used as a table source wherever a table name can appear in a SELECT statement. A four-part name can't be specified for Azure SQL Database.
Some syntax restrictions apply to SELECT statements that involve remote tables.
Logical processing order of the SELECT statement
The following steps show the logical processing order, or binding order, for a SELECT statement. This order determines when the objects defined in one step are made available to the clauses in subsequent steps. For example, if the query processor can bind to (access) the tables or views defined in the FROM clause, these objects and their columns are made available to all subsequent steps. Conversely, because the SELECT clause is step 8, any column aliases or derived columns defined in that clause can't be referenced by preceding clauses. However, they can be referenced by subsequent clauses such as the ORDER BY clause. The query processor determines the actual physical execution of the statement, and the order might vary from this list.
FROMONJOINWHEREGROUP BYWITH CUBEorWITH ROLLUPHAVINGQUALIFY(in Fabric Data Warehouse only)SELECTDISTINCTORDER BYTOP
Warning
There are uncommon cases where the previous sequence might differ. Suppose you have a clustered index on a view, and the view excludes some table rows, and the view's SELECT column list uses a CONVERT that changes a data type from varchar to int. In this situation, the CONVERT can execute before the WHERE clause executes. Often there's a way to modify your view to avoid the different sequence, if it matters in your case.
Permissions
Selecting data requires SELECT permission on the table or view, which could be inherited from a higher scope such as SELECT permission on the schema or CONTROL permission on the table. Or requires membership in the db_datareader or db_owner fixed database roles, or the sysadmin fixed server role. Creating a new table using SELECT INTO also requires both the CREATE TABLE permission, and the ALTER SCHEMA permission on the schema that owns the new table.
Examples
The following examples use the AdventureWorksPDW2022 database.
A. Use SELECT to retrieve rows and columns
This section shows three code examples. This first code example returns all rows (no WHERE clause is specified) and all columns (using the *) from the DimEmployee table.
SELECT *
FROM DimEmployee
ORDER BY LastName;
This next example using table aliasing to achieve the same result.
SELECT e.*
FROM DimEmployee AS e
ORDER BY LastName;
This example returns all rows (no WHERE clause is specified) and a subset of the columns (FirstName, LastName, StartDate) from the DimEmployee table in the AdventureWorksPDW2022 database. The third column heading is renamed to FirstDay.
SELECT FirstName,
LastName,
StartDate AS FirstDay
FROM DimEmployee
ORDER BY LastName;
This example returns only the rows for DimEmployee that have an EndDate that isn't NULL and a MaritalStatus of M (married).
SELECT FirstName,
LastName,
StartDate AS FirstDay
FROM DimEmployee
WHERE EndDate IS NOT NULL
AND MaritalStatus = 'M'
ORDER BY LastName;
B. Use SELECT with column headings and calculations
The following example returns all rows from the DimEmployee table, and calculates the gross pay for each employee based on their BaseRate and a 40-hour work week.
SELECT FirstName,
LastName,
BaseRate,
BaseRate * 40 AS GrossPay
FROM DimEmployee
ORDER BY LastName;
C. Use DISTINCT with SELECT
The following example uses DISTINCT to generate a list of all unique titles in the DimEmployee table.
SELECT DISTINCT Title
FROM DimEmployee
ORDER BY Title;
D. Use GROUP BY
The following example finds the total amount for all sales on each day.
SELECT OrderDateKey,
SUM(SalesAmount) AS TotalSales
FROM FactInternetSales
GROUP BY OrderDateKey
ORDER BY OrderDateKey;
Because of the GROUP BY clause, only one row containing the sum of all sales is returned for each day.
E. Use GROUP BY with multiple groups
The following example finds the average price and the sum of Internet sales for each day, grouped by order date and the promotion key.
SELECT OrderDateKey,
PromotionKey,
AVG(SalesAmount) AS AvgSales,
SUM(SalesAmount) AS TotalSales
FROM FactInternetSales
GROUP BY OrderDateKey, PromotionKey
ORDER BY OrderDateKey;
F. Use GROUP BY and WHERE
The following example puts the results into groups after retrieving only the rows with order dates later than August 1, 2002.
SELECT OrderDateKey,
SUM(SalesAmount) AS TotalSales
FROM FactInternetSales
WHERE OrderDateKey > '20020801'
GROUP BY OrderDateKey
ORDER BY OrderDateKey;
G. Use GROUP BY with an expression
The following example groups by an expression. You can group by an expression if the expression doesn't include aggregate functions.
SELECT SUM(SalesAmount) AS TotalSales
FROM FactInternetSales
GROUP BY (OrderDateKey * 10);
H. Use GROUP BY with ORDER BY
The following example finds the sum of sales per day, and orders by the day.
SELECT OrderDateKey,
SUM(SalesAmount) AS TotalSales
FROM FactInternetSales
GROUP BY OrderDateKey
ORDER BY OrderDateKey;
I. Use the HAVING clause
This query uses the HAVING clause to restrict results.
SELECT OrderDateKey,
SUM(SalesAmount) AS TotalSales
FROM FactInternetSales
GROUP BY OrderDateKey
HAVING OrderDateKey > 20010000
ORDER BY OrderDateKey;