Chapter 3: Data Structures

Chapter 3: Data Structures

Overview

Data structures hold data without regard to what the data is. The difference between a physical and an abstract model of a data structure is important, but often gets blurred when discussing them.

Each data structure has certain properties and operations that can be done on it, regardless of what is stored in it. Here are the basics, with informal definitions.

Data structures are important because they are the basis for many of the implementation details of real databases, for data modeling, and for relational operations, since tables are multisets.

3.1 Sets

A set is a collection of elements of the same kind of thing without duplicates in it. There is no ordering of the elements in a set. There is a special set, called the empty or null set. Since the term ?null? sounds and looks like the NULL missing value token in SQL, I will use the term ?empty set.?

The expression ?same kind of thing? is a bit vague, but it is important. In a database, the rows of a table have to be instances of the same entity; that is, a Personnel table is made up of rows that represent individual employees. However, a grouped table built from the Personnel table, say, by grouping of departments, is not the same kind of element. In the grouped table, the rows are aggregates and not individuals. Departmental data is a different level of abstraction and cannot be mixed with individual data.

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Chapter 3: Data Structures

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