Relational Operations




All procedural relational query languages provide a set of operations that can be applied to either a single relation or a pair of relations. These operations have the nice and desired property that their result is always a single relation. This property allows one to combine several of these operations in a modular way. Specifically, since the result of a relational query is itself a relation, relational operations can be applied to the results of queries as well as to the given set of relations.

The most frequent operation is the selection of specific tuples from a single relation (say instructor) that satisfies some particular predicate (say salary > $85,000). The result is a new relation that is a subset of the original relation(instructor). For example, if we select tuples from the instructor relation of Figure 2.1, satisfying the predicate “salary is greater than $85000”, we get the result shown in Figure 2.10.

Relational Operations

Relational Operations

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Another frequent operation is to select certain attributes (columns) from a relation.The result is a new relation having only those selected attributes. For example, suppose we want a list of instructor ID and salaries without listing the name and dept_name values from the instructor relation of Figure 2.1, then the result shown in Figure 2.11, has the two attributes ID and salary. Each tuple in the result is derived from a tuple of the instructor relation but with only selected attributes shown.

The join operation allows the combining of two relations by merging pairs of
tuples, one from each relation, into a single tuple. There are a number of different
ways to join relations. Figure 2.12 shows an example
of joining the tuples from the instructor and department tables with the new tuples
showing the information about each instructor and the department in which she
is working. This result was formed by combining each tuple in the instructor
relation with the tuple in the department relation for the instructor’s department.
 
In the form of join shown in Figure 2.12, which is called a natural join, a tuple
from the instructor relation matches a tuple in the department relation if the values of their dept_name attributes are the same. All such matching pairs of tuples are present in the join result. In general, the natural join operation on two relations
matches tuples whose values are the same on all attribute names that are common
to both relations.
Relational Operations
Relational Operations
 
The Cartesian product operation combines tuples from two relations, but unlike
the join operation, its result contains all pairs of tuples from the two relations,
regardless of whether their attribute values match.
 
Because relations are sets, we can perform normal set operations on relations.
The union operation performs a set union of two “similarly structured” tables
(say a table of all graduate students and a table of all undergraduate students).
For example, one can obtain the set of all students in a department. Other set
operations, such as intersection and set difference can be performed as well.
 
As we noted earlier, we can perform operations on the results of queries. For
example, if we want to find the ID and salary for those instructors who have salary
greater than $85,000, we would perform the first two operations in our example
above. First we select those tuples from the instructor relation where the salary
value is greater than $85,000 and then, from that result, select the two attributes
ID and salary, resulting in the relation shown in Figure 2.13 consisting of the ID and salary. In this example, we could have performed the operations in either
order, but that is not the case for all situations, as we shall see.
Relational Operations
Relational Operations
 
Sometimes, the result of a query contains duplicate tuples. For example, if we
select the dept_name attribute from the instructor relation, there are several cases
of duplication, including “Comp. Sci.”, which shows up three times. Certain relational languages adhere strictly to the mathematical definition of a set and remove
duplicates. Others, in consideration of the relatively large amount of processing
required to remove duplicates from large result relations, retain duplicates. In
these latter cases, the relations are not truly relations in the pure mathematical
sense of the term.
 
Of course, data in a database must be changed over time. A relation can be
updated by inserting new tuples, deleting existing tuples, or modifying tuples by
changing the values of certain attributes. Entire relations can be deleted and new
ones created.


Frequently Asked Questions

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