SELECT Examples (Transact-SQL)
This topic provides examples of using the SELECT statement.
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 AdventureWorks database.
USE AdventureWorks ;
GO
SELECT *
FROM Production.Product
ORDER BY Name ASC ;
-- Alternate way.
USE AdventureWorks ;
GO
SELECT p.*
FROM Production.Product p
ORDER BY Name ASC ;
GO
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 AdventureWorks database. Additionally, a column heading is added.
USE AdventureWorks ;
GO
SELECT Name, ProductNumber, ListPrice AS Price
FROM Production.Product
ORDER BY Name ASC ;
GO
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.
USE AdventureWorks ;
GO
SELECT Name, ProductNumber, ListPrice AS Price
FROM Production.Product
WHERE ProductLine = 'R'
AND DaysToManufacture < 4
ORDER BY Name ASC ;
GO
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.
USE AdventureWorks ;
GO
SELECT p.Name AS ProductName,
NonDiscountSales = (OrderQty * UnitPrice),
Discounts = ((OrderQty * UnitPrice) * UnitPriceDiscount)
FROM Production.Product p
INNER JOIN Sales.SalesOrderDetail sod
ON p.ProductID = sod.ProductID
ORDER BY ProductName DESC ;
GO
This is the query that calculates the revenue for each product in each sales order.
USE AdventureWorks ;
GO
SELECT 'Total income is', ((OrderQty * UnitPrice) * (1.0 - UnitPriceDiscount)), ' for ',
p.Name AS ProductName
FROM Production.Product p
INNER JOIN Sales.SalesOrderDetail sod
ON p.ProductID = sod.ProductID
ORDER BY ProductName ASC ;
GO
C. Using DISTINCT with SELECT
The following example uses DISTINCT to prevent the retrieval of duplicate titles.
USE AdventureWorks ;
GO
SELECT DISTINCT Title
FROM HumanResources.Employee
ORDER BY Title ;
GO
D. Creating tables with SELECT INTO
The following first example creates a temporary table named #Bicycles in tempdb. To use this table, always refer to it with the exact name that is shown. This includes the number sign (#).
USE tempdb ;
IF OBJECT_ID (N'#Bicycles',N'U') IS NOT NULL
DROP TABLE #Bicycles ;
GO
USE AdventureWorks;
GO
SET NOCOUNT ON
SELECT *
INTO #Bicycles
FROM Production.Product
WHERE ProductNumber LIKE 'BK%'
SET NOCOUNT OFF
SELECT name
FROM tempdb..sysobjects
WHERE name LIKE '#Bicycles%' ;
GO
Here is the result set.
name
------------------------------
#Bicycles_____________________
This second example creates the permanent table NewProducts.
USE AdventureWorks ;
GO
IF OBJECT_ID ('dbo.NewProducts', 'U') IS NOT NULL
DROP TABLE dbo.NewProducts ;
GO
ALTER DATABASE AdventureWorks SET RECOVERY BULK_LOGGED ;
GO
SELECT * INTO dbo.NewProducts
FROM Production.Product
WHERE ListPrice > $25
AND ListPrice < $100
SELECT name
FROM sysobjects
WHERE name LIKE 'New%'
USE master ;
GO
ALTER DATABASE AdventureWorks SET RECOVERY FULL ;
GO
Here is the result set.
name
------------------------------
NewProducts
(1 row(s) affected)
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.
USE AdventureWorks ;
GO
SELECT DISTINCT Name
FROM Production.Product p
WHERE EXISTS
(SELECT *
FROM Production.ProductModel pm
WHERE p.ProductModelID = pm.ProductModelID
AND pm.Name = 'Long-sleeve logo jersey') ;
GO
-- OR
USE AdventureWorks ;
GO
SELECT DISTINCT Name
FROM Production.Product
WHERE ProductModelID IN
(SELECT ProductModelID
FROM Production.ProductModel
WHERE Name = 'Long-sleeve logo jersey') ;
GO
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.
USE AdventureWorks ;
GO
SELECT DISTINCT c.LastName, c.FirstName
FROM Person.Contact c JOIN HumanResources.Employee e
ON e.ContactID = c.ContactID WHERE 5000.00 IN
(SELECT Bonus
FROM Sales.SalesPerson sp
WHERE e.EmployeeID = sp.SalesPersonID) ;
GO
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 2005 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.
USE AdventureWorks
GO
SELECT p1.ProductModelID
FROM Production.Product p1
GROUP BY p1.ProductModelID
HAVING MAX(p1.ListPrice) >= ALL
(SELECT 2 * AVG(p2.ListPrice)
FROM Production.Product p2
WHERE p1.ProductModelID = p2.ProductModelID) ;
GO
This example uses two correlated subqueries to find the names of employees who have sold a particular product.
USE AdventureWorks ;
GO
SELECT DISTINCT c.LastName, c.FirstName
FROM Person.Contact c JOIN HumanResources.Employee e
ON e.ContactID = c.ContactID WHERE EmployeeID IN
(SELECT SalesPersonID
FROM Sales.SalesOrderHeader
WHERE SalesOrderID IN
(SELECT SalesOrderID
FROM Sales.SalesOrderDetail
WHERE ProductID IN
(SELECT ProductID
FROM Production.Product p
WHERE ProductNumber = 'BK-M68B-42'))) ;
GO
F. Using GROUP BY
The following example finds the total of each sales order in the database.
USE AdventureWorks ;
GO
SELECT SalesOrderID, SUM(LineTotal) AS SubTotal
FROM Sales.SalesOrderDetail sod
GROUP BY SalesOrderID
ORDER BY SalesOrderID ;
GO
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.
Use AdventureWorks
SELECT ProductID, SpecialOfferID, AVG(UnitPrice) AS 'Average Price',
SUM(LineTotal) AS SubTotal
FROM Sales.SalesOrderDetail
GROUP BY ProductID, SpecialOfferID
ORDER BY ProductID
GO
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.
USE AdventureWorks;
GO
SELECT ProductModelID, AVG(ListPrice) AS 'Average List Price'
FROM Production.Product
WHERE ListPrice > $1000
GROUP BY ProductModelID
ORDER BY ProductModelID ;
GO
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.
USE AdventureWorks ;
GO
SELECT AVG(OrderQty) AS 'Average Quantity',
NonDiscountSales = (OrderQty * UnitPrice)
FROM Sales.SalesOrderDetail sod
GROUP BY (OrderQty * UnitPrice)
ORDER BY (OrderQty * UnitPrice) DESC ;
GO
J. Comparing GROUP BY and GROUP BY ALL
The first example that follows produces groups only for orders with quantities > 10.
The second example produces groups for all orders.
The column that holds the aggregate value (the average price) is NULL for groups that lack qualifying rows.
USE AdventureWorks ;
GO
SELECT ProductID, AVG(UnitPrice) AS 'Average Price'
FROM Sales.SalesOrderDetail
WHERE OrderQty > 10
GROUP BY ProductID
ORDER BY ProductID ;
GO
-- Using GROUP BY ALL
USE AdventureWorks ;
GO
SELECT ProductID, AVG(UnitPrice) AS 'Average Price'
FROM Sales.SalesOrderDetail
WHERE OrderQty > 10
GROUP BY ALL ProductID
ORDER BY ProductID ;
GO
K. 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.
USE AdventureWorks ;
GO
SELECT ProductID, AVG(UnitPrice) AS 'Average Price'
FROM Sales.SalesOrderDetail
WHERE OrderQty > 10
GROUP BY ProductID
ORDER BY AVG(UnitPrice) ;
GO
L. 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 AdventureWorks ;
GO
SELECT ProductID
FROM Sales.SalesOrderDetail
GROUP BY ProductID
HAVING AVG(OrderQty) > 5
ORDER BY ProductID ;
GO
This query uses the LIKE clause in the HAVING clause.
USE AdventureWorks ;
GO
SELECT SalesOrderID, CarrierTrackingNumber
FROM Sales.SalesOrderDetail
GROUP BY SalesOrderID, CarrierTrackingNumber
HAVING CarrierTrackingNumber LIKE '4BD%'
ORDER BY SalesOrderID ;
GO
M. 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.
USE AdventureWorks ;
GO
SELECT ProductID
FROM Sales.SalesOrderDetail
WHERE UnitPrice < 25.00
GROUP BY ProductID
HAVING AVG(OrderQty) > 5
ORDER BY ProductID ;
GO
N. 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.
USE AdventureWorks ;
GO
SELECT ProductID, AVG(OrderQty) AS AverageQuantity, SUM(LineTotal) AS Total
FROM Sales.SalesOrderDetail
GROUP BY ProductID
HAVING SUM(LineTotal) > $1000000.00
AND AVG(OrderQty) < 3 ;
GO
To see the products that have had total sales greater than $2000000.00, use this query:
USE AdventureWorks ;
GO
SELECT ProductID, Total = SUM(LineTotal)
FROM Sales.SalesOrderDetail
GROUP BY ProductID
HAVING SUM(LineTotal) > $2000000.00 ;
GO
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:
USE AdventureWorks ;
GO
SELECT ProductID, SUM(LineTotal) AS Total
FROM Sales.SalesOrderDetail
GROUP BY ProductID
HAVING COUNT(*) > 1500 ;
GO
O. Calculating group totals by using COMPUTE BY
The following example uses two code examples to show the use of COMPUTE BY. The first code example uses one COMPUTE BY with one aggregate function, and the second code example uses one COMPUTE BY item and two aggregate functions.
This query calculates the sum of the orders, for products with prices less than $5.00, for each type of product.
USE AdventureWorks ;
GO
SELECT ProductID, LineTotal
FROM Sales.SalesOrderDetail
WHERE UnitPrice < $5.00
ORDER BY ProductID, LineTotal
COMPUTE SUM(LineTotal) BY ProductID ;
GO
This query retrieves the product type and order total for products with unit prices under $5.00. The COMPUTE BY clause uses two different aggregate functions.
USE AdventureWorks ;
GO
SELECT ProductID, LineTotal
FROM Sales.SalesOrderDetail
WHERE UnitPrice < $5.00
ORDER BY ProductID, LineTotal
COMPUTE SUM(LineTotal), MAX(LineTotal) BY ProductID ;
GO
P. Calculating grand values by using COMPUTE without BY
The COMPUTE keyword can be used without BY to generate grand totals, grand counts, and so on.
The following example finds the grand total of the prices and advances for all types of products les than $2.00.
USE AdventureWorks ;
GO
SELECT ProductID, OrderQty, UnitPrice, LineTotal
FROM Sales.SalesOrderDetail
WHERE UnitPrice < $2.00
COMPUTE SUM(OrderQty), SUM(LineTotal) ;
GO
You can use COMPUTE BY and COMPUTE without BY in the same query. The following query finds the sum of order quantities and line totals by product type, and then computes the grand total of order quantities and line totals.
USE AdventureWorks ;
GO
SELECT ProductID, OrderQty, UnitPrice, LineTotal
FROM Sales.SalesOrderDetail
WHERE UnitPrice < $5.00
ORDER BY ProductID
COMPUTE SUM(OrderQty), SUM(LineTotal) BY ProductID
COMPUTE SUM(OrderQty), SUM(LineTotal) ;
GO
Q. Calculating computed sums on all rows
The following example shows only three columns in the select list and gives totals based on all order quantities and all line totals at the end of the results.
USE AdventureWorks ;
GO
SELECT ProductID, OrderQty, LineTotal
FROM Sales.SalesOrderDetail
COMPUTE SUM(OrderQty), SUM(LineTotal) ;
GO
R. Using more than one COMPUTE clause
The following example finds the sum of the prices of all orders whose unit price is less than $5 organized by product ID and order quantity, as well as the sum of the prices of all orders less than $5 organized by product ID only. You can use different aggregate functions in the same statement by including more than one COMPUTE BY clause.
USE AdventureWorks ;
GO
SELECT ProductID, OrderQty, UnitPrice, LineTotal
FROM Sales.SalesOrderDetail
WHERE UnitPrice < $5.00
ORDER BY ProductID, OrderQty, LineTotal
COMPUTE SUM(LineTotal) BY ProductID, OrderQty
COMPUTE SUM(LineTotal) BY ProductID ;
GO
S. Comparing GROUP BY with COMPUTE
The first example that follows uses the COMPUTE clause to calculate the sum of all orders whose product's unit price is less than $5.00, by type of product. The second example produces the same summary information by using only GROUP BY.
USE AdventureWorks ;
GO
SELECT ProductID, LineTotal
FROM Sales.SalesOrderDetail
WHERE UnitPrice < $5.00
ORDER BY ProductID
COMPUTE SUM(LineTotal) BY ProductID ;
GO
This is the second query that uses GROUP BY.
USE AdventureWorks ;
GO
SELECT ProductID, SUM(LineTotal) AS Total
FROM Sales.SalesOrderDetail
WHERE UnitPrice < $5.00
GROUP BY ProductID
ORDER BY ProductID ;
GO
T. Using SELECT with GROUP BY, COMPUTE, and ORDER BY clauses
The following example returns only those orders whose unit price is less than $5, and then computes the line total sum by product and the grand total. All computed columns appear within the select list.
USE AdventureWorks ;
GO
SELECT ProductID, OrderQty, SUM(LineTotal) AS Total
FROM Sales.SalesOrderDetail
WHERE UnitPrice < $5.00
GROUP BY ProductID, OrderQty
ORDER BY ProductID, OrderQty
COMPUTE SUM(SUM(LineTotal)) BY ProductID, OrderQty
COMPUTE SUM(SUM(LineTotal)) ;
GO
U. Using SELECT statement with CUBE
The following example shows two code examples. The first example returns a result set from a SELECT statement by using the CUBE operator. By using the CUBE operator, the statement returns an extra row.
USE AdventureWorks ;
GO
SELECT ProductID, SUM(LineTotal) AS Total
FROM Sales.SalesOrderDetail
WHERE UnitPrice < $5.00
GROUP BY ProductID, OrderQty
WITH CUBE
ORDER BY ProductID ;
GO
NULL represents all values in the ProductID column. The result set returns values for the quantity sold of each product and the total quantity sold of all products. Applying the CUBE operator or ROLLUP operator returns the same result.
The following example uses the CubeExample table to show how the CUBE operator affects the result set and uses an aggregate function (SUM). The CubeExample table contains a product name, a customer name, and the number of orders each customer has made for a particular product.
USE AdventureWorks ;
GO
IF OBJECT_ID ('dbo.CubeExample', 'U') IS NOT NULL
DROP TABLE dbo.CubeExample ;
GO
CREATE TABLE dbo.CubeExample(
ProductName VARCHAR(30) NULL,
CustomerName VARCHAR(30) NULL,
Orders INT NULL
)
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES ('Filo Mix', 'Romero y tomillo', 10)
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES ('Outback Lager', 'Wilman Kala', 10)
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES ('Filo Mix', 'Romero y tomillo', 20)
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES ('Ikura', 'Wilman Kala', 10)
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES ('Ikura', 'Romero y tomillo', 10)
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES ('Outback Lager', 'Wilman Kala', 20)
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES ('Filo Mix', 'Wilman Kala', 30)
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES ('Filo Mix', 'Eastern Connection', 40)
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES ('Outback Lager', 'Eastern Connection', 10)
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES ('Ikura', 'Wilman Kala', 40)
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES ('Ikura', 'Romero y tomillo', 10)
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES ('Filo Mix', 'Romero y tomillo', 50) ;
GO
First, issue a typical query with a GROUP BY clause and the result set.
USE AdventureWorks ;
GO
SELECT ProductName, CustomerName, SUM(Orders)
FROM CubeExample
GROUP BY ProductName, CustomerName
ORDER BY ProductName ;
GO
The GROUP BY causes the result set to form groups within groups.
Here is the result set.
ProductName CustomerName
------------------------------ ------------------------------ -----------
Filo Mix Eastern Connection 40
Filo Mix Romero y tomillo 80
Filo Mix Wilman Kala 30
Ikura Romero y tomillo 20
Ikura Wilman Kala 50
Outback Lager Eastern Connection 10
Outback Lager Wilman Kala 30
(7 row(s) affected)
Next, issue a query with a GROUP BY clause by using the CUBE operator. The result set should include the same information and super-aggregate information for each of the GROUP BY columns.
USE AdventureWorks ;
GO
SELECT ProductName, CustomerName, SUM(Orders)
FROM CubeExample
GROUP BY ProductName, CustomerName
WITH CUBE ;
GO
The result set for the CUBE operator holds the values from the previous simple GROUP BY result set, and adds the super-aggregates for each column in the GROUP BY clause. NULL represents all values in the set from which the aggregate is computed.
Here is the result set.
ProductName CustomerName
------------------------------ ------------------------------ -----------
Filo Mix Eastern Connection 40
Filo Mix Romero y tomillo 80
Filo Mix Wilman Kala 30
Filo Mix NULL 150
Ikura Romero y tomillo 20
Ikura Wilman Kala 50
Ikura NULL 70
Outback Lager Eastern Connection 10
Outback Lager Wilman Kala 30
Outback Lager NULL 40
NULL NULL 260
NULL Eastern Connection 50
NULL Romero y tomillo 100
NULL Wilman Kala 110
(14 row(s) affected)
Line 4 of the result set indicates that a total of 150 orders for Filo Mix were placed for all customers.
Line 11 of the result set indicates that the total number of orders placed for all products by all customers is 260.
Lines 12-14 of the result set indicate that the total numbers of orders for each customer for all products are 100, 110, and 50, respectively.
V. Using CUBE on a result set with three columns
In the following example, the SELECT statement returns the product model ID, product name, and quantity of orders. The GROUP BY clause in this example includes the ProductModelID and Name columns.
By using the CUBE operator, the result set contains more detailed information about the quantities of orders on products and product models. NULL represents all values in the title column.
USE AdventureWorks ;
GO
SELECT ProductModelID, p.Name AS ProductName, SUM(OrderQty)
FROM Production.Product p
INNER JOIN Sales.SalesOrderDetail sod
ON p.ProductID = sod.ProductID
GROUP BY ProductModelID, p.Name
WITH CUBE ;
GO
Increasing the number of columns in the GROUP BY clause shows why the CUBE operator is an n-dimensional operator. A GROUP BY clause with two columns returns three more kinds of groupings when the CUBE operator is used. The number of groupings can be more than three, depending on the distinct values in the columns.
The result set is grouped by the product model ID and then by the product name.
NULL in the ProductModelID column represents all ProductModels. NULL in the Name columns represents all Products. The CUBE operator returns the following groups of information from one SELECT statement:
- Quantity of orders for each product model
- Quantity of orders for each product
- Total number of orders
Each column referenced in the GROUP BY clause has been cross-referenced with all other columns in the GROUP BY clause, and the SUM aggregate has been reapplied. This produces additional rows in the result set. Information returned in the result set grows n-dimensionally along with the number of columns in the GROUP BY clause.
Note
Make sure that the columns that follow the GROUP BY clause have meaningful, real-life relationships with each other. For example, if you use Name and ProductID, the CUBE operator returns irrelevant information. Using the CUBE operator on a real-life hierarchy, such as yearly sales and quarterly sales, produces meaningless rows in the result set. It is more efficient to use the ROLLUP operator.
W. Using the GROUPING function with CUBE
The following example shows how the SELECT statement uses the SUM aggregate, the GROUP BY clause, and the CUBE operator. It also uses the GROUPING function on the two columns that are listed after the GROUP BY clause.
USE AdventureWorks ;
GO
SELECT ProductModelID, GROUPING(ProductModelID), p.Name AS ProductName, GROUPING(p.Name), SUM(OrderQty)
FROM Production.Product p
INNER JOIN Sales.SalesOrderDetail sod
ON p.ProductID = sod.ProductID
GROUP BY ProductModelID, p.Name
WITH CUBE ;
GO
The result set has two columns that contain 0 and 1 values. These are produced by the GROUPING(ProductModelID) and GROUPING(p.Name) expressions.
X. Using the ROLLUP operator
The following example shows two code examples. This first example retrieves the product name, customer name, and the sum of orders placed and uses the ROLLUP operator.
USE AdventureWorks ;
GO
SELECT ProductName, CustomerName, SUM(Orders) AS 'Sum orders'
FROM dbo.CubeExample
GROUP BY ProductName, CustomerName
WITH ROLLUP ;
GO
Here is the result set.
ProductName CustomerName Sum orders
------------------------------ ------------------------------ -----------
Filo Mix Eastern Connection 40
Filo Mix Romero y tomillo 80
Filo Mix Wilman Kala 30
Filo Mix NULL 150
Ikura Romero y tomillo 20
Ikura Wilman Kala 50
Ikura NULL 70
Outback Lager Eastern Connection 10
Outback Lager Wilman Kala 30
Outback Lager NULL 40
NULL NULL 260
(11 row(s) affected)
This second example that follows performs a ROLLUP operation on the company and department columns and totals the number of employees.
The ROLLUP operator produces a summary of aggregates. This is useful when summary information is needed, but a full CUBE provides extraneous data or when you have sets within sets. For example, departments within a company are a set within a set.
USE AdventureWorks ;
GO
IF OBJECT_ID ('dbo.Personnel', 'U') IS NOT NULL
DROP TABLE dbo.Personnel ;
GO
CREATE TABLE dbo.Personnel
(
CompanyName VARCHAR(20) NOT NULL,
Department VARCHAR(15) NOT NULL,
NumEmployees int NOT NULL
)
INSERT dbo.Personnel VALUES ('Du monde entier', 'Finance', 10)
INSERT dbo.Personnel VALUES ('Du monde entier', 'Engineering', 40)
INSERT dbo.Personnel VALUES ('Du monde entier', 'Marketing', 40)
INSERT dbo.Personnel VALUES ('Piccolo und mehr', 'Accounting', 20)
INSERT dbo.Personnel VALUES ('Piccolo und mehr', 'Personnel', 30)
INSERT dbo.Personnel VALUES ('Piccolo und mehr', 'Payroll', 40) ;
GO
In the following query, the company name, department, and the sum of all employees for the company become part of the result set, in addition to the ROLLUP calculations.
USE AdventureWorks ;
GO
SELECT CompanyName, Department, SUM(NumEmployees)
FROM dbo.Personnel
GROUP BY CompanyName, Department WITH ROLLUP ;
GO
Here is the result set.
CompanyName Department
-------------------- --------------- -----------
Du monde entier Engineering 40
Du monde entier Finance 10
Du monde entier Marketing 40
Du monde entier NULL 90
Piccolo und mehr Accounting 20
Piccolo und mehr Payroll 40
Piccolo und mehr Personnel 30
Piccolo und mehr NULL 90
NULL NULL 180
(9 row(s) affected)
Y. Using the GROUPING function
The following example adds three new rows to the CubeExample table. Each of the three records NULL in one or more columns to show only the ROLLUP function produces a value of 1 in the grouping column. Also, this example modifies the SELECT statement that was used in the previous example.
USE AdventureWorks ;
GO
-- Add first row with a NULL customer name and 0 orders.
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES ('Ikura', NULL, 0)
-- Add second row with a NULL product and NULL customer with real value
-- for orders.
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES (NULL, NULL, 50)
-- Add third row with a NULL product, NULL order amount, but a real
-- customer name.
INSERT dbo.CubeExample (ProductName, CustomerName, Orders)
VALUES (NULL, 'Wilman Kala', NULL)
SELECT ProductName AS Prod, CustomerName AS Cust,
SUM(Orders) AS 'Sum Orders',
GROUPING(ProductName) AS 'Group ProductName',
GROUPING(CustomerName) AS 'Group CustomerName'
FROM CubeExample
GROUP BY ProductName, CustomerName
WITH ROLLUP ;
GO
The GROUPING function can be used only with CUBE or ROLLUP. The GROUPING function returns 1 when an expression evaluates to NULL, because the column value is NULL and represents the set of all values. The GROUPING function returns 0 when the corresponding column, whether it is NULL or not, did not come from either the CUBE or ROLLUP options as a syntax value. The returned value has a tinyint data type.
Here is the result set.
Prod Cust Sum Orders Group ProductName Group CustomerName
------------------------------ ------------------------------ ----------- ----------------- ------------------
NULL NULL 50 0 0
NULL Wilman Kala NULL 0 0
NULL NULL 50 0 1
Filo Mix Eastern Connection 40 0 0
Filo Mix Romero y tomillo 80 0 0
Filo Mix Wilman Kala 30 0 0
Filo Mix NULL 150 0 1
Ikura NULL 0 0 0
Ikura Romero y tomillo 20 0 0
Ikura Wilman Kala 50 0 0
Ikura NULL 70 0 1
Outback Lager Eastern Connection 10 0 0
Outback Lager Wilman Kala 30 0 0
Outback Lager NULL 40 0 1
NULL NULL 310 1 1
Warning: Null value is eliminated by an aggregate or other SET operation.
(15 row(s) affected)
Z. Using SELECT with GROUP BY, an aggregate function, and ROLLUP
The following example uses a SELECT query that contains an aggregate function and a GROUP BY clause.
USE AdventureWorks ;
GO
SELECT pm.Name AS ProductModel, p.Name AS ProductName, SUM(OrderQty)
FROM Production.ProductModel pm
INNER JOIN Production.Product p
ON pm.ProductModelID = p.ProductModelID
INNER JOIN Sales.SalesOrderDetail sod
ON p.ProductID = sod.ProductID
GROUP BY pm.Name, p.Name
WITH ROLLUP ;
GO
In the result set, NULL represents all values for that column.
If you use the SELECT statement without the ROLLUP operator, the statement creates a single grouping. The query returns a sum value for each unique combination of ProductModel, ProductModelID, and ProductName:
ProductModel ProductModelID title SUM(qty)
The GROUPING function can be used with the ROLLUP operator or with the CUBE operator. You can apply this function to one of the columns in the select list. The function returns either 1 or 0 depending upon whether the column is grouped by the ROLLUP operator.
a. 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.
-- Use the specifically named INDEX.
USE AdventureWorks ;
GO
SELECT c.FirstName, c.LastName, e.Title
FROM HumanResources.Employee e WITH (INDEX(IX_Employee_ManagerID))
JOIN Person.Contact c on e.ContactID = c.ContactID
WHERE ManagerID = 3 ;
GO
-- Force a table scan by using INDEX = 0.
USE AdventureWorks ;
GO
SELECT c.LastName, c.FirstName, e.Title
FROM HumanResources.Employee e WITH (INDEX = 0) JOIN Person.Contact c
ON e.ContactID = c.ContactID
WHERE LastName = 'Johnson' ;
GO
b. Using OPTION and the GROUP hints
The following example shows how the OPTION (GROUP) clause is used with a GROUP BY clause.
USE AdventureWorks ;
GO
SELECT ProductID, OrderQty, SUM(LineTotal) AS Total
FROM Sales.SalesOrderDetail
WHERE UnitPrice < $5.00
GROUP BY ProductID, OrderQty
ORDER BY ProductID, OrderQty
OPTION (HASH GROUP, FAST 10) ;
GO
c. Using the UNION query hint
The following example uses the MERGE UNION query hint.
USE AdventureWorks ;
GO
SELECT *
FROM HumanResources.Employee e1
UNION
SELECT *
FROM HumanResources.Employee e2
OPTION (MERGE UNION) ;
GO
d. 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.
USE AdventureWorks ;
GO
IF OBJECT_ID ('dbo.Gloves', 'U') IS NOT NULL
DROP TABLE dbo.Gloves ;
GO
-- Create Gloves table.
SELECT ProductModelID, Name
INTO dbo.Gloves
FROM Production.ProductModel
WHERE ProductModelID IN (3, 4) ;
GO
-- Here is the simple union.
USE AdventureWorks ;
GO
SELECT ProductModelID, Name
FROM Production.ProductModel
WHERE ProductModelID NOT IN (3, 4)
UNION
SELECT ProductModelID, Name
FROM dbo.Gloves
ORDER BY Name ;
GO
e. 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.
USE AdventureWorks ;
GO
IF OBJECT_ID ('dbo.ProductResults', 'U') IS NOT NULL
DROP TABLE dbo.ProductResults ;
GO
IF OBJECT_ID ('dbo.Gloves', 'U') IS NOT NULL
DROP TABLE dbo.Gloves ;
GO
-- Create Gloves table.
SELECT ProductModelID, Name
INTO dbo.Gloves
FROM Production.ProductModel
WHERE ProductModelID IN (3, 4) ;
GO
USE AdventureWorks ;
GO
SELECT ProductModelID, Name
INTO ProductResults
FROM Production.ProductModel
WHERE ProductModelID NOT IN (3, 4)
UNION
SELECT ProductModelID, Name
FROM dbo.Gloves ;
GO
SELECT *
FROM dbo.ProductResults ;
f. 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.
USE AdventureWorks ;
GO
IF OBJECT_ID ('dbo.Gloves', 'U') IS NOT NULL
DROP TABLE dbo.Gloves ;
GO
-- Create Gloves table.
SELECT ProductModelID, Name
INTO dbo.Gloves
FROM Production.ProductModel
WHERE ProductModelID IN (3, 4) ;
GO
/* INCORRECT */
USE AdventureWorks ;
GO
SELECT ProductModelID, Name
FROM Production.ProductModel
WHERE ProductModelID NOT IN (3, 4)
ORDER BY Name
UNION
SELECT ProductModelID, Name
FROM dbo.Gloves ;
GO
/* CORRECT */
USE AdventureWorks ;
GO
SELECT ProductModelID, Name
FROM Production.ProductModel
WHERE ProductModelID NOT IN (3, 4)
UNION
SELECT ProductModelID, Name
FROM dbo.Gloves
ORDER BY Name ;
GO
g. 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.
USE AdventureWorks ;
GO
IF OBJECT_ID ('EmployeeOne', 'U') IS NOT NULL
DROP TABLE EmployeeOne ;
GO
IF OBJECT_ID ('EmployeeTwo', 'U') IS NOT NULL
DROP TABLE EmployeeTwo ;
GO
IF OBJECT_ID ('EmployeeThree', 'U') IS NOT NULL
DROP TABLE EmployeeThree ;
GO
SELECT c.LastName, c.FirstName, e.Title
INTO EmployeeOne
FROM Person.Contact c JOIN HumanResources.Employee e
ON e.ContactID = c.ContactID
WHERE ManagerID = 66 ;
GO
SELECT c.LastName, c.FirstName, e.Title
INTO EmployeeTwo
FROM Person.Contact c JOIN HumanResources.Employee e
ON e.ContactID = c.ContactID
WHERE ManagerID = 66 ;
GO
SELECT c.LastName, c.FirstName, e.Title
INTO EmployeeThree
FROM Person.Contact c JOIN HumanResources.Employee e
ON e.ContactID = c.ContactID
WHERE ManagerID = 66 ;
GO
-- Union ALL
SELECT LastName, FirstName
FROM EmployeeOne
UNION ALL
SELECT LastName, FirstName
FROM EmployeeTwo
UNION ALL
SELECT LastName, FirstName
FROM EmployeeThree ;
GO
SELECT LastName, FirstName
FROM EmployeeOne
UNION
SELECT LastName, FirstName
FROM EmployeeTwo
UNION
SELECT LastName, FirstName
FROM EmployeeThree ;
GO
SELECT LastName, FirstName
FROM EmployeeOne
UNION ALL
(
SELECT LastName, FirstName
FROM EmployeeTwo
UNION
SELECT LastName, FirstName
FROM EmployeeThree
) ;
GO
See Also
Reference
CREATE TRIGGER (Transact-SQL)
CREATE VIEW (Transact-SQL)
DELETE (Transact-SQL)
EXECUTE (Transact-SQL)
Expressions (Transact-SQL)
INSERT (Transact-SQL)
LIKE (Transact-SQL)
UNION (Transact-SQL)
EXCEPT and INTERSECT (Transact-SQL)
UPDATE (Transact-SQL)
WHERE (Transact-SQL)
Other Resources
Distributed Queries
Subquery Fundamentals
Using Variables and Parameters (Database Engine)
Help and Information
Getting SQL Server 2005 Assistance
Change History
| Release | History |
|---|---|
14 April 2006 |
|