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The term data integrity refers to the correctness and completeness of the data in a database. When the contents of a database are modified with the INSERT, DELETE, or UPDATE statements, the integrity of the stored data can be lost in many different ways. For example: Invalid data may be added to the database, such as an order that specifies a nonexistent product. Existing data may be modified to an incorrect value, such as reassigning a salesperson to a nonexistent office. Changes to the database may be lost due to a system error or power failure. Changes may be partially applied, such as adding an order for a product without adjusting the quantity available for sale. One of the important roles of a relational DBMS is to preserve the integrity of its stored data to the greatest extent possible. This chapter describes the SQL language features that assist the DBMS in this task.

FIGURE 16-1

To understand any of the programmatic SQL techniques, it helps to understand a little bit more about how the DBMS processes SQL statements To process a SQL statement, the DBMS goes through a series of five steps, shown in Figure 17-1: 1 The DBMS begins by parsing the SQL statement It breaks the statement up into individual words, makes sure that the statement has a valid verb, legal clauses, and so on Syntax errors and misspellings can be detected in this step 2 The DBMS validates the statement It checks the statement against the system catalog Do all the tables named in the statement exist in the database Do all of the columns exist, and are the column names unambiguous Does the user have the required privileges to execute the statement Semantic errors are detected in this step 3 The DBMS optimizes the statement.

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The ANSI/ISO SQL1 standard does not specify the structure and contents of the system catalog. In fact, the SQL1 standard does not require a system catalog at all. However, all of the major SQL-based DBMS products provide a system catalog in one form or another. The structure of the catalog and the tables it contains vary considerably from one brand of DBMS to another. Because of the growing importance of general-purpose database tools that must access the system catalog, the SQL standard (starting with SQL2) includes a specification of a set of views that provide standardized access to information typically found in the system catalog. A DBMS system that conforms to the SQL standard must support these views, which are collectively called the INFORMATION_SCHEMA. Because this schema is more complex than the actual system catalogs used by most commercial DBMS products, it is described in a separate section near the end of this chapter, The SQL Information Schema.

It explores various ways to carry out the statement Can an index be used to speed a search Should the DBMS first apply a search condition to Table A and then join it to Table B, or should it begin with the join and use the search condition afterward Can a sequential search through a table be avoided or reduced to a subset of the table After exploring alternatives, the DBMS chooses one of them 4 The DBMS then generates an application plan for the statement The application plan is a binary representation of the steps that are required to carry out the statement; it is the DBMS equivalent of executable code 5 Finally, the DBMS carries out the statement by executing the application plan Note that the steps in Figure 17-1 vary in the amount of database access they require and the amount of CPU time they take.

Each table in the system catalog contains information about a single kind of structural element in the database. Although the details vary, almost all commercial SQL products include system tables that describe each of these five entities: Tables The tables catalog describes each table in the database, identifying its table name, its owner, the number of columns it contains, its size, and so on. Columns The columns catalog describes each column in the database, giving the column s name, the table to which it belongs, its data type, its size, whether NULLs are allowed, and so on. Users The users catalog describes each authorized database user, including the user s name, an encrypted form of the user s password, and other data.

Part IV:

Parsing a SQL statement does not require access.

To preserve the consistency and correctness of its stored data, a relational DBMS typically imposes one or more data integrity constraints. These constraints restrict the data values that can be inserted into the database or created by a database update. Several different types of data integrity constraints are commonly found in relational databases, including: Required data. Some columns in a database must contain a valid data value in every row; they are not allowed to contain missing or NULL values. In the sample database, every order must have an associated customer who placed the order. Therefore, the CUST column in the ORDERS table is a required column. The DBMS can be asked to prevent NULL values in this column. Validity checking. Every column in a database has a domain, a set of data values that are legal for that column. The sample database uses order numbers that begin at

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