Scenario 3: Partitioning for Maintenance Optimization
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Partitioning for maintenance can be very beneficial. Let s look at Scenario 1 above. In most financial systems, you must keep data for a specified period of time for tax reporting or Sarbanes-Oxley compliance. In some cases, this is seven years or more. Prior to partitioning, old data must be removed by using the DELETE statement and putting the range of data to be deleted into the WHERE clause. This pruning of data can be a very expensive and time-consuming operation. As shown above, in the section on deleting partitions, SQL Server partitioning can greatly speed this operation. A workaround for deleting a partition can be done quickly and easily, as described earlier in this chapter. This allows you to easily and quickly prune a table. This is possible because you have used partitioning on the historical data in the database.
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Scenario 4: Spatial Partitioning
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Often data is stored spatially in a database. For example, data might be stored by region or state. If there is a large amount of data in this database, you can benefit by partitioning by city, state, region, and so on. An example of partitioning by region is shown here:
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CREATE PARTITION FUNCTION partfunc4 (char(2)) AS RANGE FOR VALUES ( E , N , NE , NW , S , SE , SW , W );
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CREATE PARTITION SCHEME partscheme4
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Microsoft SQL Server 2005 Architecture and Features
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AS PARTITION partfunc4 ALL TO ( PRIMARY );
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CREATE TABLE parttable4 ( col1 int, col2 int, col3 int, region char(2) ) ON partscheme4 (region);
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The partition function has to have the values of the partitioning column in alphabetical order, due to a SQL Server 2005 requirement. It might look a little strange here, but it works.
As with all partitioning, once the partitions have been created, they can then be used in an automatic manner. The key to partitioning is in the partitioning column.
Scenario 5: Account Partitioning
In this scenario, let s look at a table which stores data related to a large number of accounts. Partitioning an account table that has only one row per account is very inefficient, but a sales or other data table with a large number of rows per account that is queried or aggregated by account is very effective. By splitting up this aggregated data, you reduce the amount of time necessary for processing the data and the number of I/O operations.
Scenario 6: Join Partitioning
In the final scenario, let s look at how join performance can be improved. Join performance can be a large issue in many SQL Server systems because equijoins on columns often involve full table scans. Although table scans might not be avoidable, some of the join performance can be improved through partitioning. By joining two tables that are partitioned on the same column and that include the same number of partitions, the query optimizer actually joins the tables on a partitionby-partition basis, thus improving performance. To make sure that the tables use the same partitioning methodology, use the same partition function and partition scheme on both tables. This ensures that the join performance is improved.
The scenarios in this section focus on partitioning on one type of data. However, partitioning a database should not be limited to one partitioning type. For example, the financial system will benefit from partitioning on dates because the typical general ledger has data stored by date. However, other tables in the same financial database might benefit from partitioning on account or region. Don t be held to one particular partitioning method. Consider each database individually, and partition each table as appropriate. In addition, keep in mind that join performance can be improved by joining on partition columns.
In this chapter, you learned about SQL Server 2005 table and index partitioning. This partitioning works on a range of values and will store the data in the proper partition based on the contents of the partition column. SQL Server 2005 partitioning benefits the database in several ways. By working in conjunction with SQL Server Query Optimizer, only the necessary partitions will be accessed. This helps with the primary goal of performance tuning reducing the amount of data being accessed. Data partitioning has existed in a primitive form since SQL Server 7.0 and SQL Server 2000 using the UNION ALL view. As mentioned earlier, the UNION ALL view multiple tables are created, each with the same data structure, and are joined together with a view that is a UNION ALL between all partitions. This method works but is not optimal. It simply works better with SQL Server 2005 native partitioning. In this chapter, you learned about the fundamentals of data partitioning in SQL Server 2005, why you would want to use data partitioning, and how it can benefit your database. You also learned how to create, modify, and monitor partitions. Data partitions can be a powerful tool when created and used correctly. In order to use them correctly, they must be both designed and accessed correctly. This chapter gives information and tips on how to do both. Keep in mind that partitioning, like indexing, is very specific to the database and the data in the database. You have been provided with a number of scenarios in which partitioning might help, but as with most things, individual circumstances may vary. As the database administrator, you must decide how to partition based on your database, what it does, and what the data is like. The better you know your database, the better you can partition and take advantage of this powerful new feature.