Microsoft SQL Server 2008 R2 Unleashed- P163 ppt

The bits in the bitmap indicate whether the columns are being aggregated in the grouping set bit value is 1 or if the column is used to determine the grouping set bit value is 0 used to

Listing 42.3 demonstrates how to use the GROUPING SETSoperator to perform three

group-ings on three individual columns in a single query.

LISTING 42.3 GROUPING SETS Example

/***

** Perform a grouping by type, grouping by pub_id, and grouping by price

***/

SELECT type, pub_id, price, sum(isnull(ytd_sales, 0)) AS ytd_sales

FROM titles

where pub_id < ‘9’

GROUP BY GROUPING SETS ( type, pub_id, price)

go

type pub_id price ytd_sales

- - -

-NULL -NULL -NULL 0

NULL NULL 0.0006 111

NULL NULL 0.0017 750

NULL NULL 14.3279 4095

NULL NULL 14.595 18972

NULL NULL 14.9532 14294

NULL NULL 14.9611 4095

NULL NULL 15.894 40968

NULL NULL 15.9329 3336

NULL NULL 17.0884 2045

NULL NULL 17.1675 8780

NULL 0736 NULL 28286

NULL 0877 NULL 44219

NULL 1389 NULL 24941

business NULL NULL 30788

mod_cook NULL NULL 24278

popular_comp NULL NULL 12875

psychology NULL NULL 9939

trad_cook NULL NULL 19566

In the output in Listing 42.3, the first 11 rows are the results grouped by price, the next 3

rows are grouped by pub_id, and the bottom 5 rows are grouped by type Now, you can

modify this query to include a super-aggregate for all rows by adding a null field list, as

shown in Listing 42.4.

LISTING 42.4 GROUPING SETS Example with Null Field List to Generate Super-Aggregate

SELECT type, pub_id, price, sum(isnull(ytd_sales, 0)) AS ytd_sales

FROM titles

where pub_id < ‘9’

GROUP BY GROUPING SETS ( type, pub_id, price, () )

go

type pub_id price ytd_sales

- - -

-NULL -NULL -NULL 0

NULL NULL 0.0006 111

NULL NULL 0.0017 750

NULL NULL 14.3279 4095

NULL NULL 14.595 18972

NULL NULL 14.9532 14294

NULL NULL 14.9611 4095

NULL NULL 15.894 40968

NULL NULL 15.9329 3336

NULL NULL 17.0884 2045

NULL NULL 17.1675 8780

NULL NULL NULL 97446

NULL 0736 NULL 28286

NULL 0877 NULL 44219

NULL 1389 NULL 24941

business NULL NULL 30788

mod_cook NULL NULL 24278

popular_comp NULL NULL 12875

psychology NULL NULL 9939

trad_cook NULL NULL 19566

If you look closely at the results in Listing 42.4, you see there are two rows withNULLvalues

for all three columns fortype,pub_id, andprice How can you determine definitively

which row is the super-aggregate of all three rows, and which is a row grouped by price

where the value ofpriceisNULL? This is where the newgrouping_id()function comes in.

The grouping_id() Function

Thegrouping_id()function, new in SQL Server 2008, can be used to determine the level

of grouping in a query using GROUPING SETSor the CUBEandROLLUPoperators Unlike the

GROUPING()function, which takes only a single column expression as an argument and

returns a 1or0to indicate whether that individual column is being aggregated, the

grouping_id()function accepts multiple column expressions and returns a bitmap to

indicate which columns are being aggregated for that row.

For example, you can add the grouping_id()andgrouping()functions to the query in

Listing 42.4 and examine the results (see Listing 42.5).

LISTING 42.5 Using the grouping_id() Function

SELECT type, pub_id, price, sum(isnull(ytd_sales, 0)) AS ytd_sales,

grouping_id(type, pub_id, price) as grping_id,

grouping(type) type_rlp,

grouping(pub_id) pub_id_rlp,

grouping(price) price_rlp

FROM titles

where pub_id < ‘9’

GROUP BY GROUPING SETS ( type, pub_id, price, () )

go

type pub_id price ytd_sales grping_id type_rlp pub_id_rlp price_rlp

- - - - -

-NULL -NULL -NULL 0 6 1 1 0

NULL NULL 0.0006 111 6 1 1 0

NULL NULL 0.0017 750 6 1 1 0

NULL NULL 14.3279 4095 6 1 1 0

NULL NULL 14.595 18972 6 1 1 0

NULL NULL 14.9532 14294 6 1 1 0

NULL NULL 14.9611 4095 6 1 1 0

NULL NULL 15.894 40968 6 1 1 0

NULL NULL 15.9329 3336 6 1 1 0

NULL NULL 17.0884 2045 6 1 1 0

NULL NULL 17.1675 8780 6 1 1 0

NULL NULL NULL 97446 7 1 1 1

NULL 0736 NULL 28286 5 1 0 1

NULL 0877 NULL 44219 5 1 0 1

NULL 1389 NULL 24941 5 1 0 1

business NULL NULL 30788 3 0 1 1

mod_cook NULL NULL 24278 3 0 1 1

popular_comp NULL NULL 12875 3 0 1 1

psychology NULL NULL 9939 3 0 1 1

trad_cook NULL NULL 19566 3 0 1 1

Unlike the grouping()function, which takes only a single column name as an argument,

thegrouping_id()function accepts all columns that participate in any grouping set The

grouping_id()function produces an integer result that is a bitmap, where each bit

repre-sents a different column, producing a unique integer for each grouping set The bits in the

bitmap indicate whether the columns are being aggregated in the grouping set (bit value is

1) or if the column is used to determine the grouping set (bit value is 0) used to calculate

the aggregate value.

The bit values are assigned to columns from right to left in the order the columns are

listed in the grouping_id()function For example, in the query in Listing 42.5, priceis

the rightmost bit value, bit 1; pub_idis assigned the next bit value, bit 2, and typeis

assigned the leftmost bit value, bit 3 When the grouping_id()value equals 6, that means

the bits 2 and 3 are turned on (4 + 2 + 0 = 6) This indicates that the typeandpub_id

columns are being aggregated in the grouping set, and the pricecolumn defines the

grouping set.

Thegrouping_id()column can thus be used to determine which of the two rows where

type,pub_id, and priceare all NULLis the row with the super-aggregate of all three

columns (grouping_id = 7), and which row is an aggregate rolled up where the value of

price is NULL(grouping_id = 6).

The values returned by the grouping_id()function can also be used for further filtering

your grouping set results or for sorting your grouping set results, as shown in Listing 42.6.

LISTING 42.6 Using the grouping_id() Function to Sort Results

SELECT type, pub_id, price, sum(isnull(ytd_sales, 0)) AS ytd_sales,

grouping_id(type, pub_id, price) as grping_id

FROM titles

where pub_id < ‘9’

GROUP BY GROUPING SETS ( type, pub_id, price, () )

order by grping_id

go

type pub_id price ytd_sales grping_id

- - -

-business NULL NULL 30788 3

mod_cook NULL NULL 24278 3

popular_comp NULL NULL 12875 3

psychology NULL NULL 9939 3

trad_cook NULL NULL 19566 3

NULL 0736 NULL 28286 5

NULL 0877 NULL 44219 5

NULL 1389 NULL 24941 5

NULL NULL NULL 0 6

NULL NULL 0.0006 111 6

NULL NULL 0.0017 750 6

NULL NULL 14.3279 4095 6

NULL NULL 14.595 18972 6

NULL NULL 14.9532 14294 6

NULL NULL 14.9611 4095 6

NULL NULL 15.894 40968 6

NULL NULL 15.9329 3336 6

NULL NULL 17.0884 2045 6

NULL NULL 17.1675 8780 6

NULL NULL NULL 97446 7

In SQL Server 2008, you can now set a variable’s initial value at the same time you declare

it For example, the following line of code declares a variable named @ctrof type intand

set its value to 100:

DECLARE @ctr int = 100

Previously, this functionality was only possible with stored procedure parameters.

Assigning an initial value to a variable required a separate SETorSELECTstatement This

new syntax simply streamlines the process of assigning an initial value to a variable The

value specified can be a constant or a constant expression, as in the following:

DECLARE @start_time datetime = getdate()

You can even assign the initial value via a subquery, as long as the subquery returns only a

single value, as in the following example:

declare @max_price money = (select MAX(price) from titles)

The value being assigned to the variable must be of the same type as the variable or be

implicitly convertible to that type.

Compound Assignment Operators

Another new feature that streamlines and improves the efficiency of your T-SQL code is

compound operators This is a concept that has been around in many other programming

languages for a long time, but has now finally found its way into T-SQL Compound

oper-ators are used when you want to apply an arithmetic operation on a variable and assign

the value back into the variable.

For example, the +=operator adds the specified value to the variable and then assigns the

new value back into the variable For example,

SET @ctr += 1

is functionally the same as

SET @ctr = @ctr + 1

The compound operators are a quicker to type, and they offer a cleaner piece of finished

code Following is the complete list of compound operators provided in SQL Server 2008:

+= Add and assign

-= Subtract and assign

*= Multiply and assign

/= Divide and assign

%= Modulo and assign

&= BitwiseANDand assign

^= BitwiseXORand assign

|= BitwiseORand assign

Row Constructors

SQL Server 2008 provides a new method to insert data to SQL Server tables, referred to as

row constructors Row constructors are a feature that can be used to simplify data insertion,

allowing multiple rows of data to be specified in a single DML statement Row

construc-tors are used to specify a set of row value expressions to be constructed into a data row.

Row constructors can be specified in the VALUESclause of the INSERTstatement, in the

USINGclause of the MERGEstatement, and in the definition of a derived table in the FROM

clause The general syntax of the row constructor is as follows:

VALUES ( { expression | DEFAULT | NULL |} [ , n ] ) [ , n ]

Each column of data defined in the VALUESclause is separated from the next using a

comma Multiple rows (which may also contain multiple columns) are separated from

each other using parentheses and a comma When multiple rows are specified, the

corre-sponding column values must be of the same data type or implicitly convertible data

type The following example shows the row constructor VALUESclause being used within a

SELECTstatement to define a set of rows and columns with explicit values:

SELECT a, b FROM (VALUES (1, 2), (3, 4), (5, 6), (7, 8), (9, 10) )

AS MyTable(a, b);

GO

a b

-1 2

3 4

5 6

7 8

9 10

TheVALUESclause is commonly used in this manner to populate temporary tables but can

also be used in a view, as shown in Listing 42.7.

LISTING 42.7 Using the VALUES Clause in a View

create view book_types

as

SELECT type, description

FROM (VALUES (‘mod_cook’, ‘Modern Cooking’),

(‘trad_cook’, ‘Traditional Cooking’),

(‘popular_comp’, ‘Popular Computing’),

(‘biography’, ‘Biography’),

(‘business’, ‘Business Development’),

(‘children’, ‘Children’’s Literature’),

(‘fiction’, ‘Fiction’),

(‘nonfiction’, ‘NonFiction’),

(‘psychology’, ‘Psychology and Self Help’),

(‘drama’, ‘Drama and Theater’),

(‘lit crit’, ‘Literay Criticism’)

) AS type_lookup(type, description)

go

Defining a view in this manner can be useful as a code lookup table:

select top 10

convert(varchar(50), title) as title, description

from titles t

inner join

book_types bt

on t.type = bt.type

order by title_id desc

go

title description

————————————————————————— ————————————

Sushi, Anyone? Traditional Cooking

Fifty Years in Buckingham Palace Kitchens Traditional Cooking

Onions, Leeks, and Garlic: Cooking Secrets of the Traditional Cooking

Emotional Security: A New Algorithm Psychology and Self Help

Prolonged Data Deprivation: Four Case Studies Psychology and Self Help

Life Without Fear Psychology and Self Help

Is Anger the Enemy? Psychology and Self Help

Computer Phobic AND Non-Phobic Individuals: Behavi Psychology and Self Help

Net Etiquette Popular Computing

Secrets of Silicon Valley Popular Computing

The advantage of this approach is that unlike a permanent code table, the view with the

VALUESclause doesn’t really take up any space; it’s materialized only when it’s referenced.

Maintaining it involves simply dropping and re-creating the view rather than having to

perform inserts, updates, and deletes as you would for a permanent table.

The primary use of row constructors is to insert multiple rows of data in a single INSERT

statement Essentially, if you have multiple rows to insert, you can specify multiple rows

in the VALUESclause The maximum number of rows that can be specified in the VALUES

clause is 1000 The following example shows how to use the row constructor VALUES

clause in a single INSERTstatement to insert five rows:

insert sales (stor_id, ord_num, ord_date, qty, payterms, title_id)

VALUES (‘6380’, ‘1234’, ‘3/26/2010’, 50, ‘Net 30’, ‘BU1032’),

(‘6380’, ‘1234’, ‘3/26/2010’, 150, ‘Net 30’, ‘PS2091’),

(‘6380’, ‘1234’, ‘3/26/2010’, 25, ‘Net 30’, ‘CH2480’),

(‘6380’, ‘1234’, ‘3/26/2010’, 30, ‘Net 30’, ‘FI2046’),

(‘6380’, ‘1234’, ‘3/26/2010’, 10, ‘Net 30’, ‘FI6318’)

As you can see, this new syntax is much more concise and simple than having to issue

five individual INSERTstatements as you would have had to do in versions of SQL Server

prior to SQL Server 2008.

TheVALUESclause can also be used in the MERGEstatement as the source table Listing 42.8

uses the VALUESclause to define five rows as the source data to perform INSERT/UPDATE

operations on the store_inventorytable defined in Listing 42.1.

LISTING 42.8 Using the VALUES Clause in a MERGE Statement

MERGE

INTO store_inventory as s

USING

(VALUES

(‘A011’, ‘CH3348’, 41 , getdate()),

(‘A011’, ‘CH2480’, 125 , getdate()),

(‘A011’, ‘FI0392’, 1100 , getdate()),

(‘A011’, ‘FI2046’, 1476 , getdate()),

(‘A011’, ‘FI1872’, 520 , getdate())

) as i (stor_id, title_id, qty, update_dt)

ON s.stor_id = i.stor_id

and s.title_id = i.title_id

WHEN MATCHED and s.qty <> i.qty

THEN UPDATE

SET s.qty = i.qty, update_dt = getdate()

WHEN NOT MATCHED

THEN INSERT (stor_id, title_id, qty, update_dt)

VALUES (i.stor_id, i.title_id, i.qty, getdate())

OUTPUT $action,

isnull(inserted.title_id, ‘’) as src_titleid,

isnull(str(inserted.qty, 5), ‘’) as src_qty,

isnull(deleted.title_id, ‘’) as tgt_titleid,

isnull(str(deleted.qty, 5), ‘’) as tgt_qty

;

go

$action src_titleid src_qty tgt_titleid tgt_qty

-

-INSERT CH2480 125

UPDATE CH3348 41 CH3348 24

UPDATE FI0392 1100 FI0392 1176

INSERT FI2046 1476

New date and time Data Types and Functions

SQL Server 2008 introduces four new dateandtimedata types:

. date

. time (precision)

. datetime2 (precision)

. datetimeoffset (precision)

Two of the most welcome of these new types are the new dateandtimedata types These

new data types allow you to store date-only and time-only values In previous versions of

SQL Server, the datetimeandsmalldatetimedata types were the only available types for

storing date or time values, and they always store both the date and time This made

date-only or time-date-only comparisons tricky at times because you always had to account for the

other component (for more detailed examples on working with datetimevalues in SQL

Server, see Chapter 43) In addition, the datetimestored date values range only from

1/1/1753 to 12/31/9999, with accuracy only to 3.33 milliseconds The smalldatetime

stored date values range only from 1/1/1900 to 6/6/2079, with accuracy of only 1 minute.

The new datedata type stores only the date component without the time component,

and stores date values ranging from 1/1/0001 to 12/31/9999.

The newtimedata type stores only the time component with accuracy that can be specified

down to seven decimal places (100 nanoseconds) The default is seven decimal places.

Thedatetime2data type stores both date and time components, similar to datetime,

increases the range of allowed values to 1/1/0001 to 12/31/9999, also with accuracy down

to seven decimal places (100 ns) The default precision is seven decimal places.

Thedatetimeoffsetdata type also stores both date and time components just like

datetime2, but includes the time zone offset from Universal Time Coordinates (UTC) The

time zone offset ranges from -14:00 to +14:00.

Along with the newdateandtimedata types, SQL Server 2008 also introduces some new

date and time functions for returning the current system date and time in different formats:

. SYSDATETIME()—Returns the current system datetime as aDATETIME2(7)value

. SYSDATETIMEOFFSET()—Returns the current system datetime as aDATETIMEOFFSET(7)

value

. SYSUTCDATETIME—Returns the current system datetime as aDATETIME2(7)value

representing the current UTC time

. SWITCHOFFSET (DATETIMEOFFSET,time_zone)—Changes the DATETIMEOFFSETvalue

from the stored time zone offset to the specified time zone

. TODATETIMEOFFSET (datetime, time_zone)—Applies the specified time zone to the

datetime value that does not reflect time zone difference from UTC

Listing 42.9 demonstrates the use of some of the new data types and functions Notice the

difference in the specified decimal precision returned for the time values.

LISTING 42.9 Using the new date and time Data Types and Functions

declare @date date,

@time time,

@time3 time(3),

@datetime2 datetime2(7),

@datetimeoffset datetimeoffset,

@datetime datetime,

@utcdatetime datetime2(7)

select @datetime = getdate(),

@date = getdate(),

@time = sysdatetime(),

@time3 = sysdatetime(),

@datetime2 = SYSDATETIME(),

@datetimeoffset = SYSDATETIMEOFFSET(),

@utcdatetime = SYSUTCDATETIME()

select @datetime as ‘datetime’,

@date as ‘date’,

@time as ‘time’,