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When facts are to be studied by looking down a hierarchy, the desire is to choose a member of the hierarchy and aggregate all transactions at its level and levels below it in the hierarchy.
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10 Recursive Hierarchies and Bridges 233
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Naming Key Columns in a Hierarchy Bridge Table
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Schema designers often borrow a convention from the entity-relationship modeling world, naming the two key columns in a hierarchy bridge table the way they would appear in an ER model like the one in Figure 10-1: company_key and parent_ company_key. In a dimensional design, this convention is inadvisable for two reasons. First, note that the bridge table does not cover parent child relationships exclusively. For a company at the bottom of the hierarchy, you will find a bridge row relating it to its parent but also to its grandparent, great-grandparent, and so forth. Therefore, parent_company_key is a misnomer; a better name might be ancestor_ company_key. Second, the ER naming approach implies a focus on a particular company, with the intent to look upward. Although it does not have to be used this way, this naming approach makes sense from an ER perspective where the columns are part of an entity. The column that represents the focus is simply called company_key. It is the primary key of the entity. The column used to find the parent, parent_company_key, is a foreign key. It gets a descriptive prefix in order to distinguish it. The hierarchy bridge does not represent a company entity, and as you will see shortly, it can be used to look up or down the hierarchy, depending on how it is joined to other tables. (In ER parlance, one would say that the primary key of the bridge table is the pair of foreign keys.) It is, therefore, advisable to give both key columns a descriptive prefix, rather than just one. This helps ensure there is never any confusion about what each row represents. The question, then, is what to name these columns. Although I am partial to the prefixes superior_ and subordinate_ as in the example, other prefixes are also possible. Upper_ and lower_ do the job just as nicely. If you really like sticking to the parent child analogy, use the column names ancestor_company_key and descendant_company_key. These names reflect the fact that not all rows are strict parent child associations. You can even call the level indicator generations_apart. These names make more sense, although the language sounds a little weird when you are talking about ownership of companies. They work nicely for people, though. Now that you are thinking about people in a parent child relationship, it may have occurred to you that most children have not one parent but two. Children who have been adopted have three or more parents. We will deal with the multiple-parent issue later in this chapter.
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In order to achieve this aggregation, the bridge table will be inserted in between the dimension table and the fact table. Since the intent is to aggregate transactions below the member in question, the lower- or subordinate-level key in the bridge will join to the fact table. The upper- or superior-level key will be used to join to the dimension table, where the query can be qualified for the member in question. This makes a lot more sense in the context of an example.
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Figure 10-7 illustrates how the bridge table can be used to aggregate all transactions at or below Company 5. Once again, the tree picture and bridge table contents are repeated, so you will not need to flip between figures to understand how this works. The top of the diagram illustrates the tables needed and how they are joined to one another. We will work through this diagram step by step to be sure you understand what is going on.
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