In SQL Server, indexes can also be partitioned based on the value ranges. Similar to the partitioned tables, the partitioned indexes also improve query performance. Partitioning enables you to manage and access subsets of data quickly and efficiently. When indexes become very large, you can partition the data into smaller, more manageable sections as the data is spread across file groups in a database.
Consider an example. In the Adventure Works database, the SalesOrderHeader table contains the details about the order received by Adventure Works, Inc. As the data in this table is large, the query takes a long time to execute. To solve this problem, you can create a partitioned index on the table. Partitioning an index will distribute the data in the table into multiple filegroups, thereby partitioning the table. This will enable the database engine to read or write data quickly. This also helps in maintaining the data efficiently.
Partitioning is allowed only in the Enterprise Edition of SQL Server. To create a partitioned index, you need to perform the following tasks:
Consider an example. The queries on the SalesOrderHeader table are mostly base on the OrderData column. The sales manager of Adventure Works requires the details of the orders received, on a yearly basis. The table contains the details of orders for the last five years beginning from 2001. Based on this information, you can create a partition function as follows:
CREATE PARTITION FUNCTION PFOrderDate (date time)
AS RANGE RIGHT FOR VALUES (‘2002-01-01’, ‘2003-01-01’, ‘2004-01-01’, ‘2005-01-01’)
The preceding statement creates a partition function, PFOrderDate, by using the date time data type. It specifies four boundary values. Therefore, there will be five partitions. As range right is specified for partitioning, the first partition will contain data less than the first boundary value, 2002-01-01. The second partition will contain data greater than or equal to 2002-01-01 and less than or equal to 2003-01-01. Similarly, other partitions will store data.
Consider an example. In the Adventure Works database, the SalesOrderHeader table contains the details about the order received by Adventure Works, Inc. As the data in this table is large, the query takes a long time to execute. To solve this problem, you can create a partitioned index on the table. Partitioning an index will distribute the data in the table into multiple filegroups, thereby partitioning the table. This will enable the database engine to read or write data quickly. This also helps in maintaining the data efficiently.
Partitioning is allowed only in the Enterprise Edition of SQL Server. To create a partitioned index, you need to perform the following tasks:
Creating a Partition Function
Similar to creating a partitioned table, you need to create a partition function to create a partitioned index. The partition function will determine the boundary values for creating partitions.Consider an example. The queries on the SalesOrderHeader table are mostly base on the OrderData column. The sales manager of Adventure Works requires the details of the orders received, on a yearly basis. The table contains the details of orders for the last five years beginning from 2001. Based on this information, you can create a partition function as follows:
CREATE PARTITION FUNCTION PFOrderDate (date time)
AS RANGE RIGHT FOR VALUES (‘2002-01-01’, ‘2003-01-01’, ‘2004-01-01’, ‘2005-01-01’)
The preceding statement creates a partition function, PFOrderDate, by using the date time data type. It specifies four boundary values. Therefore, there will be five partitions. As range right is specified for partitioning, the first partition will contain data less than the first boundary value, 2002-01-01. The second partition will contain data greater than or equal to 2002-01-01 and less than or equal to 2003-01-01. Similarly, other partitions will store data.