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quantity_sold[for year from 2002 to 2006 increment 1] =
round(quantity_sold[currentv()-1] *
(1 + (round(avg(percent_chng)[year between currentv()-3 and
currentv()-1] ,2) / 100))))
order by prod_category, channel_desc, year;
4. Notice the projected values for 2002 to 2006 for each channel_desc.
The steps in this project build on the discussions we've had on Oracle Database 10g's analytic capabilities. We used the lag function to calculate percentage change and used the model clause of the select statement to project sales five years into the future based on past trends. By going to the next level of examples, we can start to appreciate the significance of these functions and how they can be used.
Oracle Database 10g's analytic functions provide powerful and efficient analysis capabilities that would otherwise require complex SQL and/or third-party tools. All of these functions are part of the core database—ready and waiting to be exploited by your users.
So, now we have come to the end of our discussions on large database features. A great deal of material has been presented in this chapter and we have really only seen the tip of the iceberg! However, you can feel confident that with this background information, you are primed to tackle almost any large database environment out there.
Chapter 9 Mastery Check1. Which of the following is not a valid combination for composite partitioning?
A. Range partitioning with hash partitioning
B. List partitioning with hash partitioning
C. Range partitioning with list partitioning
2. What data population methods can be used on a compressed table that result in the data being compressed?
3. __________ partitioned indexes are defined independently of the data partitions, and __________ partitioned indexes have a one-to-one relationship with the data partitions.
4. Explain the functions of the Parallel Execution Coordinator in parallel processing.
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