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CHAPTER 1 RELATION AL DATABA SE OV ERVIEW
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Figure 1-2. A table representing the instances of our Member class
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Figure 1-3. A relationship between two classes
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Relationships are read in both directions. Reading Figure 1-3 from left to right, we have that one particular member doesn t have to play for a team and can play for at most one team (the numbers 0 and 1 at the end of the line nearest the Team class). Reading from right to left, we can say that one particular team doesn t need to have any members and can have many (the numbers 0 and n nearest the Member class). A relationship like the one in Figure 1-3 is called a 1-Many relationship (a member can belong to just one team, and a team can have many members). Most relationships in a relational database will be 1-Many relationships. For members of a team, you might think there should be exactly four members (say for an interclub team). Although this might be true when the team plays a round of golf, our database might record different numbers of members associated with the team as we add and remove players through the year. A data model usually uses 0, 1, and many to model the relationships between tables. Other constraints (such as the maximum number in a team) are more usually expressed with business rules or with UML use cases.4
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4. For more information, see Writing Effective Use Cases by Alistair Cockburn (Addison Wesley, 2001).
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CHAPTER 1 RELA TION AL DA TA BAS E OVERVIEW
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Introducing Tables
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The earlier description of a relational database as a set of tables was a little oversimplified. A more accurate definition is that a relational database is a set of relations. When people refer to tables in a relational database, they generally assume (whether they know it or not) that they are dealing with relations. The reason for the distinction between tables and relations is that there is a well-defined set of operations on relations that allow them to be combined and manipulated in various ways.5 This is exactly what we need in order to be able to extract accurate information from a database. We won t be covering the actual mathematics in this book, but we will be using the operations. So, in nonmathematical speak, what is so special about relations One of the most important features of a relation is that it is a set of unique rows.6 No two rows in a relation can have identical values for every attribute. A table does not generally have this restriction. If we consider our member data, it is clear why this uniqueness constraint is so important. If, in the table in Figure 1-2, we had two identical rows (say for Brenda Nolan), we would have no way to differentiate them. We might associate a team with one row and a subscription payment with the other, thereby generating all sorts of confusion. The way that a relational database maintains the uniqueness of rows is by specifying a primary key. A primary key is an attribute, or set of attributes, that is guaranteed to be different in every row of a given relation. For data such as the member data in this example, we cannot guarantee that all our members will have different names or addresses (a dad and son may share a name and an address and both belong to the club). To help distinguish different members, we have included an ID number as one of the member attributes, or fields. You will find that adding an identifying number (colloquially referred to as a surrogate key) is very common in database tables. If MemberID is defined as the primary key for the Member table, then the database system will ensure that in every row the value of MemberID is different. The system will also ensure that the primary key field always has a value. That is, we can never enter a row that has an empty MemberID field. These two requirements for a primary key field (uniqueness and not being empty) ensure that given the value of MemberID, we can always find a single row that represents that member. We will see that this is very important when we start establishing relationships between tables later in this chapter. Once a table has a primary key nominated, then it satisfies the uniqueness requirement of a relation. Another feature of a relation is that each attribute (or column) has a domain. A domain is a set of allowed values and might be something very general. For example, the domain for the FirstName attribute in the Member table is just any string of characters, for example, Michael or Helen. The domain for columns storing dates might be any valid date (so that February 29 is allowed only in leap years), whereas for columns keeping quantities,
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5. The relational theory was first introduced by the mathematician E. F. Codd in June 1970 in his article A Relational Model of Data for Large Shared Data Banks in Communications of the ACM: 13. 6. More accurately, a relation is a set of tuples.
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