**APPLIES TO:** ![yes](media/yes.png)SQL Server (starting with 2008) ![yes](media/yes.png)Azure SQL Database ![no](media/no.png)Azure SQL Data Warehouse ![no](media/no.png)Parallel Data Warehouse

A. Using SELECT to retrieve rows and columns

The following example shows three code examples. This first code example returns all rows (no WHERE clause is specified) and all columns (using the *) from the Product table in the **AdventureWorks2012** database.

This example returns all rows (no WHERE clause is specified), and only a subset of the columns (Name, ProductNumber, ListPrice) from the Product table in the **AdventureWorks2012** database. Additionally, a column heading is added.

This example returns only the rows for Product that have a product line of R and that have days to manufacture that is less than 4.

B. Using SELECT with column headings and calculations

The following examples return all rows from the Product table. The first example returns total sales and the discounts for each product. In the second example, the total revenue is calculated for each product.

This is the query that calculates the revenue for each product in each sales order.

C. Using DISTINCT with SELECT

The following example uses DISTINCT to prevent the retrieval of duplicate titles.

D. Creating tables with SELECT INTO

The following first example creates a temporary table named #Bicycles in tempdb.

E. Using correlated subqueries

The following example shows queries that are semantically equivalent and illustrates the difference between using the EXISTS keyword and the IN keyword. Both are examples of a valid subquery that retrieves one instance of each product name for which the product model is a long sleeve logo jersey, and the ProductModelID numbers match between the Product and ProductModel tables.

The following example uses IN in a correlated, or repeating, subquery. This is a query that depends on the outer query for its values. The query is executed repeatedly, one time for each row that may be selected by the outer query. This query retrieves one instance of the first and last name of each employee for which the bonus in the SalesPerson table is 5000.00 and for which the employee identification numbers match in the Employee and SalesPerson tables.

The previous subquery in this statement cannot be evaluated independently of the outer query. It requires a value for Employee.EmployeeID, but this value changes as the SQL Server Database Engine examines different rows in Employee.

A correlated subquery can also be used in the HAVING clause of an outer query. This example finds the product models for which the maximum list price is more than twice the average for the model.

This example uses two correlated subqueries to find the names of employees who have sold a particular product.

F. Using GROUP BY

Because of the GROUP BY clause, only one row containing the sum of all sales is returned for each sales order.

G. Using GROUP BY with multiple groups

The following example finds the average price and the sum of year-to-date sales, grouped by product ID and special offer ID.

H. Using GROUP BY and WHERE

The following example puts the results into groups after retrieving only the rows with list prices greater than $1000.

I. Using GROUP BY with an expression

The following example groups by an expression. You can group by an expression if the expression does not include aggregate functions.

J. Using GROUP BY with ORDER BY

The following example finds the average price of each type of product and orders the results by average price.

K. Using the HAVING clause

The first example that follows shows a HAVING clause with an aggregate function. It groups the rows in the SalesOrderDetail table by product ID and eliminates products whose average order quantities are five or less. The second example shows a HAVING clause without aggregate functions.

USE AdventureWorks2012 ;  
GO  
SELECT SalesOrderID, CarrierTrackingNumber   
FROM Sales.SalesOrderDetail  
GROUP BY SalesOrderID, CarrierTrackingNumber  
HAVING CarrierTrackingNumber LIKE '4BD%'  
ORDER BY SalesOrderID ;  
GO

L. Using HAVING and GROUP BY

The following example shows using GROUP BY, HAVING, WHERE, and ORDER BY clauses in one SELECT statement. It produces groups and summary values but does so after eliminating the products with prices over $25 and average order quantities under 5. It also organizes the results by ProductID.

M. Using HAVING with SUM and AVG

The following example groups the SalesOrderDetail table by product ID and includes only those groups of products that have orders totaling more than $1000000.00 and whose average order quantities are less than 3.

To see the products that have had total sales greater than $2000000.00, use this query:

If you want to make sure there are at least one thousand five hundred items involved in the calculations for each product, use HAVING COUNT(*) > 1500 to eliminate the products that return totals for fewer than 1500 items sold. The query looks like this:

N. Using the INDEX optimizer hint

The following example shows two ways to use the INDEX optimizer hint. The first example shows how to force the optimizer to use a nonclustered index to retrieve rows from a table, and the second example forces a table scan by using an index of 0.

M. Using OPTION and the GROUP hints

The following example shows how the OPTION (GROUP) clause is used with a GROUP BY clause.

O. Using the UNION query hint

P. Using a simple UNION

In the following example, the result set includes the contents of the ProductModelID and Name columns of both the ProductModel and Gloves tables.

Q. Using SELECT INTO with UNION

In the following example, the INTO clause in the second SELECT statement specifies that the table named ProductResults holds the final result set of the union of the designated columns of the ProductModel and Gloves tables. Note that the Gloves table is created in the first SELECT statement.

R. Using UNION of two SELECT statements with ORDER BY

The order of certain parameters used with the UNION clause is important. The following example shows the incorrect and correct use of UNION in two SELECT statements in which a column is to be renamed in the output.

S. Using UNION of three SELECT statements to show the effects of ALL and parentheses

The following examples use UNION to combine the results of three tables that all have the same 5 rows of data. The first example uses UNION ALL to show the duplicated records, and returns all 15 rows. The second example uses UNION without ALL to eliminate the duplicate rows from the combined results of the three SELECT statements, and returns 5 rows.

The third example uses ALL with the first UNION and parentheses enclose the second UNION that is not using ALL. The second UNION is processed first because it is in parentheses, and returns 5 rows because the ALL option is not used and the duplicates are removed. These 5 rows are combined with the results of the first SELECT by using the UNION ALL keywords. This does not remove the duplicates between the two sets of 5 rows. The final result has 10 rows.

SELECT Examples (Transact-SQL)