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SELECT (Transact-SQL)

  • Artikel

Applies to: SQL Server Azure SQL Database Azure SQL Managed Instance Azure Synapse Analytics Analytics Platform System (PDW) SQL analytics endpoint in Microsoft Fabric Warehouse in Microsoft Fabric SQL database in Microsoft Fabric

Retrieves rows from the database and enables the selection of one or many rows or columns from one or many tables in the SQL Server Database Engine. The full syntax of the SELECT statement is complex, but the main clauses can be summarized as follows:

[ WITH { [ XMLNAMESPACES , ] [ common_table_expression ] } ]

SELECT select_list [ INTO new_table ]

[ FROM table_source ] [ WHERE search_condition ]

[ GROUP BY group_by_expression ]

[ HAVING search_condition ]

[ WINDOW window_expression ]

[ ORDER BY order_expression [ ASC | DESC ] ]

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:

<SELECT statement> ::=
    [ WITH { [ XMLNAMESPACES , ] [ <common_table_expression> [ , ...n ] ] } ]
    <query_expression>
    [ ORDER BY <order_by_expression> ]
    [ <FOR Clause> ]
    [ OPTION ( <query_hint> [ , ...n ] ) ]
<query_expression> ::=
    { <query_specification> | ( <query_expression> ) }
    [  { UNION [ ALL ] | EXCEPT | INTERSECT }
        <query_specification> | ( <query_expression> ) [ ...n ] ]
<query_specification> ::=
SELECT [ ALL | DISTINCT ]
    [ TOP ( expression ) [ PERCENT ] [ WITH TIES ] ]
    <select_list>
    [ INTO new_table ]
    [ FROM { <table_source> } [ , ...n ] ]
    [ WHERE <search_condition> ]
    [ <GROUP BY> ]
    [ HAVING <search_condition> ]
[ ; ]

Syntax for Azure Synapse Analytics and Parallel Data Warehouse and Microsoft Fabric:

[ WITH <common_table_expression> [ , ...n ] ]
SELECT <select_criteria>
[ ; ]

<select_criteria> ::=
    [ TOP ( top_expression ) ]
    [ ALL | DISTINCT ]
    { * | column_name | expression } [ , ...n ]
    [ FROM { table_source } [ , ...n ] ]
    [ WHERE <search_condition> ]
    [ GROUP BY <group_by_clause> ]
    [ HAVING <search_condition> ]
    [ ORDER BY <order_by_expression> ]
    [ OPTION ( <query_option> [ , ...n ] ) ]

Remarks

Because of the complexity of the SELECT statement, detailed syntax elements and arguments are shown per clause:

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.

  1. FROM
  2. ON
  3. JOIN
  4. WHERE
  5. GROUP BY
  6. WITH CUBE or WITH ROLLUP
  7. HAVING
  8. SELECT
  9. DISTINCT
  10. ORDER BY
  11. TOP

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;

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