Friday 27 April 2012

Introduction to Transact SQL User-Defined Functions


Introduction

SQL Server 2000 supports User-Defined Functions (UDFs) - one or more Transact-SQL statements that can be used to encapsulate code for reuse. User-defined functions cannot make a permanent changes to the data or modify database tables. UDF can change only local objects for this UDF, such as local cursors or variables. 


There are three types of UDF in SQL Server 2000:

  • Scalar functions
  • Inline table-valued functions
  • Multistatement table-valued functions
  •  
    Scalar functions return a single data value (not a table) with RETURNS clause. Scalar functions can use all scalar data types, with exception of timestamp and user-defined data types.
     
    Inline table-valued functions return the result set of a single SELECT statement.
     
    Multistatement table-valued functions return a table, that was built with many TRANSACT-SQL statements.
    User-defined functions can be invoked from a query like built-in functions such as OBJECT_ID, LEN, DATEDIFF, or can be executed through an EXECUTE statement like stored procedures.



    1 . Scalar Functions
     
    Scalar functions return a data type such as int, money, varchar, real, etc. They can be used anywhere a built-in SQL function is allowed. The syntax for a scalar function is the following:

    1. CREATE FUNCTION [owner_name.] function_name
    2. ( [{ @parameter_name scalar_parameter_type [ = default]} [,..n]])
    3. RETURNS scalar_return_type
    4. [WITH <function_option> >::={SCHEMABINDING | ENCRYPTION]
    5. [AS]
    6. BEGIN
    7. function_body
    8. RETURN scalar_expression
    9. END
    10. A simple scalar function to cube a number would look like this:
    11. CREATE FUNCTION dbo.Cube( @fNumber float)
    12. RETURNS float
    13. AS
    14. BEGIN
    15. RETURN(@fNumber * @fNumber * @fNumber)
    16. END
    17. Surprisingly, user-defined functions (UDFs) support recursion. Here is an
    18. SQL Server 2000 UDF using the standard factorial example:
    19. CREATE FUNCTION dbo.Factorial ( @iNumber int )
    20. RETURNS INT
    21. AS
    22. BEGIN
    23. DECLARE @i int
    24. IF @iNumber <= 1
    25. SET @i = 1
    26. ELSE
    27. SET @i = @iNumber * dbo.Factorial( @iNumber - 1 )
    28. RETURN (@i)
    29. END
    30.  
    31.  


    On Other Example 


    The following scalar function returns a maximum amount of books sold for a specified title. This function should be executed in pubs database. If the title has no sales, the UDF will return zero.
    /* scalar function to return max amount of books sold
    ** for the specified title_id
    */

    CREATE FUNCTION dbo.udf_max_copies_sold_for_title (@title_id CHAR(6))
    RETURNS INT
    AS
    BEGIN

    DECLARE @qty INT
    -- initialize the variable at 0:
    SELECT @qty = 0
    
    SELECT 
        @qty = MAX(qty) 
    FROM sales 
    WHERE
    title_id = @title_id
    
    /* If there are no books sold for title_id specified 
    ** then return 0:
    */
    RETURN ISNULL(@qty, 0)
    
    END
     
    Now we can execute this function as follows:
    SELECT dbo.udf_max_copies_sold_for_title ('bu2075')

    Results:
    ----------- 
    55
     
     
    2. In-Line Table Functions

    In-line table functions are functions that return the output of a single SELECT statement as a table data type. Since this type of function returns a table, the output can be used in joins of queries as if it was a standard table. The syntax for an in-line table function is as follows:

    1. CREATE FUNCTION [owner_name.] function_name
    2. ( [{ @parameter_name scalar_parameter_type [ = default]} [,..n]])
    3. RETURNS TABLE
    4. [WITH <function_option>::={SCHEMABINDING | ENCRYPTION}]
    5. RETURN [(] select_statement [)]
    6. An in-line function to return the authors from a particular state would
    7. look like this:
    8. CREATE FUNCTION dbo.AuthorsForState(@cState char(2) )
    9. RETURNS TABLE
    10. AS
    11. RETURN (SELECT * FROM Authors WHERE state = @cState)
    Other Example

    The following in-line function returns the product name, quantity ordered, and supplier for the top five best sellers in a particular year in the Northwind database:
     
    /* in-line function to return quantity, product name and supplier
    ** for the top 5 best-selling products within the specified year
    */
    
    CREATE FUNCTION dbo.udf_top_5_best_sellers (@year INT)
    RETURNS TABLE
    AS
    RETURN
    
    SELECT TOP 5 
         SUM(quantity) AS quantity_ordered, 
         a.ProductID, 
         ProductName, 
         CompanyName AS Supplier
    FROM [order details] a INNER JOIN products b
       ON a.productid = b.productid
       INNER JOIN suppliers c ON c.supplierid = b.supplierid
       INNER JOIN orders d ON d.orderid = a.orderid
          AND DATEPART(YEAR, OrderDate) = @year
    GROUP BY a.productid, productname, CompanyName
    ORDER BY 1 DESC

    We can execute this function as follows:
     
    SELECT * FROM dbo.udf_top_5_best_sellers (1998)

    Results:
    quantity_ordered
    ProductID
    ProductName
    Supplier
    659
    13
    Konbu
    Mayumi's
    546
    24
    Guaraná Fantástica
    Refrescos Americanas LTDA
    542
    60
    Camembert Pierrot
    Gai pturage
    513
    59
    Raclette Courdavault
    Gai pturage
    414
    7
    Uncle Bob's Organic Dried Pears
    Grandma Kelly's Homestead

    Alternatively, we can SELECT only the desired columns from this function:
     
    SELECT ProductID, 
            ProductName 
    FROM dbo.udf_top_5_best_sellers (1998)

    Results:
    ProductID
    ProductName
    13
    Konbu
    24
    Guaraná Fantástica
    60
    Camembert Pierrot
    59
    Raclette Courdavault
    7
    Uncle Bob's Organic Dried Pears





    3. Multistatement Table Functions
      Multistatement table functions are similar to stored procedures except that they return a table. This type of function is suited to address situations where more logic is required than can be expressed in a single query. The following is the syntax for a multistatement table function:
    1. CREATE FUNCTION [owner_name.] function_name
    2. ( [{ @parameter_name scalar_parameter_type [ = default]} [,..n]])
    3. RETURNS TABLE
    4. [WITH <function_option> >::={SCHEMABINDING | ENCRYPTION]
    5. [AS]
    6. BEGIN
    7. function_body
    8. RETURN
    9. END
    10.  
    Hierarchical data, such as an organizational structure, is an example of data that cannot be gathered in a single query. The Northwind Company database's Employees table contains a field called ReportsTo that contains the EmployeeID of the employee's manager. GetManagerReports is a multistatement table function that returns a list of the employees who report to a specific employee, either directly or indirectly.

    1. CREATE FUNCTION dbo.GetManagerReports ( @iEmployeeID int )
    2. RETURNS @ManagerReports TABLE
    3. (
    4. EmployeeID int,
    5. EmployeeFirstName nvarchar(10),
    6. EmployeeLastName nvarchar(20),
    7. Title nvarchar(30),
    8. TitleOfCourtesy nvarchar(25),
    9. Extension nvarchar(4),
    10. ManagerID int
    11. )
    12. AS
    13. BEGIN
    14. DECLARE
    15. @iRowsAdded int, -- Counts rows added to
    16. -- table with each iteration
    17. @PREPROCESSED tinyint, -- Constant
    18. for record prior
    19. -- to processing
    20. @PROCESSING tinyint, -- Constant
    21. for record
    22. -- being processed
    23. @POSTPROCESSED tinyint -- Constant for
    24. records that
    25. -- have been processed
    26. SET @PREPROCESSED = 0
    27. SET @PROCESSING = 1
    28. SET @POSTPROCESSED = 2
    29. DECLARE @tblReports TABLE (
    30. -- Holds employees added with each pass thru source employees table
    31. EmployeeID int,
    32. EmployeeFirstName nvarchar(10),
    33. EmployeeLastName nvarchar(20),
    34. Title nvarchar(30),
    35. TitleOfCourtesy nvarchar(25),
    36. Extension nvarchar(4),
    37. ManagerID int,
    38. ProcessedState tinyint
    39. DEFAULT 0
    40. )
    41. --Begin by adding employees who report to the Manager directly.
    42. INSERT INTO @tblReports
    43. SELECT EmployeeID, FirstName, LastName, Title, TitleOfCourtesy,
    44. Extension, ReportsTo, @PREPROCESSED
    45. FROM Employees
    46. WHERE ReportsTo = @iEmployeeID
    47. --Save number of direct reports
    48. SET @iRowsAdded = @@ROWCOUNT
    49. -- Loop through Employees table until no more iterations are necessary
    50. -- (e.g., no more rows added) to add all indirect reports.
    51. WHILE @iRowsAdded > 0
    52. BEGIN
    53. --Set just added employees ProcessedState to PROCESSING
    54. -- (for first pass)
    55. UPDATE @tblReports
    56. SET ProcessedState = @PROCESSING
    57. WHERE ProcessedState = @PREPROCESSED
    58. --Add employees who report to Managers in
    59. -- ProcessedState = PROCESSING
    60. INSERT INTO @tblReports
    61. SELECT e.EmployeeID, e.FirstName, e.LastName, e.Title,
    62. e.TitleOfCourtesy, e.Extension, e.ReportsTo, @PREPROCESSED
    63. FROM Employees e
    64. INNER JOIN @tblReports r ON e.ReportsTo = r.EmployeeID
    65. WHERE r.ProcessedState = @PROCESSING
    66. AND e.ReportsTo <> @iEmployeeID
    67. --Save number of rows added for this iteration
    68. SET @iRowsAdded = @@ROWCOUNT
    69. --Set ProcessedState to POSTPROCESSED for Managers whose
    70. --reports were added in this iteration
    71. UPDATE @tblReports
    72. SET ProcessedState = @POSTPROCESSED
    73. WHERE ProcessedState = @PROCESSING
    74. END
    75. --Save all data to output table
    76. INSERT INTO @ManagerReports
    77. SELECT EmployeeID, EmployeeFirstName, EmployeeLastName, Title,
    78. TitleOfCourtesy, Extension, ManagerID
    79. FROM @tblReports
    80. RETURN
    81. END
    82.  
    The output of this function would be used in the same manner as a standard table. Figure 1 demonstrates JOINING the output of GetManagerReports with the Employees table to produce a listing of the organizational structure of the Northwind Company:
    User function used in JOIN query
    Figure 1: User function used in JOIN query.



    Other Example


    The following multi-statement function accepts a delimited list as a parameter parses the string and returns the table containing each of the values in the parameter.
     
    /* multi-statement function to parse
    ** a delimited list and turn it into a rowset
    ** DEFAULT delimiter is comma
    */
    
    CREATE FUNCTION dbo.parse_comma_delimited_integer(
        @list    VARCHAR(8000), 
        @delimiter VARCHAR(10) = ',')
    
    -- table variable that will contain values
    RETURNS @tablevalues TABLE (
        item INT)
    AS
    BEGIN 
      DECLARE @item VARCHAR(255)
     
      /* Loop over the commadelimited list */
      WHILE (DATALENGTH(@list) > 0)
        BEGIN 
          IF CHARINDEX(@delimiter,@list) > 0
            BEGIN
              SELECT @item =
                 SUBSTRING(@list,1,(CHARINDEX(@delimiter, @list)-1))
              SELECT @list =
                    SUBSTRING(@list,(CHARINDEX(@delimiter, @list) +
                    DATALENGTH(@delimiter)),DATALENGTH(@list))
            END
    
         ELSE
            BEGIN
              SELECT @item = @list
              SELECT @list = NULL
            END
     
       -- Insert each item into temp table
        INSERT @tablevalues (
            item)
        SELECT item = CONVERT(INT, @item) 
       END
    
     RETURN
    END

    Now we can execute this function as follows:
    SELECT * FROM dbo.parse_comma_delimited_integer 
    ('39, 549, 324, 3556, 24, 2132, 345', ',')

    Results

    item
    39
    549
    324
    3556
    24
    2132
    345

    The following multi-statement UDF written for the Northwind database finds customers who have bought products in large quantities during a given year. The UDF accepts the year and amount of total sales and returns the customer name, the product that they have bought in large quantities, and all sales representatives who interfaced with these customers within the given year: 


    CREATE FUNCTION dbo.udf_top_customers_and_reps (
      @year INT, 
      @amount INT)
    
    RETURNS 
      @temp TABLE(
        ProductName VARCHAR(200), 
        CategoryName VARCHAR(200),
        CustomerID CHAR(5),
        CompanyName VARCHAR(200),
        TotalSales INT, 
        EmployeeNames VARCHAR(2000))
    
    AS 
    BEGIN
    
    /* populate the temp table with customers that have purchased any product 
    * with total sales greater than the specified amount, within the given year
    */
    
    INSERT @temp (
         ProductName ,
         CategoryName ,
         CompanyName ,
         CustomerID ,
         TotalSales 
    )
    
    
    SELECT 
        ProductName, 
        CategoryName, 
        CompanyName, 
        b.CustomerID, 
        SUM(a.UnitPrice * quantity) AS total_sales 
    FROM [order details] a 
    INNER JOIN orders b ON a.orderid = b.orderid
    INNER JOIN products c ON c.productid = a.productid
    INNER JOIN customers d ON d.customerid = b.customerid
    INNER JOIN categories e ON e.CategoryID = c.CategoryID
    WHERE DATEPART(YEAR, OrderDate) = @year
    GROUP BY c.ProductName, e.CategoryName, b.CustomerID, 
    d.CompanyName, DATEPART(YEAR, OrderDate) 
    HAVING SUM(a.UnitPrice * quantity) > @amount
    ORDER BY ProductName
    
    /* now get all the employees that have been involved with the customers
    * in the given year and return them in a comma-delimited list
    */
    
    
    DECLARE @CustomerID CHAR(5), 
        @EmployeeName VARCHAR(200)
    
    DECLARE @Employees TABLE (
     EmployeeName VARCHAR(80))
    
    DECLARE CustomerCursor CURSOR FOR
    SELECT CustomerID
    FROM @temp a 
    
    OPEN CustomerCursor
    FETCH NEXT FROM CustomerCursor INTO @CustomerID
    
    WHILE @@FETCH_STATUS = 0
    BEGIN
    
    INSERT @employees
    SELECT DISTINCT FirstName + ' ' + LastName 
     FROM Employees a INNER JOIN Orders b ON a.EmployeeID = b.EmployeeID
     AND DATEPART(YEAR,OrderDate) = @year
     WHERE b.CustomerID = @CustomerID
    
    
    /* create a comma-delimited list of employees */
    
    SELECT @EmployeeName = ''
     SELECT @EmployeeName = @EmployeeName + ', ' + EmployeeName
     FROM @Employees 
    
    SELECT @EmployeeName = SUBSTRING(@EmployeeName, 3, LEN(@EmployeeName)-2)
    
    
    
    UPDATE @temp
    SET EmployeeNames = @EmployeeName
    WHERE CustomerID = @CustomerID
    
    DELETE @Employees
    FETCH NEXT FROM CustomerCursor INTO @CustomerID
    END
    CLOSE CustomerCursor
    DEALLOCATE CustomerCursor
    
    
    RETURN
    END
    The following execution of the function returns customers who have bought any product in amounts of over $10,000 during 1997:
    SELECT * FROM dbo.udf_top_customers_and_reps (1997, 10000)
     
    Results



    ProductName
    CategoryName
    CustomerID
    Companyname
    TotalSales
    EmployeeNames
    Côte de Blaye
    Beverages
    MEREP
    Mère Paillarde
    10329
    Janet Leverling, Laura Callahan, Margaret Peacock, Michael Suyama, Nancy Davolio, Robert King
    Côte de Blaye
    Beverages
    SIMOB
    Simons bistro
    10540
    Andrew Fuller, Margaret Peacock, Robert King

     
    Invoking Functions


    There are a few syntax idiosyncrasies to observe when invoking user-defined functions. SQL Server 2000 provides some system-level user-defined functions in the Master database. These system functions are invoked with a slightly different syntax than ones that you would create. System functions that return a table have the following syntax:

    1.  
    2. ::function_name ([argument_expr], [,...])
    3. System functions that return a scalar value use this syntax:
    4. function_name ([argument_expr], [,...])
    5. User-created scalar and rowset functions are invoked in exactly the same
    6. manner. The syntax for invoking a user-created function looks like this:
    7. [database_name] owner_name. function_name ([argument_expr], [,...])
    8.  

    Limitations


     User-defined functions do have some restrictions placed upon them. Not every SQL statement or operation is valid within a function. The following lists enumerate the valid and invalid function operations: Valid:
    • Assignment statements
    • Control-flow statements
    • Variable declarations
    • SELECT statements that modify local variables
    • Cursor operations that fetch into local variables
    • INSERT, UPDATE, DELETE statement that act upon local table variables
    Invalid:
    • Built-in, nondeterministic functions such as GetDate()
    • Statements that update, insert, or delete tables or views
    • Cursor fetch operations that return data to the client

    Performance Implications

    Using UDFs will impact the performance of queries. The extent of the performance impact depends upon how and where you use a user-defined function. This is also true of built-in functions. However, UDFs have the potential for more dramatic performance hits than built-in functions. You should exercise caution when implementing functions in your queries and perform benchmarking tests to insure that the benefits of using your functions exceed the performance costs of using them.

    Uses for Functions


    Check constraints
     
    Scalar user-defined functions can be used as check constraints for columns in table definitions. As long as an argument to the function is a constant or built-in function or an argument is the column being checked, the function may be used to validate the column's value. These UDF check constraints provide the ability to use more complex logic for determining acceptable column values than Boolean expressions or LIKE patterns would allow.
    The following function validates that a serial number follows a specific pattern and portions of the serial number match a specific algorithm for a product type.

    
    CREATE FUNCTION dbo.ValidSerialNumber( @nvcSerialNumber nvarchar(50))
    RETURNS BIT
    AS
    BEGIN
    
    DECLARE
    @bValid  BIT,
     @iNumber  INT
    
     --default to invalid serial number
     SET @bValid = 0
    
     --Home Office Product
     IF @nvcSerialNumber LIKE
    '[0-9][A-Z][0-9][A-Z][0-9][0-9][0-9][0-9]'
     BEGIN
      SET @iNumber = CONVERT(int,RIGHT(@nvcSerialNumber,4))
      IF @iNumber % 7 = 2
      BEGIN
       SET @bValid = 1
      END
     END
    
     -- Video Game
     IF @nvcSerialNumber LIKE '[0-9][0-9][0-9][A-Z][0-9]5[A-Z]'
    
     BEGIN
      SET @iNumber = CONVERT(int,LEFT(@nvcSerialNumber, 3))
      IF @iNumber % 2 = 0
      BEGIN
       SET @bValid = 1
      END
     END
    
    RETURN ( @bValid)
    END
    
    CREATE TABLE dbo.CustomerProduct
    (
     CustomerID  int  NOT NULL PRIMARY KEY,
     ProductID  int  NOT NULL,
     SerialNumber  nvarchar(20) NOT NULL
     CHECK(dbo.ValidSerialNumber(SerialNumber) = 1)
    )
    
    
    Computed columns
     
    Scalar functions can be used to compute column values in table definitions. Arguments to computed column functions must be table columns, constants, or built-in functions. This example shows a table that uses a Volume function to compute the volume of a container:

    
    
    CREATE FUNCTION dbo.Volume (   @dHeight  decimal(5,2),
    @dLength  decimal(5,2),
    @dWidth decimal(5,2) )
    RETURNS decimal (15,4)
    AS
    BEGIN
     RETURN (@dHeight * @dLength * @dWidth )
    END
    
    
    CREATE TABLE dbo.Container
    (
     ContainerID  int  NOT NULL
     PRIMARY KEY,
     MaterialID  int  NOT NULL
    REFERENCES Material(MaterialID),
     ManufacturerID  int  NOT NULL
          REFERENCES
    Manufacturer(ManufacturerID)
     Height   decimal(5,2) NOT NULL,
     Length   decimal(5,2) NOT NULL,
     Width   decimal(5,2)  NOT NULL,
     Volume AS
      (
       dbo.Volume( Height, Length, Width )
      )
    )
    
    
    You should note that computed columns might be excluded from being indexed if user-defined functions determine their value. An index can be created on the computed column if the user-defined function is deterministic (e.g., always returns the same value given the same input). 

    Default constraints

    Default column values can be set with user-defined functions. UDFs can be very useful when a hard-coded value or built-in function does not suffice. For example, if a doctor's office wished to save a patient's appointment preference, a user-defined function could calculate the default day and time in a function by using the current date/time when the patient's record was created. If the patient's record were created on a Friday at 10:34 AM the AppointmentPref column would default to "Friday at 10:00" using the following function:

    
    CREATE FUNCTION dbo.AppointmentPreference ( @dtDefaultDateTime datetime )
    RETURNS nvarchar(50)
    AS
    BEGIN
    
    DECLARE @nDay   nvarchar(10),
     @nHour  nvarchar(6),
     @nPreference  nvarchar(50),
     @tiHour  tinyint
    
     --Get date description
     SET @nDay = DATENAME(dw, @dtDefaultDateTime )
    
     --Find current hour
     SET @tiHour = DATEPART(hh,@dtDefaultDateTime)
    
     --Use only 12-hour times
     IF @tiHour > 12
     BEGIN
      SET @tiHour = @tiHour - 12
     END
    
     --Don't allow appointments during lunch
     IF @tiHour = 12
     BEGIN
      SET @tiHour = 1
     END
    
     -- These are invalid hours
     IF @tiHour IN(5,6,7,8)
     BEGIN
      SET @tiHour = 4
     END
    
     --Create preference text
     SET @nPreference = RTRIM(@nDay) + '''s at ' +
    CONVERT(varchar(2),@tiHour) + ':00'
     RETURN ( @nPreference)
    END
    
    
    CREATE TABLE dbo.Patient
    (
     PatientID  int  NOT NULL PRIMARY KEY
          IDENTITY,
     FirstName  nvarchar(20) NOT NULL,
     LastName  nvarchar(20) NOT NULL,
     Addr1   nvarchar(50),
     Addr2   nvarchar(50),
     City   nvarchar(50),
     State   nvarchar(2),
     ZipCode  nvarchar(20),
     HomePhone  nvarchar(20),
     WorkPhone  nvarchar(20),
    AppointmentPref nvarchar(50)
    DEFAULT (dbo.AppointmentPreference(GETDATE()))
    
    )
    
    
    
    
    Assignments
     
    Scalar user-defined functions can be used to assign values to scalar variables. They may be used in any situation where a scalar built-in function may be used.

    
    
    DECLARE @fCube  float
    
    SET @fCube = dbo.Cube( 4.5 )
    
    
    
    Control flow
    Scalar user-defined functions may be used to control program flow when used in Boolean expressions.

    
    
    IF dbo.ValidSerialNumber('002A15A') = 1
     PRINT 'Yes'
    
    ELSE
     PRINT 'No'
    
    
    Case expressions
    User-defined functions that return a scalar value can be used in any of the cases of CASE expressions. The following example uses the DailySpecial function in a case function to determine what to display for a given day:

    
    
    CREATE FUNCTION dbo.DailySpecial( @nvcDay nvarchar(10))
    RETURNS NVARCHAR(100)
    AS
    BEGIN
    
    DECLARE @nvcSpecial nvarchar(100)
    
     SET @nvcDay = UPPER(@nvcDay)
    
     IF @nvcDay = 'SUNDAY'
      SET @nvcSpecial = 'Roast beef with green beans and
    baked potato'
    
     IF @nvcDay = 'MONDAY'
      SET @nvcSpecial = 'Chopped beef with green bean
    casserole'
    
     IF @nvcDay = 'TUESDAY'
      SET @nvcSpecial = 'Beef stew'
    
     IF @nvcDay = 'WEDNESDAY'
      SET @nvcSpecial = 'Beef pot pie'
    
     IF @nvcDay = 'THURSDAY' OR @nvcDay = 'FRIDAY'
      OR @nvcDay = 'SATURDAY'
      SET @nvcSpecial = 'Beef surprise'
    
    RETURN ( @nvcSpecial )
    END
    
    
    --Use output of DailySpecial function
    SELECT   Special =
        CASE DateName(dw, getdate())
    WHEN 'Sunday' THEN dbo.DailySpecial('Sunday')
             WHEN 'Monday' THEN
    dbo.DailySpecial('Monday')
              WHEN 'Tuesday' THEN
    dbo.DailySpecial('Tuesday')
     WHEN 'Wednesday' THEN dbo.DailySpecial('Wednesday')
             ELSE 'It's a mystery!'
    
          END
    
    
    Alternative to views
    Rowset functions, functions that return tables, can be used as alternatives to read-only views. Since views are limited to a single select statement, user-defined functions can provide greater functionality than a view. Powerful logic can be used when determining the records returned, which is not possible within a view. Also, views cannot accept parameters so a separate view must be created if the WHERE clause must change for different search c riteria.
    Alternative to temporary tables Rowset functions can be used as alternatives to temporary tables. For example, if you wished to find authors in the Pubs database who sold no books in a particular state, you could create a couple of functions that would generate the desired resultset.
    To find the quantity of books sold for a particular author in a given state you could write the following function:

    
    
    CREATE FUNCTION dbo.AuthorPoularityForState ( @cState Char(2))
    RETURNS  TABLE
    
    AS
    RETURN (
            SELECT a.au_id, a.au_fname, a.au_lname,
                   SUM(s.qty) AS QTY
            FROM Authors a
      INNER JOIN TitleAuthor ta ON a.au_id = ta.au_id
      INNER JOIN Titles t ON t.title_id = ta.title_id
      INNER JOIN Sales s ON s.title_id = t.title_id
      INNER JOIN Stores st ON st.Stor_ID = s.stor_id
     WHERE  st.state = @cState
     GROUP BY a.au_id, a.au_fname, a.au_lname
     ORDER BY QTY DESC, a.au_lname, a.au_fname
       )
    END
    
    
    You could then create another function that would use the output from the first function to find the authors in a particular state that have not had any sales:

    
    
    CREATE FUNCTION dbo.ReallyBoringAuthorsForState ( @cState Char(2) )
    RETURNS TABLE
    
    RETURN(
    SELECT a.au_id as AuthorID, a.au_fname AS AuthorFirstName,
     a.au_lname AS AuthorLastName, @cState AS State
     FROM AuthorPopularityForState(@cState ) pa
     RIGHT JOIN authors a ON pa.AuthorID = a.au_id
     WHERE IsNull(pa.UnitsSold, 0) = 0
    
    )
    
    
    The following SQL statement would list the California authors who had not sold any books:
    
    
    SELECT AuthorLastName, AuthorFirstName, AuthorID
     FROM ReallyBoringAuthorsForState('CA')
    ORDER BY AuthorLastName, AuthorFirstName
    
    
    List of authors without book sales
      List of authors without book sales

    Before the release of SQL Server 2000, temporary tables would likely have been used to generate the interim data to be used for the final query output. By using functions instead of temporary tables, potential table name concurrency problems are avoided. Functions also offer greater code reuse than temporary tables.



















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