Although you can interact with the data in a database one row at a time, relational databases are really all about sets. You have seen how tables can be created via queries or subqueries, made persistent via `insert`

statements, and brought together via joins; this chapter will explore how multiple tables can be combined using various set operators.

In many parts of the world, basic set theory is included in elementary-level math curriculums. Perhaps you recall looking at something like what is shown in Figure 6-1.

Figure 6-1. The union operation

The shaded area in Figure 6-1 represents the *union* of sets A and B, which is the combination of the two sets (with any overlapping regions included only once). Is this starting to look familiar? If so, then you’ll finally get a chance to put that knowledge to use; if not, don’t worry, because it’s easy to visualize using a couple of diagrams.

Using circles to represent two data sets (A and B), imagine a subset of data that is common to both sets; this common data is represented by the overlapping area shown in Figure 6-1. Since set theory is rather uninteresting without an overlap between data sets, I will use the same diagram to illustrate each set operation. There is another set operation that is concerned *only* with the overlap between two data sets; this operation is known as the *intersection* and ...

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