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The Relational Model
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a subset of tuples from another relation only), inclusion rules (a period when a supplier has supplied a product must be included in a period when the supplier had valid contract), process rules (which event should happen rst), and much more. It is up to the database and application designer to decide where to implement the rules. I strongly advocate having at least declarative constraints in your relational database. After all, if you do not use them, why do you use an RDBMS Constraints can be classi ed in other ways as well. For example, they can be classi ed according to which kind of object they constrain: type, attribute, relation, and database constraints. They can also be classi ed as immediate or deferred, based on when they are enforced: immediately or at the end of the current transaction. Note that according to the rule that there must be no value in a database at any time that would violate its constrained predicate, only immediate constraints should work inside a relational database. This means that constraints must be enforced at a single DML statement boundary, not at the end of a transaction or even later. A single DML statement is treated in an RDBMS as an atomic operation even if it modi es multiple rows; therefore, during the statement execution you could get rows that violate some constraint but never after the statement is nished. Note that immediate constraints only cannot guarantee that a database would re ect a valid state of affairs in real-world environment at all times. For example, although transferring money from one account to another is intended as an atomic operation, it involves two updates in a database. Both updates must nish successfully, or none should be performed. Therefore, we clearly need some other means to make databases consistent with the real world at any time. This can be done with transactions. A transaction is a logical unit of work that extends a statement-level notion of atomicity. Although transactions play an important role in an RDBMS, I am not going to explain them more in detail here; to learn more about them, please refer to Inside Microsoft SQL Server 2008: T-SQL Programming. ANSI standard SQL allows deferred constraints. SQL Server does not implement them. However, they can be implemented in procedural code for advanced checks and searches for incorrect data. Correctness is a stricter term than consistency; an RDBMS can enforce data consistency but not correctness. Consistency means that data is in accordance with business rules declared and known to the system; correctness is de ned outside the system by users of the system.
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Declarative Constraints
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Because declarative constraints are the most important way of implementing business rules in a relational database, I ll discuss them in more detail than other constraints.
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Tables in a database are physical representation of relations, and the rows of a table represent tuples; relations consist of unique tuples. This is what entity integrity is about uniquely
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Inside Microsoft SQL Server 2008: T-SQL Querying
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identifying rows in a table. You must have a combination of columns (which physically represent attributes) that uniquely identify a row. The minimal set of columns that still uniquely identify each row is called a key. Each table can have multiple unique column combinations in other words, multiple candidate keys. It is up to you to select one of them as your primary reference for each row and call it the primary key. SQL Server has two constraints for entity integrity: the Unique constraint for candidate keys and the Primary Key constraint for primary keys. You can have multiple Unique constraints and one Primary Key constraint per table. You know that every table should have a key. You also know that SQL Server does not enforce this; you can create a table without a Primary Key or Unique constraint. The reason for this is purely practical. Imagine you need to import data from a text le. If you had a key de ned, you would have to cleanse the data in your text le before the import. Cleansing text les is much less practical than cleansing data in a SQL Server table. Nevertheless, in production, all your tables should have a key de ned for each table. Each key has two required and two desired properties (D. Sarka, 2008). Uniqueness and applicability are required; stability and minimality are desired. Uniqueness means the key identi es each tuple uniquely. Applicability means the key has to be applicable for all tuples in a relation, it has to be known, and it should not consist of attributes that are meaningless for some tuples. (See the section Generalization and Specialization later in this chapter.) Stability means the key should not change, if possible. Minimality means the key should consist of the fewest columns possible and the fewest bytes possible. Nevertheless, because of physical problems, you should search for keys with all four properties. To track changes for an entity over time, such as in data warehousing scenarios, stability becomes a necessary property. And minimal keys provide the best performance. There is an old debate about keys and which are better: natural or surrogate. A natural key is a subset of the attributes that de ne an entity. A surrogate key is a key the designer creates and adds to the attributes of an entity; typically it is a sequential number. Personally, I avoid participating in this old debate. You cannot strictly distinguish between natural and surrogate keys. Is a Social Security ID (SSID) a natural or surrogate key Somebody could add it to the attributes of Person entity. Let me try to express a de nition of a natural key: a key is natural if the attribute it represents is used for identi cation independently of the database. If you have something unique, applicable, stable, and short in your table, use it. If you don t, add a sequential number for the primary reference, and you will have all required and desired properties for your primary key. If a key is applicable, its values must be known. SQL Server enforces this rule by prohibiting columns that allow NULLs from participating in Primary Key constraints; however, it allows nullable columns in Unique constraints. I ll come back to NULL, which is the marker for something unknown, later in this chapter. For now, I ll simply advise you not to use nullable columns for keys.
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