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PART VI
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Part VI:
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SQL Today and Tomorrow
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retrieves a row containing a LOB that contains document text, and that updates 100 characters in the middle of the LOB data:
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declare lob CLOB; textbuf varchar(255); begin /* Put text to be inserted into buffer / . . . /* Get select from where for lob locator and lock LOB for update */ document_lob into lob documents document_id = '34218' update;
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/* Write new text 500 bytes into LOB */ dbms_lob.write(lob,100,500,textbuf); commit; end;
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Abstract (Structured) Data Types
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The data types envisioned by the relational data model are simple, indivisible, atomic data values. If a data item such as an address is actually composed of a street address, city, state, and postal code, as a database designer, you have two choices. You can treat the address as four separate data items, each stored in its own column, so that you can search and retrieve the items individually. Or you can treat the address as a single unit, in which case, you cannot process its individual component parts within the database. There is no middle ground that allows you to treat the address as a unit for certain situations and to access its component parts for others. Many programming languages (including even non object-oriented languages like C or Pascal) do provide such a middle ground. They support compound data types or named data structures. The data structure is composed of individual data items or lower-level structures, which can be accessed individually. But the entire data structure can also be treated as a single unit when that is most convenient. Structured or composite data types in object-relational databases provide this same capability in a DBMS context. Informix Universal Server supports abstract data types through its concept of row data types. You can think of a row type as a structured sequence of individual data items, called fields. Here is an Informix CREATE TABLE statement for a simple PERSONNEL table that uses a row data type to store both name and address information:
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CREATE TABLE PERSONNEL ( EMPL_NUM INTEGER, NAME ROW(
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24:
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SQL and Objects
F_NAME M_INIT L_NAME ADDRESS STREET CITY STATE POSTCODE MAIN SFX
VARCHAR(15), CHAR(1), VARCHAR(20)) ROW( VARCHAR(35), VARCHAR(15), CHAR(2), ROW( INTEGER, INTEGER)));
This table has three columns. The first one, EMPL_NUM, has an integer data type. The last two, NAME and ADDRESS, have a row data type, indicated by the keyword ROW, followed by a parenthesized list of the fields that make up the row. The NAME column s row data type has three fields within it. The ADDRESS column s row data type has four fields. The last of these four fields (POSTCODE) itself has a row data type and consists of two fields. In this simple example, the hierarchy is only two levels deep, but the capability can be (and often is) extended to additional levels. Individual fields within the columns of the table are accessible in SQL statements through an extension of the SQL dot notation that is already used to qualify column names with table names and user names. Adding a dot after a column name allows you to specify the names of individual fields within a column. This SELECT statement retrieves the employee numbers and first and last names of all personnel with a specified main postal code:
SELECT EMPL_NUM, NAME.F_NAME, NAME.L_NAME FROM PERSONNEL WHERE ADDRESS.POSTCODE.MAIN = '12345';
Suppose another table within the database, named MANAGERS, had the same NAME structure as one of its columns. Then this query retrieves the employee numbers of employees who are also managers:
SELECT EMPL_NUM FROM PERSONNEL, MANAGERS WHERE PERSONNEL.NAME = MANAGERS.NAME;
In the first of these two queries, it makes sense to retrieve the individual fields within the NAME column. The second query shows a situation where it s more convenient to use the entire name column (all three fields) as the basis for comparison. It s clearly a lot more convenient to ask the DBMS to compare the two abstract data typed columns than it is to specify separate comparisons for each of the individual fields. Together, these examples show the advantages of the row data type in allowing access to the fields at any level of the hierarchy. The row data type columns require special handling when you re inserting data into the database. The PERSONNEL table has three columns, so an INSERT statement for the table must have three items in its VALUES clause. The columns that have a row data type require a special ROW value-constructor to put together the individual data items into a row-type
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