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Inserting Data into Partitioned Tables
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Inserting data into a partitioned table is completely automatic. The data is routed to the correct partition without any intervention by the SQL Server engine. Simply insert data into the table.
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Selecting Data from Partitioned Tables
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Selecting data from a partitioned table is as simple as inserting data into the partitioned table. As with insertion, data is automatically selected from the appropriate partition or partitions. As with an index, if no partition column is mentioned in the WHERE clause of the SQL statement, all partitions will be used, thus bypassing the primary benefit of the partitioned table.
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Selecting Data from a Specific Partition
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It is possible to select data from a specific partition by using the $PARTITION function. However, this serves the same purpose as simply putting the proper WHERE clause into the query. Hence, partitioning is essentially automatic. In order to view information about the partitions and their configuration, see the earlier sections of this chapter.
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Include the Partition Column
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I once consulted for a client using a third-party application intended for a hosted environment. The application vendor built partitioning into every table because of this model. For all of their pre-built queries and stored procedures, the partition
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Microsoft SQL Server 2005 Architecture and Features
column was included. The issue occurred when ad-hoc users began querying the database by using another reporting tool. Some of the users did not include the partition column in their queries, thus causing the partition and sometimes the indexes to be bypassed, causing queries to run much more slowly than they should have run. So, remember to include the partition column in your query.
Partitioning Scenarios
As discussed earlier in this chapter, there are a number of good reasons for using partitioning. This section presents a few scenarios of where and how partitioning can be especially beneficial.
Scenario 1: Partitioning Historical Data
In the first scenario, we will look at how partitioning can benefit systems by partitioning based on historical data. This is probably the most beneficial type of partitioning because most financial systems include data that has a date attached to it. As mentioned earlier in this chapter, I generally do not recommend indexing on date fields. Probably the most effective method of partitioning a financial database is on date. Not all tables include date fields, but the largest tables (for example, general ledger and sales) have date fields. Remember, earlier in the chapter you were told that the following two questions must be answered when partitioning a table: 1. What column will be partitioned 2. How will that column be partitioned The answer to the first question is that the general ledger table will be partitioned on date. Depending on the exact table definition of your general ledger table, this is based on how dates are stored. The answer to the second question depends on the size of your database and how queries are run. In addition, any performance problems that you are experiencing should be included in the decision process. The more granular the partitioning, the more effective the partitioning will be when you take advantage of it. In many cases, database administrators decide to partition financial systems by quarter, both to simplify the partitioning itself and to accommodate the end-of-quarter processing. Queries that involve aggregates by day, week, or month might benefit from more
19
Data Partitioning
granular partitioning, but a balance must be struck between managing many partitions and query benefits. In summary, a financial system can benefit from partitioning sales and general ledger data by date. The granularity of the partitioning depends on your particular needs. In addition, other large table such as customers can benefit from additional partitioning on region and so on.
Scenario 2: Storage Partitioning
Partitioning for storage is becoming less and less necessary as storage systems improve. However, there are still benefits of packing older, historical data on slower storage. This is purely for cost savings. If you have sufficient disk capacity, both space and performance, there is really no need to physically separate the partitions into different filegroups. However, you will see a benefit from partitioning based on the reduction in I/Os that SQL Server must do in order to perform some operations.
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