SQL 2008 Performance Improvements

Agenda

• Partitioning Enhancements

• Sparse Columns

• Filtered indexes

• Plan Freezing

• MERGE (T-SQL)

Some notes…

• SQL Status within the industry compared to other DB providers

• Caught up on many features, such as Parallel Data Warehouse (R2) – this used dedicated architecture and design.

• On windows platform performance is virtually unmatched.

• Has connectors/APIs from other non windows languages, namely java platform.

Table Partitioning Background

• File Types

• What is Table Partitioning

• How to create, some concepts– File groups – Partition function– Partition Schema

File Types

Filegroups

• Filegroups – a single or a group of files logically aliased. Default filegroup: PRIMARY.

Partitioning• Filegroups – a single or a group of files logically aliased. Default

filegroup: PRIMARY.

• Partition function – A user defined function which allows to define to which file group a row in a table will be inserted.

Example:

Create three partitions: > 1 , 1-100, 1000>

CREATE PARTITION FUNCTION myRangePF1 (int) AS RANGE LEFT FOR VALUES (1, 100, 1000);

Partitioning• Partition Scheme – A schema where a partition

function will be applied. Defined/Created in a Filegroup, here we used PRIMARY.

Example: CREATE PARTITION FUNCTION myRangePF1 (int) AS RANGE LEFT FOR VALUES (1, 100, 1000);

CREATE PARTITION SCHEME myRangePS1 AS PARTITION myRangePF1 TO (test1fg, test2fg, test3fg, test4fg);

CREATE TABLE PartitionTable (col1 int, col2 char(10)) ON myRangePS1 (col1) ;

PartitioningFilegroup test1fg test2fg test3fg test4fg

Partition Num. 1 2 3 4

Values col1 <= 1 col1 > 1 AND col1 <= 100 col1 > 100 AND col1 <= 1000 col1 > 1000

Partitioning

• Predicate usage in query:

CREATE PARTITION FUNCTION RangePF1 ( int ) AS RANGE FOR VALUES (10, 100, 1000) ;

SELECT $PARTITION.RangePF1 (10) ; GO

SELECT $PARTITION.TransactionRangePF1(TransactionDate) AS Partition, COUNT(*) AS [COUNT] FROM Production.TransactionHistory GROUP BY PARTITION.TransactionRangePF1(TransactionDate)

ORDER BY Partition ;

Multiple Threads per Partition

Multiple Threads per Partition

Utilises machines with large number of processors, each thread will run on separate CPU.

Partition Level Lock Escalation- New CREATE | ALTER Table Option in syntax

ALTER TABLE MyPartitionedTable SET (LOCK_ESCALATION = TABLE);

- Default is ‘Table’

- Option can be disabled

- Increase the risk of deadlocks but in return can increase performance

- Example:

A very large table where the partition function is date based on a certain field. If we are certain we will not touch the old partitions (for older dates) then we could safely insert new records as this will occur in a different partition.

Partition Aware Seek operation

-PartitionID Logical column

-New Skip/Scan Operation

Link: http://msdn.microsoft.com/en-us/library/ms345599.aspx

Partition Information Enhancements

Added to Execution plan:

§ Partitioned (True | False)§ Actual partitioned Count§ Actual partitioned Accessed

Sparse Columns- Optimized for storing NULLs, reduced space requirements for NULL values

- In turn: significant overhead for non NULL values

- Good candidates for sparse colum:

-Columns with many NULLs but from a datatype where its easy to get a 20-40% space saving, for example datetime (ratio 8 to 12) but only need 52% of data to be NULLs.

- Table in next page.

- Some restrictions apply: certain data types are not allowed, keys are not allowed to be sparse etc.

- http://msdn.microsoft.com/en-us/library/cc280604.aspx

Sparse Columns – Decision Table

Data type Nonsparse bytes Sparse bytes NULL percentage

bit 0.125 4.125 98%

tinyint 1 5 86%

smallint 2 6 76%

int 4 8 64%

bigint 8 12 52%

real 4 8 64%

float 8 12 52%

smallmoney 4 8 64%

money 8 12 52%

smalldatetime 4 8 64%

datetime 8 12 52%

uniqueidentifier 16 20 43%

date 3 7 69%

Sparse ColumnsProperties not allowed on sparse columns:

- IDENTITY

- ROWGUIDCOL

- FILESTREAM

- Columns can not have default columns

- Not supported for computed columns

Other Important restrictions:

- Can not be used as part of Primary Key or clustered key

- http://msdn.microsoft.com/en-us/library/cc280604.aspx

Sparse ColumnsUseful for:

- Flat Data Warehouse Tables

- Entity-Attribute-Value Design where NULLs are expected on some properties.

- When using Column Sets (a query can return all sparse columns in untyped XML)

http://msdn.microsoft.com/en-us/library/cc280521.aspx

Filtered Indexes- Index will include only a subset of Rows

- Query optimizer is aware of filtered indexes.

- Can improve performance

- Reduces index maintenance & Storage Costs

- Supports Simple predicates only

http://technet.microsoft.com/en-us/library/cc280372.aspx

Filtered IndexesCREATE NONCLUSTERED INDEX INDEX_1  

ON

Production.BillOfMaterials

(ComponentID, StartDate)     

WHERE EndDate IS NOT NULL ;

Filtered IndexesGood for:

- Sparse columns as NOT NULL predicate can be used.

- Categories of Data

- Partial Unique Constraints.

Plan FreezingUsed for:

- Change/Optimize query without change the text of query directly

- Does so by adding/attaching query hints to existing plan guide.

- Types:

- Object: Will override function / SP.

- SQL Plan: Will override stand alone SQL queries or batches of queries.

- TEMPLATE: Override stand alone + parameterized plans.

SampleExisting SP:

SELECT TOP 1 * FROM Sales.SalesOrderHeader ORDER BY OrderDate DESC;

SampleOverride plan:

sp_create_plan_guide

@name = N'Guide2',

@stmt = N'SELECT TOP 1 * FROM Sales.SalesOrderHeader ORDER BY OrderDate DESC',

@type = N'SQL',

@module_or_batch = NULL,

@params = NULL,

@hints = N'OPTION (MAXDOP 1)';

MERGE StatementOutperforms equivalent multiple statement query which achieve the same query goal.

Simplifies multiple operations in 1 query syntax – easy to read and understand.

MERGE INTO [AdventureWorks].[Person].[Contact_Base] AS Target

USING

(SELECT ContactID,Title,FirstName,MiddleName,LastName,EmailAddress

FROM [AdventureWorks].[Person].[Contact_Temp]) AS Source (ContactID,Title,FirstName,MiddleName,LastName,EmailAddress)

ON Target.ContactID = Source.ContactID

WHEN MATCHED THEN

UPDATE SET EmailAddress = Source.EmailAddress

WHEN NOT MATCHED BY TARGET THEN

INSERT (ContactID,Title,FirstName,MiddleName,LastName,EmailAddress)

VALUES (ContactID,Title,FirstName,MiddleName,LastName,EmailAddress);

Demo: http://www.youtube.com/watch?gl=GB&v=_D4Eu-GDboU

Links:http://www.sqllion.com/2009/07/transaction-isolation-levels-in-sql-server/ http://sqlblog.com/blogs/erin_welker/archive/2008/02/10/partitioning-enhancements-in-sql-server-2008.aspx http://www.sqlskills.com/blogs/paul/post/SQL-Server-2008-Partition-level-lock-escalation-details-and-examples.aspx