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The same logic holds for UPDATE statements. This one changes the employee number, regardless of which table in the hierarchy actually holds the row for the employee:
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UPDATE PERSONNEL SET L_NAME = 'Harrison' WHERE EMPL_NUM = 1234;
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Again, the ONLY construct may be used to restrict the scope of the UPDATE operation to only rows that actually appear in the named table and not those that appear in its subtables. Of course, when operating at a given level within the table hierarchy, your SQL statements can reference only columns that are defined at that level. You cannot use this statement:
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DELETE FROM PERSONNEL WHERE SALARY < 20000.00;
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because the SALARY column doesn t exist in the top-level PERSONNEL table (class). It is defined only for some of its subtables (subclasses). You can use this statement:
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because SALARY is defined at this level of the table (class) hierarchy. As noted, table inheritance moves the operation of Informix Universal Server fairly far out of the relational database realm and into the object-oriented world. Relational purists point to examples like the previous ones to claim that object-relational databases bring with them dangerous inherent inconsistencies. They ask these typical kinds of questions: Why should an INSERT of a row into one table cause it to suddenly appear in two other tables and Why should a searched DELETE statement that doesn t match any rows of a table cause other rows in other tables to disappear Of course, the table hierarchy has stopped behaving strictly as if it were a set of relational tables, and instead has taken on many of the characteristics of an object class and object class hierarchy. Whether this is good or bad depends on your point of view. It does mean that you must be very careful about applying relational database assumptions blindly to an object-relational implementation.
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Sets, Arrays, and Collections
In a relational database, tables are the only database structure used to represent a set of objects. For example, the set of engineers in our personnel database is represented by the rows in the ENGINEERS table. Suppose each engineer has a set of academic degrees (a B.S. in science from MIT, a Ph.D. in electrical engineering from Michigan, and so on) that are to be stored in the database. The number of degrees for each engineer will vary from none for some engineers to perhaps half a dozen for others. In a pure relational database, there is only one correct way to add this information to the data model. A new table, DEGREES, must be created, as shown in Figure 24-5. Each row in the DEGREES table represents one individual academic degree held by one of the engineers. A column in the DEGREES table holds the employee number of the engineer holding the degree described by that particular row, and serves as a foreign key to the ENGINEERS table, linking the two tables in a parent/child relationship. The other columns in the DEGREES table describe the particulars of the degree. You have seen the type of parent/child relational table structure shown in Figure 24-5 many times in the earlier chapters of this book, and it has been a basic construct of relational databases since the beginning. However, there are some disadvantages to
Figure 24-5.
A relational modeling of engineers and their degrees
24:
SQL and Objects
having this be the only way in which sets of data attributes can be modeled. First, the database tends to have a great many tables and foreign key relationships and becomes hard to understand. Second, many common queries need to join three, four, or more tables to get the required answers. Third, with the implementations of relational joins provided by most DBMS systems, the performance of queries will deteriorate as they involve more and more joins. An object-oriented model of the engineers and their degrees would tend to reject the table structure of Figure 24-5. It would claim that the degrees are not substantial objects in their own right and deserving of their own table. Instead, they are attributes of the engineer holding the degrees. True, a variable number of degrees are associated with each engineer, but the object-oriented model would have no problem with representing this situation as an array or a set of data within the engineer object. The object-relational databases support this object-oriented view of data by supporting sets, arrays, or other collection data types. A column within a table can be defined to have one of these data types. It will then contain not a single data item value, but a set of data item values. Special SQL extensions allow a user, or more often a stored procedure, to manipulate the set of data items as a whole or to access individual members of the set.
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