SQL: Data partitioning in SQL Server 2005 - Part V (nice example)

Reference: http://www.databasejournal.com/features/mssql/article.php/3647561/Data-partitioning-in-SQL-Server-2005---Part-V.htm

Data partitioning in SQL Server 2005 - Part V


By Muthusamy Anantha Kumar aka The MAK<http://www.databasejournal.com/feedback.php/http:/www.databasejournal.com/features/mssql/article.php/3647561/Data-partitioning-in-SQL-Server-2005---Part-V.htm>

In Part IV<http://www.databasejournal.com/features/mssql/article.php/3647271> of this article series, we have seen how to partition an existing table based on certain range of dates.

Part V illustrates how to merge and split existing partitions.

First let us create a database with a table. Then let us insert data and then partition the table.

Step 1
Let us assume we have created the folder, C:\Data2, and the following subfolders. [Refer Fig 1.0]
C:\Data2\Primary
C:\Data2\FG1
C:\Data2\FG2
C:\Data2\FG3
C:\Data2\FG4
[cid:image001.jpg@01CD8ACB.2C95A050]
Fig 1.0
Step 2
Let us assume that we have a database, Data Partition DB3, with five different file groups, as shown below.
use master
IF EXISTS (SELECT name FROM sys.databases WHERE name = N'Data Partition DB5')
DROP DATABASE [Data Partition DB5]
GO
CREATE DATABASE [Data Partition DB5]
ON PRIMARY
(NAME='Data Partition DB5',
FILENAME=
'C:\Data2\Primary\Data Partition DB5.mdf',
SIZE=5,
MAXSIZE=500,
FILEGROWTH=1 ),
FILEGROUP [Data Partition DB5 FG1]
(NAME = 'Data Partition DB5 FG1',
FILENAME =
'C:\Data2\FG1\Data Partition DB5 FG1.ndf',
SIZE = 5MB,
MAXSIZE=500,
FILEGROWTH=1 ),
FILEGROUP [Data Partition DB5 FG2]
(NAME = 'Data Partition DB5 FG2',
FILENAME =
'C:\Data2\FG2\Data Partition DB5 FG2.ndf',
SIZE = 5MB,
MAXSIZE=500,
FILEGROWTH=1 ),
FILEGROUP [Data Partition DB5 FG3]
(NAME = 'Data Partition DB5 FG3',
FILENAME =
'C:\Data2\FG3\Data Partition DB5 FG3.ndf',
SIZE = 5MB,
MAXSIZE=500,
FILEGROWTH=1 ),
FILEGROUP [Data Partition DB5 FG4]
(NAME = 'Data Partition DB5 FG4',
FILENAME =
'C:\Data2\FG4\Data Partition DB5 FG4.ndf',
SIZE = 5MB,
MAXSIZE=500,
FILEGROWTH=1 )
Step 3
Let us assume that we have a table on the primary file group. You could create that table by executing the following T-SQL statement.
USE [Data Partition DB5]
go
CREATE TABLE MyTable
(ID INT NOT NULL,
Date DATETIME,
Cost money ) on [primary]
Step 4
Now let us create a unique clustered index on the table by executing the following T-SQL statement.
USE [Data Partition DB5]
go
CREATE UNIQUE CLUSTERED INDEX MyTable_IXC
ON MyTable(ID) on [PRIMARY]
Step 5
Now let us insert some data onto the table, MyTable, using the following T-SQL statements.
USE [Data Partition DB5]
go
declare @count int
set @count =-25
while @count <=100
begin
insert into MyTable select @count,getdate(),100.00
set @count=@count+1
end
set @count =101
while @count <=200
begin
insert into MyTable select @count,getdate(),200.00
set @count=@count+1
end
set @count =201
while @count <=300
begin
insert into MyTable select @count,getdate(),300.00
set @count=@count+1
end
set @count =301
while @count <=400
begin
insert into MyTable select @count,getdate(),400.00
set @count=@count+1
end
set @count =401
while @count <=800
begin
insert into MyTable select @count,getdate(),500.00
set @count=@count+1
end
Let us query the table using the T-SQL statement shown below.

select * from MyTable

ID Date Cost

----------- ----------------------- ---------------------

-25 2006-11-09 15:12:01.177 100.00

-24 2006-11-09 15:12:01.207 100.00

-23 2006-11-09 15:12:01.207 100.00

-22 2006-11-09 15:12:01.223 100.00

-21 2006-11-09 15:12:01.223 100.00

-20 2006-11-09 15:12:01.223 100.00

-19 2006-11-09 15:12:01.240 100.00

.

.

.

0 2006-11-09 15:12:01.347 100.00

1 2006-11-09 15:12:01.347 100.00

2 2006-11-09 15:12:01.363 100.00

3 2006-11-09 15:12:01.363 100.00

.

.

792 2006-11-09 15:12:06.270 500.00

793 2006-11-09 15:12:06.270 500.00

794 2006-11-09 15:12:06.287 500.00

795 2006-11-09 15:12:06.287 500.00

796 2006-11-09 15:12:06.287 500.00

797 2006-11-09 15:12:06.300 500.00

798 2006-11-09 15:12:06.300 500.00

799 2006-11-09 15:12:06.317 500.00

800 2006-11-09 15:12:06.317 500.00

Now let us query the partition information of this table by executing the following query.

select * from sys.partitions where object_name(object_id)='MyTable'

You can see the result as shown below [Refer Fig 1.1]. It is obvious that all of the 826 rows are in the same partition.

[cid:image002.jpg@01CD8ACB.2C95A050]
Fig 1.1

Step 6

Partitioning of the tables depends on the partition range defined by Partition Function. Let us assume that we are going to partition the table into four parts, onto four different file groups.

use [Data Partition DB5]

GO

CREATE PARTITION FUNCTION [Data Partition Range](int)

AS RANGE LEFT FOR VALUES (100,200,300)

When we use LEFT clause in the range, the first partition could hold values from negative infinity to 100, the second partition could hold values from 101 to 200, the third partition could hold values from 201 to 300 and the fourth partition could hold values from 301 to infinity or whatever the max range of the integer value.

When we use RIGHT clause in the range, the first partition could hold values from negative infinity to 99, the second partition could hold values from 100 to 199, the third partition could hold values from 200 to 299 and the fourth partition could hold values from 300 to Infinity or whatever the max range of the integer value.

Execute the following query to see the partition information.

SELECT * FROM sys.partition_range_values

Step 7

Partition Function is not useful, unless it is associated with the proper file groups that we have created.

Let us assume that we are going to use file group [Data Partition DB5 FG1], [Data Partition DB5 FG2], [Data Partition DB5 FG3], [Data Partition DB5 FG4] for the partition table that we are going to create. This can be created as shown below.

USE [Data Partition DB5]

go

CREATE PARTITION SCHEME [Data Partition Scheme]

AS PARTITION [Data Partition Range]

TO ([Data Partition DB5 FG1], [Data Partition DB5 FG2], [Data Partition DB5 FG3],[Data Partition DB5 FG4]);

Step 8
Now, let us move the table to the new partition by using the following TSQL command.

Drop index MyTable_IXC on MyTable with (Move To [Data Partition Scheme] (ID) )

Now, let us query the partition information by using the following query.

select * from sys.partitions where object_name(object_id)='MyTable'

You can see the result as shown below [Refer Fig 1.2]. It is obvious that all of the 826 rows are spread across all four file groups, based on the partition range.

[cid:image003.jpg@01CD8ACB.2C95A050]
Fig 1.2

Now we have MyTable partitioned in to four different partitions. It is time to merge the first two partitions.

Merge partition

Execute the following T-SQL statement to merge the first two partitions together.

Alter partition function [Data Partition Range]()

merge range(100)

Now, let us query the partition information by using the following query.

select * from sys.partitions where object_name(object_id)='MyTable'

You will the see the following results showing the merge of partition number 1 and 2. [Refer Fig 1.3]

[cid:image004.jpg@01CD8ACB.2C95A050]
Fig 1.3

Split partition

Execute the following T-SQL statement to split last partition into two partitions.

Alter partition function [Data Partition Range]()

split range(300)

When executed you will get the following error.

Msg 7707, Level 16, State 1, Line 1

The associated partition function 'Data Partition Range' generates

more partitions than there are file groups mentioned in the scheme

'Data Partition Scheme'.

In order to avoid this, we have to add another file group to the database.

Let us execute the below T-SQl statement, which will add a new file group to the database.

Alter database [Data Partition DB5] add FILEGROUP [Data Partition DB5 FG5]

go

alter database [Data Partition DB5]

ADD FILE

(NAME = 'Data Partition DB5 FG5',

FILENAME =

'C:\Data2\FG4\Data Partition DB5 FG5.ndf',

SIZE = 5MB,

MAXSIZE=500,

FILEGROWTH=1 )

TO FILEGROUP [Data Partition DB5 FG5]

Go

Now let us try again to split the partition range by executing the following T-SQL statement.

Use [Data Partition DB5]

go

ALTER PARTITION SCHEME [Data Partition Scheme]

NEXT USED [Data Partition DB5 FG5]

GO

Alter partition function [Data Partition Range]()

split range(500)

Note: We should make SQL Server aware that it should use the next partition when it is splitting. The clause NEXT USED does that.

Now, let us query the partition information by using the following query.

select * from sys.partitions where object_name(object_id)='MyTable'

You will the see the following results showing the split of partition number 3. [Refer Fig 1.4]

[cid:image005.jpg@01CD8ACB.2C95A050]
Fig 1.4

You can see that any ID values between 300 and 500 are moved to partition 3 and any ID values more than 500 are moved to partition 4.

Conclusion

Part V of this article series has illustrated how to merge and split existing partitions.

Implementing Semaphore At Database Level (SQL Server)

Hi,

I am Bishnu Patro.
Recently, I had an requirement to execute a particular stored proc certain number of times (it should be configurable depending upon the available Memory). The reason, is if the stored proc is executed certain number of times simultaneously, it used to take more time to execute since the all available memory is consumed and there is no free memory left. So, we decided to limit the number of parallel execution at the stored procedure level and it should be configurable. If it configured to run the stored proc simultaneouly to a maximum of 2. Then when the next request comes for execution of the stored proc, this request will wait for one of the execution to complete.

I have implemented this by way of implementing customized semaphore at database level.

I have created a table MultipleInstanceJobConfiguration, to keep track of the number of simultaneous execution of the stored proc.


CREATE TABLE [dbo].[MultipleInstanceJobConfiguration](
[JobType] [nvarchar](50) NULL,
[Total] [smallint] NULL,
[Available] [smallint] NULL,
[IsEnabled] [bit] NULL
) ON [PRIMARY]


Here, jobtype is the name of the stored proc.
Total is the number of simultaneous execution of the stored proc.
Available is at any point how many simultaneous execution available.
IsEnabled is to whether you want to enable this feature or disable it.


The following statement inserts for a jobtype SI:

INSERT INTO [dbo].[MultipleInstanceJobConfiguration] ([JobType] ,[Total] ,[Available] ,[IsEnabled]) VALUES ('SI',2,2,1)
GO


The following stored proc is used to take a lock on an object:


CREATE Proc [dbo].[AcqLock]
@Resource_Name1 as nvarchar(255),
@Lock_Mode1 as nvarchar(32),
@Lock_TimeOut1 as int
As

DECLARE @LockResult int

EXECUTE @LockResult = sp_getapplock
@Resource = @Resource_Name1,
@LockMode = @Lock_Mode1,
@LockOwner = 'Session',
@LockTimeout = @Lock_TimeOut1


while( @LockResult <> 0)
BEGIN
WAITFOR DELAY '00:00:01'
EXECUTE @LockResult = sp_getapplock
@Resource = @Resource_Name1,
@LockMode = @Lock_Mode1,
@LockOwner = 'Session',
@LockTimeout = @Lock_TimeOut1
END
GO


The following stored proc is used to release a lock on an object:


CREATE Proc [dbo].[ReleseLock]
@Resource_Name1 as nvarchar(255)
As
EXECUTE sp_releaseapplock
@Resource = @Resource_Name1, @LockOwner = 'Session'
GO


The following stored proc is an example implementing semphore:


CREATE PROC [dbo].[StoredProcUsingSemaphore]
AS

--Updating Configuation Available Count On Start of stored proc
declare @total int
declare @available int
declare @isEnabled bit
select @total = Total,@available = Available,@isEnabled = IsEnabled from dbo.MultipleInstanceJobConfiguration with (nolock) where JobType like 'SI'
WHILE(@total > 0 and @isEnabled = 1)
BEGIN
if( @available > 0)
BEGIN
Begin Try
EXEC dbo. AcqLock 'MY_MULTIPLEINSTANCES','Exclusive',0
select @available = Available,@isEnabled = IsEnabled from dbo.MultipleInstanceJobConfiguration with (nolock) where JobType like 'SI'
if(@available > 0 and @isEnabled = 1)
BEGIN
Update dbo.MultipleInstanceJobConfiguration
Set Available = Available - 1
where JobType like 'SI'

INSERT INTO MetricsLoadProcessingLog VALUES (@loadID,'SI_Job_Configuration',null ,1 ,'Decremented Available Count',GETUTCDATE())

Exec dbo. ReleseLock 'MY_MULTIPLEINSTANCES'
BREAK
END
End Try
Begin Catch
Exec dbo. ReleseLock 'MY_MULTIPLEINSTANCES'
End Catch

END
WAITFOR DELAY '00:00:15'
select @available = Available,@isEnabled = IsEnabled from dbo.MultipleInstanceJobConfiguration with (nolock) where JobType like 'SI'

END


----Your piece of code will go here.....


-----Updating Available Count on Finish
if(@total > 0 and @isEnabled = 1)
BEGIN
EXEC dbo. AcqLock 'MY_MULTIPLEINSTANCES ','Exclusive',0

Update dbo.MultipleInstanceJobConfiguration
Set Available = Available + 1
where JobType like 'SI' and Available < Total


Exec dbo. ReleseLock 'MY_MULTIPLEINSTANCES'
END

GO


Please let me know if the post was useful....

SQL: Tips For Lightning-Fast Insert Performance On SQL Server

http://arnosoftwaredev.blogspot.in/2011/10/tips-for-lightning-fast-insert.html

Tips For Lightning-Fast Insert Performance On SQL Server
1. Increase ADO.NET BatchSize to eliminate unnecessary network roundtrips, e.g. SqlDataAdapter.UpdateBatchSize<http://msdn.microsoft.com/en-us/library/xw5z0hdd(v=VS.100).aspx> when working with DataAdapters, or SqlBulkCopy.BatchSize<http://msdn.microsoft.com/en-us/library/system.data.sqlclient.sqlbulkcopy.batchsize.aspx> when applying SqlBulkCopy.

2. Limit the number of indices on the target table to what is really essential for query performance.

3. Place indices on master table columns referenced by the target table's foreign keys.

4. Choose the target table's clustered index wisely, so that inserts won't lead to clustered index node splits. Usually an identity column (AKA "autoinc") is a good choice. If you don't have autoinc primary keys, consider introducing a new identity column just for the sake of making it your clustered index.

5. Let the client insert into a temporary heap table first (that is, a table that has no clustered index, resp. no index at all). Then, issue one big "insert-into-select"<http://blog.sqlauthority.com/2007/08/15/sql-server-insert-data-from-one-table-to-another-table-insert-into-select-select-into-table/> statement to push all that staging table data into the actual target table. The "insert-into-select"-statement must contain an "order-by"-clause which guarantees ordering by clustered index.

6. Apply SqlBulkCopy<http://msdn.microsoft.com/en-us/library/system.data.sqlclient.sqlbulkcopy.aspx>.

7. Decrease transaction logging by choosing bulk-logged recovery model<http://msdn.microsoft.com/en-us/library/ms189275.aspx>, resp. setting SqlServer traceflag 610<http://sqlserverplanet.com/sql-server-2008/sql-server-2008-minimally-logged-inserts/>.

8. If your business scenario allows for it, place a table lock before inserting. This will make any further locking unnecessary, and is especially a viable option on staging tables as described in (5). SqlBulkCopy also supports table locks via SqlBulkCopyOptions<http://msdn.microsoft.com/en-us/library/system.data.sqlclient.sqlbulkcopyoptions.aspx>.

9. Place database datafile and logfile on two physically separated devices, e.g. on two disks or two SAN LUNs configured for different spindles.

10. Prefer server-side processsing (e.g. by means of "insert-into-select") to client-to-server-roundtrips wherever possible.

11. This is probably the fastest insert-approach I have ever heard of (taken from this sqlbi whitepaper<http://www.sqlbi.eu/LinkClick.aspx?fileticket=svahq1Mpp9A%3D&tabid=169&mid=375>, see final paragraph): Create a new heap table just for the current insert batch, SqlBulk-Copy data into that table, then create a suited clustered index on the table, and add the table as a new table partition to an existing partitioned table.

12. Check execution plan when inserting, and go sure it does not contain anything unexpected or dispensable that might slow down your inserts, e.g. UDF-calls during check constraint execution, heavyweight trigger code, referential integrity checks without index usage or indexed view updates.

SQL Server 2005: Immediate Deadlock notifications (example)

http://weblogs.sqlteam.com/mladenp/archive/2008/05/21/SQL-Server-2005-Immediate-Deadlock-notifications.aspx


SQL Server 2005: Immediate Deadlock notifications<http://weblogs.sqlteam.com/mladenp/archive/2008/05/21/SQL-Server-2005-Immediate-Deadlock-notifications.aspx>



Deadlocks... huh??
Deadlocks can be a pain to debug since they're so rare and unpredictable. The problem lies in repeating them in your dev environment. That's why it's crucial to have as much information about them from the production environment as possible.
There are two ways to monitor deadlocks, about which I'll talk about in the future posts. Those are SQL Server tracing and Error log checking. Unfortunately both of them suffer from the same thing: you don't know immediately when a deadlock occurs. Getting this info as soon as possible is sometimes crucial in production environments. Sure you can always set the trace flag 1222 on, but this still doesn't solve the immediate notification problem.
One problem for some might be that this method is only truly useful if you limit data access to stored procedures. <joke> So all you ORM lovers stop reading since this doesn't apply to you anymore! </joke>
The other problem is that it requires a rewrite of the problematic stored procedures to support it. However since SQL Server 2005 came out my opinion is that every stored procedure should have the try ... catch block implemented. There's no visible performance hit from this and the benefits can be huge. One of those benefits are the instant deadlocking notifications.
Needed "infrastructure"
So let's see how it done. This must be implemented in the database you wish to monitor of course.
First we need a view that will get lock info about the deadlock that just happened. You can read why this type of query gives info we need in my previous post<http://weblogs.sqlteam.com/mladenp/archive/2008/04/29/SQL-Server-2005-Get-full-information-about-transaction-locks.aspx>.
CREATE VIEW vLocks
AS
SELECT L.request_session_id AS SPID,
DB_NAME(L.resource_database_id) AS DatabaseName,
O.Name AS LockedObjectName,
P.object_id AS LockedObjectId,
L.resource_type AS LockedResource,
L.request_mode AS LockType,
ST.text AS SqlStatementText,
ES.login_name AS LoginName,
ES.host_name AS HostName,
TST.is_user_transaction AS IsUserTransaction,
AT.name AS TransactionName
FROM sys.dm_tran_locks L
LEFT JOIN sys.partitions P ON P.hobt_id = L.resource_associated_entity_id
LEFT JOIN sys.objects O ON O.object_id = P.object_id
LEFT JOIN sys.dm_exec_sessions ES ON ES.session_id = L.request_session_id
LEFT JOIN sys.dm_tran_session_transactions TST ON ES.session_id = TST.session_id
LEFT JOIN sys.dm_tran_active_transactions AT ON TST.transaction_id = AT.transaction_id
LEFT JOIN sys.dm_exec_requests ER ON AT.transaction_id = ER.transaction_id
CROSS APPLY sys.dm_exec_sql_text(ER.sql_handle) AS ST
WHERE resource_database_id = db_id()
GO
Next we have to create our stored procedure template:
CREATE PROC <ProcedureName>
AS
BEGIN TRAN
BEGIN TRY

<SPROC TEXT GOES HERE>

COMMIT
END TRY
BEGIN CATCH
-- check transaction state
IF XACT_STATE() = -1
BEGIN
DECLARE @message xml
-- get our deadlock info FROM the VIEW
SET @message = '<TransactionLocks>' + (SELECT * FROM vLocks ORDER BY SPID FOR XML PATH('TransactionLock')) + '</TransactionLocks>'

-- issue ROLLBACK so we don't ROLLBACK mail sending
ROLLBACK

-- get our error message and number
DECLARE @ErrorNumber INT, @ErrorMessage NVARCHAR(2048)
SELECT @ErrorNumber = ERROR_NUMBER(), @ErrorMessage = ERROR_MESSAGE()

-- if it's deadlock error send mail notification
IF @ErrorNumber = 1205
BEGIN
DECLARE @MailBody NVARCHAR(max)
-- create out mail body in the xml format. you can change this to your liking.
SELECT @MailBody = '<DeadlockNotification>'
+
(SELECT 'Error number: ' + isnull(CAST(@ErrorNumber AS VARCHAR(5)), '-1') + CHAR(10) +
'Error message: ' + isnull(@ErrorMessage, ' NO error message') + CHAR(10)
FOR XML PATH('ErrorMeassage'))
+
CAST(ISNULL(@message, '') AS NVARCHAR(MAX))
+
'</DeadlockNotification>'
-- for testing purposes
-- SELECT CAST(@MailBody AS XML)

-- send an email with the defined email profile.
-- since this is async it doesn't halt execution
EXEC msdb.dbo.sp_send_dbmail
@profile_name = 'your mail profile',
@recipients = 'dba@yourCompany.com',
@subject = 'Deadlock occured notification',
@body = @MailBody;
END
END
END CATCH
GO
The main part of this stored procedure is of course the CATCH block. The first line in there is check of the XACT_STATE()<http://msdn.microsoft.com/en-us/library/ms189797.aspx> value. This is a scalar function that reports the user transaction state. -1 means that the transaction is uncommittable and has to be rolled back. This is the state of the victim transaction in the internal deadlock killing process. Next we read from our vLocks view to get the full info (SPID, both SQL statements text, values, etc...) about both SPIDs that created a deadlock. This is possible since our deadlock victim transaction hasn't been rolled back yet and the locks are still present. We save this data into an XML message. Next we rollback our transaction to release locks. With error message and it's corresponding number we check if the error is 1205 - deadlock and if it is we send our message in an email. How to configure database mail can be seen here<http://msdn.microsoft.com/en-us/library/ms175887.aspx>.
Both the view and the stored procedures template can and probably should be customized to suit your needs.
Testing the theory
Let's try it out and see how it works with a textbook deadlock example that you can find in every book or tutorial.
-- create our deadlock table with 2 simple rows
CREATE TABLE DeadlockTest ( id INT)
INSERT INTO DeadlockTest
SELECT 1 UNION ALL
SELECT 2
GO
Next create two stored procedures (spProc1 and spProc2) with our template:
For spProc1 replace <SPROC TEXT GOES HERE> in the template with:
UPDATE DeadlockTest
SET id = 12
WHERE id = 2

-- wait 5 secs TO SET up deadlock condition IN other window
WAITFOR DELAY '00:00:05'

UPDATE DeadlockTest
SET id = 11
WHERE id = 1
For spProc2 replace <SPROC TEXT GOES HERE> in the template with:
UPDATE DeadlockTest
SET id = 11
WHERE id = 1

-- wait 5 secs TO SET up deadlock condition IN other window
WAITFOR DELAY '00:00:05'

UPDATE DeadlockTest
SET id = 12
WHERE id = 2
Next open 2 query windows in SSMS:
In window 1 run put this script:
exec spProc1
In window 2 put this script:
exec spProc2
Run the script in the first window and after a second or two run the script in the second window. A deadlock will happen and a few moments after the victim transaction fails you should get the notification mail. Mail profile has to be properly configured of course.
The resulting email should contain an XML with full info about the deadlock. You can view it by commenting msdb.dbo.sp_send_dbmail execution and uncommenting the SELECT CAST(@MailBody AS XML) line.
If you fire up the SQL Profiler, reset the table values, rerun both scripts and observe the deadlock graph event you should get a picture similar to this one:
[cid:image001.png@01CD761E.26957D40]<http://weblogs.sqlteam.com/images/weblogs_sqlteam_com/mladenp/WindowsLiveWriter/SQLServer2005SendmailwhenDeadlockhappens_124F2/deadlockProfiler_6.png>
End ? ... for now... but more to come soon!
With the upper technique we can get mostly the same info as with trace flags with the advantage of knowing immediately after happening, plus if we want we can extend this to notify/log about every error which I actually prefer to do.
We can see just how awesome is the new async functionality like database mail built on top of the SQL Server Service Broker<http://weblogs.sqlteam.com/mladenp/archive/2007/08/21/Service-Broker-goodies-Cross-Server-Many-to-One-One-to.aspx>. And instead of sending mail you can put the error in an error logging table in the same async way which I've demonstrated here<http://www.sqlteam.com/article/centralized-asynchronous-auditing-with-service-broker>.

SQL Server Isolation Levels By Example (Nice One)

http://www.gavindraper.co.uk/2012/02/18/sql-server-isolation-levels-by-example/


SQL Server Isolation Levels By Example
Posted on February 18, 2012<http://www.gavindraper.co.uk/2012/02/18/sql-server-isolation-levels-by-example/> by Gavin<http://www.gavindraper.co.uk/author/admin/>

Isolation levels in SQL Server control the way locking works between transactions.
SQL Server 2008 supports the following isolation levels
§ Read Uncommitted
§ Read Committed (The default)
§ Repeatable Read
§ Serializable
§ Snapshot
Before I run through each of these in detail you may want to create a new database to run the examples, run the following script on the new database to create the sample data. Note : You'll also want to drop the IsolationTests table and re-run this script before each example to reset the data.
CREATE TABLE IsolationTests
(
Id INT IDENTITY,
Col1 INT,
Col2 INT,
Col3 INT
)
INSERT INTO IsolationTests(Col1,Col2,Col3)
SELECT 1,2,3
UNION ALL SELECT 1,2,3
UNION ALL SELECT 1,2,3
UNION ALL SELECT 1,2,3
UNION ALL SELECT 1,2,3
UNION ALL SELECT 1,2,3
UNION ALL SELECT 1,2,3

Also before we go any further it is important to understand these two terms....
1. Dirty Reads - This is when you read uncommitted data, when doing this there is no guarantee that data read will ever be committed meaning the data could well be bad.
2. Phantom Reads - This is when data that you are working with has been changed by another transaction since you first read it in. This means subsequent reads of this data in the same transaction could well be different.
Read Uncommitted
This is the lowest isolation level there is. Read uncommitted causes no shared locks to be requested which allows you to read data that is currently being modified in other transactions. It also allows other transactions to modify data that you are reading.
As you can probably imagine this can cause some unexpected results in a variety of different ways. For example data returned by the select could be in a half way state if an update was running in another transaction causing some of your rows to come back with the updated values and some not to.
To see read uncommitted in action lets run Query1 in one tab of Management Studio and then quickly run Query2 in another tab before Query1 completes.
Query1
BEGIN TRAN
UPDATE Tests SET Col1 = 2
--Simulate having some intensive processing here with a wait
WAITFOR DELAY '00:00:10'
ROLLBACK

Query2
SET TRANSACTION ISOLATION LEVEL READ UNCOMMITTED
SELECT * FROM IsolationTests

Notice that Query2 will not wait for Query1 to finish, also more importantly Query2 returns dirty data. Remember Query1 rolls back all its changes however Query2 has returned the data anyway, this is because it didn't wait for all the other transactions with exclusive locks on this data it just returned what was there at the time.
There is a syntactic shortcut for querying data using the read uncommitted isolation level by using the NOLOCK table hint. You could change the above Query2 to look like this and it would do the exact same thing.
SELECT * FROM IsolationTests WITH(NOLOCK)

Read Committed
This is the default isolation level and means selects will only return committed data. Select statements will issue shared lock requests against data you're querying this causes you to wait if another transaction already has an exclusive lock on that data. Once you have your shared lock any other transactions trying to modify that data will request an exclusive lock and be made to wait until your Read Committed transaction finishes.
You can see an example of a read transaction waiting for a modify transaction to complete before returning the data by running the following Queries in separate tabs as you did with Read Uncommitted.
Query1
BEGIN TRAN
UPDATE Tests SET Col1 = 2
--Simulate having some intensive processing here with a wait
WAITFOR DELAY '00:00:10'
ROLLBACK

Query2
SELECT * FROM IsolationTests

Notice how Query2 waited for the first transaction to complete before returning and also how the data returned is the data we started off with as Query1 did a rollback. The reason no isolation level was specified is because Read Committed is the default isolation level for SQL Server. If you want to check what isolation level you are running under you can run "DBCC useroptions". Remember isolation levels are Connection/Transaction specific so different queries on the same database are often run under different isolation levels.
Repeatable Read
This is similar to Read Committed but with the additional guarantee that if you issue the same select twice in a transaction you will get the same results both times. It does this by holding on to the shared locks it obtains on the records it reads until the end of the transaction, This means any transactions that try to modify these records are force to wait for the read transaction to complete.
As before run Query1 then while its running run Query2
Query1
SET TRANSACTION ISOLATION LEVEL REPEATABLE READ
BEGIN TRAN
SELECT * FROM IsolationTests
WAITFOR DELAY '00:00:10'
SELECT * FROM IsolationTests
ROLLBACK

Query2
UPDATE IsolationTests SET Col1 = -1

Notice that Query1 returns the same data for both selects even though you ran a query to modify the data before the second select ran. This is because the Update query was forced to wait for Query1 to finish due to the exclusive locks that were opened as you specified Repeatable Read.
If you rerun the above Queries but change Query1 to Read Committed you will notice the two selects return different data and that Query2 does not wait for Query1 to finish.
One last thing to know about Repeatable Read is that the data can change between 2 queries if more records are added. Repeatable Read guarantees records queried by a previous select will not be changed or deleted, it does not stop new records being inserted so it is still very possible to get Phantom Reads at this isolation level.
Serializable
This isolation level takes Repeatable Read and adds the guarantee that no new data will be added eradicating the chance of getting Phantom Reads. It does this by placing range locks on the queried data. This causes any other transactions trying to modify or insert data touched on by this transaction to wait until it has finished.
You know the drill by now run these queries side by side...
Query1
SET TRANSACTION ISOLATION LEVEL SERIALIZABLE
BEGIN TRAN
SELECT * FROM IsolationTests
WAITFOR DELAY '00:00:10'
SELECT * FROM IsolationTests
ROLLBACK

Query2
INSERT INTO IsolationTests(Col1,Col2,Col3)
VALUES (100,100,100)

You'll see that the insert in Query2 waits for Query1 to complete before it runs eradicating the chance of a phantom read. If you change the isolation level in Query1 to repeatable read, you'll see the insert no longer gets blocked and the two select statements in Query1 return a different amount of rows.
Snapshot
This provides the same guarantees as serializable. So what's the difference? Well it's more in the way it works, using snapshot doesn't block other Queries from inserting or updating the data touched by the snapshot transaction. Instead it creates it's own little snapshot of the data being read at that time, if you then read that data again in the same transaction it reads it from its snapshot, This means that even if another transaction has made changes you will always get the same results as you did the first time you read the data.
So on the plus side your not blocking anyone else from modifying the data whilst you run your transaction but.... You're using extra resources on the SQL Server to allocate each snapshot transaction the additional resources to store the snapshot data which can be quite significant if your transaction is working with a large amount of data.
To use the snapshot isolation level you need to enable it on the database by running the following command
ALTER DATABASE IsolationTests
SET ALLOW_SNAPSHOT_ISOLATION ON

If you rerun the examples from serializable but change the isolation level to snapshot you will notice that you still get the same data returned but Query2 no longer waits for Query1 to complete.
Summary
You should now have a good idea how each of the different isolation levels work. You can see how the higher the level you use the less concurrency you are offering and the more blocking you bring to the table. You should always try to use the lowest isolation level you can which is usually read committed.

SQL: How to Create Dynamic Table Names in SQL Server

http://support.microsoft.com/kb/175850

INF: How to Create Dynamic Table Names in SQL Server


-- Variable that will contain the name of the table
declare @mytable varchar(30)
-- Creates a temp table name
select @mytable ='TEMP'+ CONVERT(char(12), GETDATE(), 14)
print @mytable

-- Table cannot be created with the character ":" in it
-- The following while loop strips off the colon
declare @pos int
select @pos = charindex(':',@mytable)

while @pos > 0
begin
select @mytable = substring(@mytable,1,@pos - 1) +
substring(@mytable,@pos + 1,30-@pos )
select @pos = charindex(':',@mytable)
end
print 'Name without colon is :'
print @mytable

--create table @mytable (col1 int)

-- Create the temporary table
execute ('create table '+ @mytable +
'(col1 int)' )

-- Insert two rows in the table
execute ('insert into ' + @mytable +
' values(1)')

execute ('insert into ' + @mytable +
' values(2)')

-- Select from the temporary table
execute ('select col1 from ' + @mytable )
-- Drop the temporary table
execute ('drop table ' + @mytable)

division in SQL results in 0

http://social.msdn.microsoft.com/Forums/en-US/transactsql/thread/483c81d4-8e6d-41fb-9a6e-cc61b42772e6/


declare @x int, @y int, @f float
set @x = 100
set @y = 2000
set @f = @x / (@y * 1.0)
print @x
print @y
print @f