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Low Priority All efforts will be made to recover lost information within 24 hours from the report of loss, but no guarantee is provided It is recommended that all user files that are not business-critical be submitted as Low Priority..

The RESTRICT rule for deletes and updates is a "single-level" rule it affects only the parent table in a relationship. The CASCADE rule, on the other hand, can be a "multi-level" rule, as shown in Figure 11-3.

Figure 15-5

The chargeback costs associated with this operation will be based on how quickly the data must be restored. (See Costs .) With this approval, please call the Help Desk at extension 5937 for more information on the turn-around time of your request. GENERAL SUPPORT For general questions and comments, or for support on issues not related to data protection, contact the Help Desk at extension 5937.

Armed with this metadata, the tool is able to determine what can be included in a brandlevel attribute and maintain the aggregate structure accordingly. TiP Summarizing dimensional data does not require an attribute hierarchy, but some tools rely on this kind of relationship to define and generate aggregates. The existence of hierarchies like these may help define an aggregate, but they are not necessary. Brands, for example, might not fall neatly into categories the way Figure 15-5 depicts. This would not prevent either brand or category from being used to define an aggregate of order_facts. Indeed, even a product-level attribute, such as the product s color, might be used to define a summary table. Don t let tools that focus on attribute hierarchies cause you to lose sight of possibilities like this. It may still be possible to generate the aggregate, even if it requires working around a hierarchy-based view of dimensions.

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Based on last year s information and statistics, the following costs are expected for service:

A dimensional aggregate schema that conforms to the base schema is but one way to organize the storage of summary data. Derived tables, as described in the previous chapter, may provide a useful alternative. A single-table design, on the other hand, is likely to lead to trouble.

Monthly Chargeback none $60 $320 $700 $1,800 $10,000 $22,000 $130,000

Assume for this discussion that the OFFICES/SALESREPS and SALESREPS/ORDERS relationships shown in the figure both have CASCADE rules. What happens when you delete Los Angeles from the OFFICES table The CASCADE rule for the OFFICES/SALESREPS relationship tells the DBMS to automatically delete all of the SALESREPS rows that refer to the Los Angeles office (office number 21) as well. But deleting the SALESREPS row for Sue Smith brings into play the CASCADE rule for the SALESREPS/ORDERS relationship. This rule tells the DBMS to automatically delete all of the ORDERS rows that refer to Sue (employee number 102). Deleting an office thus causes cascaded deletion of salespeople, which causes cascaded deletion of orders. As the example shows, CASCADE delete rules must be specified with care because they can cause widespread automatic deletion of data if they're used incorrectly. Cascaded update rules can cause similar multilevel updates if the foreign key in the child table is also its primary key. In practice, this is not very common, so cascaded updates typically have less far-reaching effects than cascaded deletes. The SET NULL and SET DEFAULT update and delete rules are both two-level rules; their impact stops with the child table. Figure 11-4 shows the OFFICES, SALESREPS, and ORDERS tables again, with a SET NULL delete rule for the OFFICES/SALESREPS relationship. This time, when the Los Angeles office is deleted, the SET NULL delete rule tells the DBMS to set the REP_OFFICE column to NULL in the SALESREPS rows that refer to office number 21. The rows remain in the SALESREPS table, however, and the impact of the delete operation extends only to the child table.

As defined in this chapter, an aggregate schema is a very specific form of summarization: one that conforms to the original, base schema Data can be summarized in other ways that do not preserve the organizational structure of the base data These too are valid summaries Since they transform the structure of the base data they summarize, they are examples of derived schemas, as discussed in 14 As you have learned, the tables in an aggregate schema conform to those in the base schema it summarizes The aggregate facts have the same name, meaning, and content as those in the base fact table; dimension tables are the same as those in the base star, or are conformed rollups whose attributes share the name, meaning, and content of those in the base star This conformance ensures semantic consistency across stars and facilitates a simple query-rewriting process.