SQL Server 2008 Partitioning

Here are some notes on “SQL Server 2008 Partitioning” I took while attending an advanced class on SQL Server taught by Kimberly Tripp (http://sqlskills.com/AboutKimberlyLTripp.asp).

Please note that, although these notes were taken during the class, I might have added some of my own (mis)interpretation :-). Always check your facts on Books Online (I try to provide links when applicable). As with anything else you get from a blog, never use any of this in production before you thoroughly validate it a test environment. Please keep in mind that some of those will be hard to follow without the right pre-requisite knowledge and the right context. Reading the post from top to bottom will help.

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Partitioning misconceptions

• It’s not all about speeding up for parallelism
• It’s not all about scaling out databases for performance
• It’s not all about very large and slow databases
• It’s also (mostly?) about range-based inserts or range-based deletes
• It’s also (mostly?) about the sliding window scenario
• There are cases when you do get peformance/paralelism benefits

Need partitioning

• Problem: Customer query was slow and asked for partitioning
• Solution: fixed the problem with indexing
• They did not need partitioning in that scenario

Partitioning strategies

• SQL Server 7 or later: read only partitioned views
• SQL Server 2000 or later: updatable partitioned views
• SQL Server 2005 or later: partitioned tables
• SQL Server 2008 or later: enhanced partitioned tables

Vertical partitioning

• Case: Large Patient table. Lots of columns, including picture.
• You could: Have a table for critical columns.
• Leave all the less used and BLOB columns in a second table.

Horizontal partitioning

• Case: Sales table for last few years.
• Problem: Weekly full backup of 1 billion rows.
• Problem: INSERTs blocked by queries on historical data.
• You could: Create multiple tables with partition views (PV).
• Uses constraints to implement the partitioning rules.
• You could: Create partitioned tables (PT) with read-only file groups.
• Uses a partition function and a partition scheme.
• Saves in management, backup. Could have different SLAs per year.

Easier Maintenance

• Loading options
• Index maintanence
• Backup/restore

Files and File Groups

• Multiple files in same file group: round robin between files
• If you lose one file in the FG, you can’t access the data
• Multiple file groups with partitions: spread by partitioning scheme.
• You can lose just one FG and still acess some of the data

The range-based delete problem

• Large table, large delete of old data takes a lot of time
• It’s all about reducing the impact on the multiple indexes
• Turn into an instant operation with the right partitioning

The data load problem

• Typical issue: need to load a lot of data into a table
• Again, it’s all about reducing the impact on the multiple indexes
• Typical: Load into heap, build clustered index, then non-clustered
• If source data is ordered and ever increasing: Load into clustered index, then non-clustered
• Will not work so well if you’re parellelizing the load operation
• Do not shrink in the end! It will cause massive fragmentation
• In any case, the impact on the log is big. Consider going to bulk logging mode.

Sliding window numbers

• Single processor, 5.7 million rows, 2 non-clustered indexes
• Data load – from 28m to 1m26s with partitioned table
• Data delete – from 15m to <1s with partitioned table
• Partitioned scneario benefits greatly from multiple processor
• Parallel bulk load and parallel index creation – almost linear gains

PVs

• Partitioned Views – Many tables, single view : SELECTS + UNION ALL
• Manually create the tables with constraints, place in separate FG
• Constraint: CHECK (SalesDate >= ‘20090101’ AND SalesDate < ‘20090201’)
• Create the view, which are then updateable
• Be careful not to make mistakes when creating the table and constraints
• SQL does not know of the PV when you create the tables
• Lots of tables, indexes, constraints – do it right

PVs and Constraints

• SQL uses the constraints to figure it all out
• Constraints need to allways be trusted – on create table, always check, never disable
• SQL can’t prune tree if the constraints are not trusted
• Check if NOT OBJECTPROPERTY(OBJECT_ID(‘constraint’),’CnstIsNotTrusted’)
• Use DBCC CHECKCONSTRAINTS. If not trusted, DROP and re-CREATE.
• See http://sqlblog.com/blogs/kalen_delaney/archive/2006/10/10/281.aspx

PTs

• Partitioned tables are defined in a more structured fashion.
• You define specific partitioning points “on a line”. 4 points = 5 partitions.
• Classic case is years or months on a time line. Which changes over time.
• It’s OK if you end up with an empty partition in the beginning or end.

Partitioning Function

• Partition Function – Logical – Defines the points on the line (right or left)
• Classic case is years or months on a time line. Which changes over time.
• Left is OK, but be careful with date boundaries – ’01/31/2009 23:59:59.997′
• You can get lost in the syntax – Do it in a white board first – do the code later
• It has to be over a single column – typically a date, country
• Partition function with n items creates n+1 partitions
• MOD function on an identity field? Possible, with maintanence issues…

Partitioning Scheme

• Partition Scheme – Physical – Maps to the file groups (could be a single one)
• You can add one extra file group that is not allocated – Next used
• Typically, you want different FG in different drives (or sets of drives)
• You cannot remove the first file in the file group

Final Step

• Create the table on the scheme – same place where you specify the file group
• Add the data to the table, which flow to the right partition
• Create non-clustered indexes also aligned with the partitions – many benefits
• You can even rebuild a table with a clustered index on the scheme as an online operation
• This is done with ALTER TABLE … ON psdate(SalesDate)

Rolling windows

• Create new metadata on filegroup: table, constraints, indexes, views (same schema)
• Switch the partition live. It’s all physically just updating the IAM pointers.
• You can only add one partition in a command.
• Could do a switch in and switch out together as a transaction.
• The first (in RIGHT) partition will remain empty as data slides/rolls forward
• Be careful not to merge when there’s data on it, or else data needs to move (expensive)

Other

• Cannot rebuild indexes online for only one partition, only for entire partitioned table.
• Separate into multiple tables to be able to do this. Benefits in doing this…
• Can use read-only and read-write partitioned tables. Benefits in doing this…
• New in SQL Server 2008: partition-aligned indexed views.
• Partitioned table parallelism. “Non-selective leading index columns”. Skip scanning.

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White Paper: Partitioned Tables and Indexes in SQL Server 2005
http://msdn.microsoft.com/en-us/library/ms345146.aspx