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For many very large databases, most large tables are effectively range partitioned by time, especially databases supporting business intelligence or data warehousing applications This is because these types of applications generally consist of data that is inserted and then can be modified for a period of time afterward After a certain period of time (hours, days, weeks, or months), data is considered read-only For these types of applications, it is also common to specify dates or times as search criteria, providing a perfect use-case for pruning Further, there is frequently a need to maintain a rolling window of data, perhaps only the past 3 months, or the past 13 months, or 25 months, and so forth Again, this provides an almost perfect use-case for range partitioning by time, because operations such as DROP PARTITION or TRUNCATE PARTITION can be used to purge data that is no longer necessary.

2. Frank Buschmann, et al., Pattern-Oriented Software Architecture, Volume 1: A System of Patterns (Indianapolis: Wiley Publishing, 1996), p. 323.

After implementing the framework to support this 5-layer architecture, I ll create a sample application with three different interfaces: Windows Forms, Web Forms, and Web Services. This will give you the opportunity to see firsthand how the framework supports the following models: High-scalability smart client Optimal performance web client Optimal performance web service Due to the way the framework is implemented, switching to any of the other models just discussed will require only configuration file changes. The result is that you can easily adapt your application to any of the physical configurations without having to change your code.

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The important property here is DataSource, which is set to the same BindingSource control as the detail controls in the UI itself. Everything else is handled automatically by either the business object or the ErrorProvider control itself.

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It would not make much sense to list partitions by time, because list partitioning deals only with individual data values and does not include the concept of adjacent data values So, in order to specify a partition containing a day s worth of data by using a DATE column, we would have to list all 86,400 possible seconds in each day That isn t feasible, and even if we found a way around that problem, we d still be faced with the inability to relate a list partition for one day to a list partition for the next day, or grouping into weeks, months, quarters, or years.

Figure 3-6. The location in the content pipeline of the processor you ll overwrite I ll show images like Figure 3-6 throughout this book each time you ll be working on a content pipeline so you can easily visualize on which parts you ll be working.

When you have an ON DELETE CASCADE and have not indexed the child table. For example, EMP is child of DEPT. DELETE FROM DEPT WHERE DEPTNO = 10 should cascade to EMP. If DEPTNO in EMP is not indexed, you will get a full table scan of EMP. This full scan is probably undesirable, and if you delete many rows from the parent table, the child table will be scanned once for each parent row deleted. When you query from the parent to the child. Consider the EMP/DEPT example again. It is very common to query the EMP table in the context of a DEPTNO. If you frequently query

Bad Decision Blocker (Utilities) Tint Color (Productivity) Pirate Glossary (Entertainment) What's in This : Brightkite: A Location-based Social Network Double Encore: An iPhone Development Agency Why Build a Native Application Using TabBar Navigation for Complex Apps The Importance of First Use Virtually Infinite Drill-Down with Navigation Controllers Best Practices for Address Book Integration Key Technologies: Navigation Controller and Tab Bar Controller Address Book Core Location Memory Management

Each method of partitioning is best suited to different types of data and the search operators used upon them: Range partitioning uses a finite to infinite list of data values, searched using equivalence operators (that is, =) and range operators ( >, >=, <, <=, BETWEEN, LIKE, and so forth) List partitioning uses a finite list of identified data values plus DEFAULT for everything else, searched using equivalence operators only Hash partitioning uses an infinite list of data values, searched using equivalence operators only..

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