Partitioning is the database process where very large tables are divided into multiple smaller parts. By splitting a large table into smaller, individual tables, queries that access only a fraction of the data can run faster because there is less data to scan. The main of goal of partitioning is to aid in maintenance of large tables and to reduce the overall response time to read and load data for particular SQL operations.
Benefits of Partitioning
- The relative speedup of queries that require only portions of large data sets. In this case, the optimizer eliminates searching in partitions that do not have relevant information.
- Faster data load
- Faster deletion of old data limited to certain partitions, if they are no longer needed.
- Faster archival of rarely used or old data can be migrated to cheaper and slower storage media.
Partitioning large tables or indexes can have the following manageability and performance benefits.
- You can transfer or access subsets of data quickly and efficiently, while maintaining the integrity of a data collection. For example, an operation such as loading data from an OLTP to an OLAP system takes only seconds, instead of the minutes and hours the operation takes when the data is not partitioned.
- You can perform maintenance operations on one or more partitions more quickly. The operations are more efficient because they target only these data subsets, instead of the whole table. For example, you can choose to compress data in one or more partitions or rebuild one or more partitions of an index.
- You may improve query performance, based on the types of queries you frequently run and on your hardware configuration. For example, the query optimizer can process equi-join queries between two or more partitioned tables faster when the partitioning columns in the tables are the same, because the partitions themselves can be joined.
When SQL Server performs data sorting for I/O operations, it sorts the data first by partition. SQL Server accesses one drive at a time, and this might reduce performance. To improve data sorting performance, stripe the data files of your partitions across more than one disk by setting up a RAID. In this way, although SQL Server still sorts data by partition, it can access all the drives of each partition at the same time.
In addition, you can improve performance by enabling lock escalation at the partition level instead of a whole table. This can reduce lock contention on the table. To reduce lock contention by allowing lock escalation to the partition, set the
LOCK_ESCALATION option of the
ALTER TABLE statement to AUTO.
Components and Concepts
The following terms are applicable to table and index partitioning.
A database object that defines how the rows of a table or index are mapped to a set of partitions based on the values of certain column, called a partitioning column. That is, the partition function defines the number of partitions that the table will have and how the boundaries of the partitions are defined. For example, given a table that contains sales order data, you may want to partition the table into twelve (monthly) partitions based on a datetime column such as a sales date.
A database object that maps the partitions of a partition function to a set of filegroups. The primary reason for placing your partitions on separate filegroups is to make sure that you can independently perform backup operations on partitions. This is because you can perform backups on individual filegroups.
The column of a table or index that a partition function uses to partition the table or index. Computed columns that participate in a partition function must be explicitly marked PERSISTED. All data types that are valid for use as index columns can be used as a partitioning column, except timestamp. The ntext, text, image, xml, varchar(max), nvarchar(max), or varbinary(max) data types cannot be specified. Also, Microsoft .NET Framework common language runtime (CLR) user-defined type and alias data type columns cannot be specified.
Vertical Partitioning on SQL Server tables
Vertical table partitioning is mostly used to increase SQL Server performance especially in cases where a query retrieves all columns from a table that contains a number of very wide text or BLOB columns.
An example for vertical partitioning can be a large table with reports for employees containing basic information, such as report name, id, number of report and a large column with report description.
Horizontal Partitioning on SQL Server tables
Horizontal partitioning divides a table into multiple tables that contain the same number of columns, but fewer rows. For example, if a table contains a large number of rows that represent monthly reports it could be partitioned horizontally into tables by years, with each table representing all monthly reports for a specific year. This way queries requiring data for a specific year will only reference the appropriate table. Tables should be partitioned in a way that queries reference as few tables as possible.
Tables are horizontally partitioned based on a column which will be used for partitioning and the ranges associated to each partition. Partitioning column is usually a datetime column but all data types that are valid for use as index columns can be used as a partitioning column, except a timestamp column.
There are two different approaches we could use to accomplish table partitioning. The first is to create a new partitioned table and then simply copy the data from your existing table into the new table and do a table rename. The second approach is to partition an existing table by rebuilding or creating a clustered index on the table.
Creating a partitioned table or index typically happens in four parts:
- Create a filegroup or filegroups and corresponding files that will hold the partitions specified by the partition scheme.
- Create a partition function that maps the rows of a table or index into partitions based on the values of a specified column.
- Create a partition scheme that maps the partitions of a partitioned table or index to the new filegroups.
- Create or modify a table or index and specify the partition scheme as the storage location.
After you have created the File Group and added File to each File Group run the following queries to confirm.
SELECT name AS AvailableFilegroups
WHERE type = 'FG'
name as [FileName],
physical_name as [FilePath]
WHERE type_desc = 'ROWS'
Creating Partition Function
CREATE PARTITION FUNCTION [PartitioningByMonth] (datetime)
AS RANGE RIGHT FOR VALUES ('20140201', '20140301', '20140401',
'20140501', '20140601', '20140701', '20140801',
'20140901', '20141001', '20141101', '20141201');
Create Partition Scheme
CREATE PARTITION SCHEME PartitionBymonth
AS PARTITION PartitioningBymonth
TO (January, February, March,
April, May, June, July,
Avgust, September, October,
Create New Table
CREATE TABLE Reports
(ReportDate datetime PRIMARY KEY,
ON PartitionBymonth (ReportDate);
INSERT INTO Reports (ReportDate,MonthlyReport)
SELECT '20140105', 'ReportJanuary' UNION ALL
SELECT '20140205', 'ReportFebryary' UNION ALL
SELECT '20140308', 'ReportMarch' UNION ALL
SELECT '20140409', 'ReportApril' UNION ALL
SELECT '20140509', 'ReportMay' UNION ALL
SELECT '20140609', 'ReportJune' UNION ALL
SELECT '20140709', 'ReportJuly' UNION ALL
SELECT '20140809', 'ReportAugust' UNION ALL
SELECT '20140909', 'ReportSeptember' UNION ALL
SELECT '20141009', 'ReportOctober' UNION ALL
SELECT '20141109', 'ReportNovember' UNION ALL
SELECT '20141209', 'ReportDecember'
Check to see if partition is working
p.partition_number AS PartitionNumber,
f.name AS PartitionFilegroup,
p.rows AS NumberOfRows
JOIN sys.destination_data_spaces dds ON p.partition_number = dds.destination_id
JOIN sys.filegroups f ON dds.data_space_id = f.data_space_id
OBJECT_NAME(OBJECT_ID) = 'Reports'