For example, the
element p1 and p6 belong to the same category but have different structures.
(a)
(b)
Handling Structural Heterogeneity in OLAP
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of Idea Group Inc. is prohibited.
data are modeled using a star schema (Kimball, 1996), the dimension would be a
single table having a tuple for each leaf element in its hierarchy domain. One may
generalize this idea and think of an element as a tuple composed of the ancestor??™s
elements and their attributes. As an example, the element p1 in the dimension of
Figure 1 produces the tuple:
Figure 3. Different structures mixed in the heterogeneous dimension of Figure 2
2 Hurtado & Gutierrez
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Idea Group Inc. is prohibited.
[Product: p1, Brand: b1, Category: c1, Department: d1, All: all].
By viewing a dimension as a set of relational tuples, it is not difficult to realize
practical situations that cause structural heterogeneity. As an example, the problem
may arise when the OLAP server extracts tuples from more than one table having
different attributes. In addition, a table itself may have nonapplicable attributes or
missing values, which translate into non-applicable attributes for the corresponding
elements in the dimension.
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