Oracle® Database Rules Manager and Expression Filter Developer's Guide 11g Release 1 (11.1) Part Number B31088-01 |
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Oracle Expression Filter, a feature of Oracle Database 10g, is a component of Rules Manager that allows application developers to store, index, and evaluate conditional expressions (expressions) in one or more columns of a relational table. Expressions are a useful way to describe interests in expected data.
Expression Filter matches incoming data with expressions stored in a column to identify rows of interest. It can also derive complex relationships by matching data in one table with expressions in a second table. Expression Filter simplifies SQL queries; allows expressions to be inserted, updated, and deleted without changing the application; and enables reuse of conditional expressions in rules by separating them from the application and storing them in the database. Applications involving information distribution, demand analysis, and task assignment can benefit from Expression Filter.
Expression Filter provides a data type, operator, and index type to store, evaluate, and index expressions that describe an interest in a data item or piece of information. See Oracle Database Data Cartridge Developer's Guide for an explanation of these terms. Expressions are stored in a column of a user table. Expression Filter matches expressions in a column with a data item passed by a SQL statement or with data stored in one or more tables, and evaluates each expression to be true or false. Optionally, expressions can be indexed when using the Enterprise Edition of Oracle Database. Expression Filter includes the following elements:
Attribute set: a definition of the event and its set of attributes
Expression data type: A virtual data type created through a constraint placed on a VARCHAR2
column in a user table that stores expressions
EVALUATE
operator: An operator that evaluates expressions for each data item
Administrative utilities: A set of utilities that validate expressions and suggest optimal index structure
Expression indexing: An index that enhances performance of the EVALUATE
operator for large expression sets. Expression indexing is available in Oracle Database Enterprise Edition
This section provides examples of how you can use Expression Filter.
Match Incoming Data with Conditional Expressions
Expression Filter can match incoming data with conditional expressions stored in the database to identify rows of interest. For example, consider an application that matches buyers and sellers of cars. A table called Consumer
includes a column called BUYER_PREFERENCES
with an Expression data type. The BUYER_PREFERENCES
column stores an expression for each consumer that describes the kind of car the consumer wants to purchase, including make, model, year, mileage, color, options, and price. Data about cars for sale is included with the EVALUATE
operator in the SQL WHERE
clause. The SQL EVALUATE
operator matches the incoming car data with the expressions to find prospective buyers.
The SQL EVALUATE
operator also enables batch processing of incoming data. Data can be stored in a table called CARS
and matched with expressions stored in the CONSUMER
table using a join between the two tables.
The SQL EVALUATE
operator saves time by matching a set of expressions with incoming data and enabling large expression sets to be indexed for performance. This saves labor by allowing expressions to be inserted, updated, and deleted without changing the application and providing a results set that can be manipulated in the same SQL statement, for instance to order or group results. In contrast, a procedural approach stores results in a temporary table that must be queried for further processing, and those expressions cannot be indexed.
Maintain Complex Table Relationships
Expression Filter can convey N-to-M (many-to-many) relationships between tables. Using the previous example:
A car may be of interest to one or more buyers.
A buyer may be interested in one or more cars.
A seller may be interested in one or more buyers.
To answer questions about these relationships, the incoming data about cars is stored in a table called CARS
with an Expression column (column of Expression data type) called SELLER_PREFERENCES
. The CONSUMERS
table includes a column called BUYER_PREFERENCES
. The SQL EVALUATE
operator can answer questions such as:
What cars are of interest to each consumer?
What buyers are of interest to each seller?
What demand exists for each car? This can help to determine optimal pricing.
What unsatisfied demand is there? This can help to determine inventory requirements.
This declarative approach saves labor. No action is needed if changes are made to the data or the expressions. Compare this to the traditional approach where a mapping table is created to store the relationship between the two tables. A trigger must be defined to recompute the relationships and to update the mapping table if the data or expressions change. In this case, new data must be compared to all expressions, and a new expression must be compared to all data.
Application Attributes
Expression Filter is a good fit for applications where the data has the following attributes:
A large number of data items exist to be evaluated.
Each data item has structured data attributes, for example VARCHAR, NUMBER, DATE, XMLTYPE
.
Incoming data is evaluated by a significant number of unique and persistent queries containing expressions.
The expression (in the SQL WHERE
clause) describes an interest in incoming data items.
The expressions compare attributes to values using relational operators (=, !=, <, >, and so on).
Expressions describe interests in an item of data. Expressions are stored in a column of a user table and compared, using the SQL EVALUATE
operator, to incoming data items specified in a SQL WHERE
clause or to a table of data. Expressions are evaluated as true or false, or return a null value if an expression does not exist for a row.
An expression describes interest in an item of data using one or more variables, known as elementary attributes. An expression can also include literals, functions supplied by Oracle, user-defined functions, and table aliases. A valid expression consists of one or more simple conditions called predicates. The predicates in the expression are linked by the logical operators AND
and OR
. Expressions must adhere to the SQL WHERE
clause format. (For more information about the SQL WHERE
clause, see Oracle Database SQL Language Reference.) An expression is not required to use all the defined elementary attributes; however, the incoming data must provide a value for every elementary attribute. Null is an acceptable value.
For example, the following expression includes the UPPER
function supplied by Oracle and captures the interest of a user in a car (the data item) with the model, price, and year as elementary attributes:
UPPER(Model) = 'TAURUS' and Price < 20000 and Year > 2000
Expressions are stored in a column of a user table with an Expression data type. The values stored in a column of this type are constrained to be expressions. (See Section 11.2.2.) A user table can have one or more Expression columns. A query to display the contents of an Expression column displays the expressions in string format.
You insert, update, and delete expressions using standard SQL. A group of expressions that are stored in a single column is called an expression set and shares a common set of elementary attributes. This set of elementary attributes plus any functions used in the expressions are the metadata for the expression set. This metadata is referred to as the attribute set. The attribute set consists of the elementary attribute names and their data types and any functions used in the expressions. The attribute set is used by the Expression column to validate changes and additions to the expression set. An expression stored in the Expression column can use only the elementary attribute and functions defined in the corresponding attribute set. Expressions cannot contain subqueries.
Expression Filter provides the DBMS_EXPFIL
package which contains procedures to manage the expression data.
There are four basic steps to create and use an Expression column:
Define an attribute set. See Section 11.2.1.
Define an Expression column in a user table. See Section 11.2.2.
Insert expressions in the table. See Section 11.2.3.
Apply the SQL EVALUATE
operator to compare expressions to incoming data items. See Section 11.3.
Figure 11-1 shows the process steps for creating and implementing a rules application based on Expression Filter. The remaining sections in this chapter guide you through this procedure.
Figure 11-1 Expression Filter Implementation Process for a Rules Application
A special form of an Oracle object type is used to create an attribute set. (For more information about object types, see Oracle Database Object-Relational Developer's Guide.)
The attribute set defines the elementary attributes for an expression set. It implicitly allows all SQL functions supplied by Oracle to be valid references in the expression set. If the expression set refers to a user-defined function, it must be explicitly added to the attribute set. An elementary attribute in an attribute set can refer to data stored in another database table using table alias constructs. One or more or all elementary attributes in an attribute set can be table aliases. If an elementary attribute is a table alias, the value assigned to the elementary attribute is a ROWID
from the corresponding table. For more information about table aliases, see Appendix A.
You can create an attribute set using one of two approaches:
Use an existing object type to create an attribute set with the same name as the object type. This approach is most appropriate to use when the attribute set does not contain any table alias elementary attributes. You use the CREATE_ATTRIBUTE_SET
procedure of the DBMS_EXPFIL
package. See Example 11-1.
Individually add elementary attributes to an existing attribute set. Expression Filter automatically creates an object type to encapsulate the elementary attributes and gives it the same name as the attribute set. This approach is most appropriate to use when the attribute set contains one or more elementary attributes defined as table aliases. You use the ADD_ELEMENTARY_ATTRIBUTE
procedure of the DBMS_EXPFIL
package. See Example 11-2.
If the expressions refer to user-defined functions, you must add the functions to the corresponding attribute set, using the ADD_FUNCTIONS
procedure of the DBMS_EXPFIL
package. See Example 11-3.
Example 11-1 shows how to use an existing object type to create an attribute set. It uses the CREATE_ATTRIBUTE_SET
procedure.
Example 11-1 Defining an Attribute Set From an Existing Object Type
CREATE OR REPLACE TYPE Car4Sale AS OBJECT (Model VARCHAR2(20), Year NUMBER, Price NUMBER, Mileage NUMBER); / BEGIN DBMS_EXPFIL.CREATE_ATTRIBUTE_SET(attr_set => 'Car4Sale', from_type => 'YES'); END; /
For more information about the CREATE_ATTRIBUTE_SET
procedure, see CREATE_ATTRIBUTE_SET
Procedure.
Example 11-2 shows how to create an attribute set Car4Sale
and how to define the variables one at a time. It uses the CREATE_ATTRIBUTE_SET
and ADD_ELEMENTARY_ATTRIBUTE
procedures.
Example 11-2 Defining an Attribute Set Incrementally
BEGIN DBMS_EXPFIL.CREATE_ATTRIBUTE_SET(attr_set => 'Car4Sale'); DBMS_EXPFIL.ADD_ELEMENTARY_ATTRIBUTE( attr_set => 'Car4Sale', attr_name => 'Model', attr_type => 'VARCHAR2(20)'); DBMS_EXPFIL.ADD_ELEMENTARY_ATTRIBUTE( attr_set => 'Car4Sale', attr_name => 'Year', attr_type => 'NUMBER', attr_defv1 => '2000'); DBMS_EXPFIL.ADD_ELEMENTARY_ATTRIBUTE( attr_set => 'Car4Sale', attr_name => 'Price', attr_type => 'NUMBER'); DBMS_EXPFIL.ADD_ELEMENTARY_ATTRIBUTE( attr_set => 'Car4Sale', attr_name => 'Mileage', attr_type => 'NUMBER'); END;/
For more information about the ADD_ELEMENTARY_ATTRIBUTE
procedure, see ADD_ELEMENTARY_ATTRIBUTES
Procedure.
If the expressions refer to user-defined functions, you must add the functions to the corresponding attribute set. Example 11-3 shows how to add user-defined functions, using the ADD_FUNCTIONS
procedure, to an attribute set.
Example 11-3 Adding User-Defined Functions to an Attribute Set
CREATE or REPLACE FUNCTION HorsePower(Model VARCHAR2, Year VARCHAR2) return NUMBER isBEGIN -- Derive HorsePower from other relational tables uisng Model and Year values.-- return 200; END HorsePower; / CREATE or REPLACE FUNCTION CrashTestRating(Model VARCHAR2, Year VARCHAR2) return NUMBER is BEGIN -- Derive CrashTestRating from other relational tables using Model -- -- and Year values. -- return 5; END CrashTestRating; / BEGIN DBMS_EXPFIL.ADD_FUNCTIONS (attr_set => 'Car4Sale', funcs_name => 'HorsePower'); DBMS_EXPFIL.ADD_FUNCTIONS (attr_set => 'Car4Sale', funcs_name => 'CrashTestRating'); END; /
For more information about the ADD_FUNCTIONS
procedure, see ADD_FUNCTIONS
Procedure.
To drop an attribute set, you use the DROP_ATTRIBUTE_SET
procedure. For more information, see DROP_ATTRIBUTE_SET
Procedure.
Expression is a virtual data type. Assigning an attribute set to a VARCHAR2
column in a user table creates an Expression column. The attribute set determines which elementary attributes and user-defined functions can be used in the expression set. An attribute set can be used to create multiple columns of EXPRESSION
data type in the same table and in other tables in the same schema. Note that an attribute set in one schema cannot be associated with a column in another schema.
To create an Expression column:
Add a VARCHAR2
column to a table or create a table with the VARCHAR2
column. An existing VARCHAR2
column in a user table can also be used for this purpose. The following example creates a table with a VARCHAR2
column, named Interest
, that will be used with an attribute set:
CREATE TABLE Consumer (CId NUMBER, Zipcode NUMBER, Phone VARCHAR2(12), Interest VARCHAR2(200));
Assign an attribute set to the column, using the ASSIGN_ATTRIBUTE_SET
procedure. The following example assigns an attribute set to a column named Interest
in a table called Consumer
:
BEGIN DBMS_EXPFIL.ASSIGN_ATTRIBUTE_SET ( attr_set => 'Car4Sale', expr_tab => 'Consumer', expr_col => 'Interest'); END; /
For more information about the ASSIGN_ATTRIBUTE_SET
procedure, see ASSIGN_ATTRIBUTE_SET
Procedure.
Figure 11-2 is a conceptual image of consumers' interests (in trading cars) being captured in a Consumer
table.
To remove an attribute set from a column, you use the UNASSIGN_ATTRIBUTE_SET
procedure of the DBMS_EXPFIL
package. See UNASSIGN_ATTRIBUTE_SET
Procedure.
To drop an attribute set not being used for any expression set, you use the DROP_ATTRIBUTE_SET
procedure of the DBMS_EXPFIL
package. See DROP_ATTRIBUTE_SET
Procedure.
To copy an attribute set across schemas, you use the COPY_ATTRIBUTE_SET
procedure of the DBMS_EXPFIL
package. See COPY_ATTRIBUTE_SET
Procedure.
You use standard SQL to insert, update, and delete expressions. When an expression is inserted or updated, it is checked for correct syntax and constrained to use the elementary attributes and functions specified in the corresponding attribute set. An error message is returned if the expression is not correct. For more information about evaluation semantics, see Section 11.4.
Example 11-4 shows how to insert an expression (the consumer's interest in trading cars, which is depicted in Figure 11-2) into the Consumer
table using the SQL INSERT
statement.
Example 11-4 Inserting an Expression into the Consumer Table
INSERT INTO Consumer VALUES (1, 32611, '917 768 4633', 'Model=''Taurus'' and Price < 15000 and Mileage < 25000'); INSERT INTO Consumer VALUES (2, 03060, '603 983 3464', 'Model=''Mustang'' and Year > 1999 and Price < 20000');
If an expression refers to a user-defined function, the function must be added to the corresponding attribute set (as shown in Example 11-3). Example 11-5 shows how to insert an expression with a reference to a user-defined function, HorsePower
, into the Consumer
table.
Example 11-5 Inserting an Expression That References a User-Defined Function
INSERT INTO Consumer VALUES (3, 03060, '603 484 7013', 'HorsePower(Model, Year) > 200 and Price < 20000');
Expression data can be bulk loaded into an Expression column using SQL*Loader. For more information about bulk loading, see Section 15.1.
You use the SQL EVALUATE
operator in the WHERE
clause of a SQL statement to compare stored expressions to incoming data items. The SQL EVALUATE
operator returns 1
for an expression that matches the data item and 0
for an expression that does not match. For any null values stored in the Expression column, the SQL EVALUATE
operator returns NULL
.
The SQL EVALUATE
operator has two arguments: the name of the column storing the expressions and the data item to which the expressions are compared. In the data item argument, values must be provided for all elementary attributes in the attribute set associated with the Expression column. Null is an acceptable value. The data item can be specified either as string-formatted name-value pairs or as an AnyData
instance.
In the following example, the query returns a row from the Consumer
table if the expression in the Interest
column evaluates to true for the data item:
SELECT * FROM Consumer WHERE EVALUATE (Consumer.Interest, <data item>) = 1;
Data Item Formatted as a String
If the values of all the elementary attributes in the attribute set can be represented as readable values, such as those stored in VARCHAR
, DATE
, and NUMBER
data types and the constructors formatted as a string, then the data item can be formatted as a string:
Operator Form
EVALUATE (VARCHAR2, VARCHAR2) returns NUMBER;
Example
SELECT * FROM Consumer WHERE EVALUATE (Consumer.Interest, 'Model=>''Mustang'', Year=>2000, Price=>18000, Mileage=>22000' ) = 1;
If a data item does not require a constructor for any of its elementary attribute values, then a list of values provided for the data item can be formatted as a string (name-value pairs) using two getVarchar
methods (a STATIC
method and a MEMBER
method) in the object type associated with the attribute set. The STATIC
method formats the data item without creating the object instance. The MEMBER
method can be used if the object instance is already available.
The STATIC
and MEMBER
methods are implicitly created for the object type and can be used as shown in the following example:
SELECT * FROM Consumer WHERE EVALUATE (Consumer.Interest, Car4Sale.getVarchar('Mustang', -- STATIC getVarchar API -- 2000, 18000, 22000) ) = 1; SELECT * FROM Consumer WHERE EVALUATE (Consumer.Interest, Car4Sale('Mustang', 2000, 18000, 22000).getVarchar() -- MEMBER getVarchar() API -- ) = 1;
Data Item Formatted as an AnyData Instance
Any data item can be formatted using an AnyData
instance. AnyData
is an object type supplied by Oracle that can hold instances of any Oracle data type, both supplied by Oracle and user-defined. For more information, see Oracle Database Object-Relational Developer's Guide.
Operator Form
EVALUATE (VARCHAR2, AnyData) returns NUMBER;
An instance of the object type capturing the corresponding attribute set is converted into an AnyData
instance using the AnyData
convertObject
method. Using the previous example, the data item can be passed to the SQL EVALUATE
operator by converting the instance of the Car4Sale
object type into AnyData
, as shown in the following example:
SELECT * FROM Consumer WHERE EVALUATE (Consumer.Interest, AnyData.convertObject( Car4Sale('Mustang', 2000, 18000, 22000)) ) = 1;
For the syntax of the SQL EVALUATE
operator, see "EVALUATE" in Chapter 16. For additional examples of the SQL EVALUATE
operator, see Appendix B.
When an expression is inserted or updated, Expression Filter validates the syntax and ensures that the expression refers to valid elementary attributes and functions associated with the attribute set. The SQL EVALUATE
operator evaluates expressions using the privileges of the owner of the table that stores the expressions. For instance, if an expression includes a reference to a user-defined function, during its evaluation, the function is executed with the privileges of the owner of the table. References to schema objects with no schema extensions are resolved in the table owner's schema.
An expression that refers to a user-defined function may become invalid if the function is modified or dropped. An invalid expression causes the SQL statement evaluating the expression to fail. To recover from this error, replace the missing or modified function with the original function.
The Expression Validation utility is used to verify an expression set. It identifies expressions that have become invalid since they were inserted, perhaps due to a change made to a user-defined function or table. This utility collects references to the invalid expressions in an exception table. If an exception table is not provided, the utility fails when it encounters the first invalid expression in the expression set.
The following commands collect references to invalid expressions found in the Consumer
table. The BUILD_EXCEPTIONS_TABLE
procedure creates the exception table, InterestExceptions
, in the current schema. The VALIDATE_EXPRESSIONS
procedure validates the expressions and stores the invalid expressions in the InterestExceptions
table.
BEGIN DBMS_EXPFIL.BUILD_EXCEPTIONS_TABLE (exception_tab => 'InterestExceptions'); DBMS_EXPFIL.VALIDATE_EXPRESSIONS (expr_tab => 'Consumer', expr_col => 'Interest', exception_tab => 'InterestExceptions'); END; /
For more information, see BUILD_EXCEPTIONS_TABLE
Procedure and VALIDATE_EXPRESSIONS
Procedure.
A user requires SELECT
privileges on a table storing expressions to evaluate them. The SQL EVALUATE
operator evaluates expressions using the privileges of the owner of the table that stores the expressions. The privileges of the user issuing the query are not considered.
Expressions can be inserted, updated, and deleted by the owner of the table. Others must have INSERT
and UPDATE
privileges for the table, and they must have INSERT
EXPRESSION
and UPDATE
EXPRESSION
privileges for a specific Expression column in the table to be able to make modifications to it.
In the following example, the owner of the Consumer
table grants expression privileges, using the GRANT_PRIVILEGE
procedure, on the Interest
column to a user named Andy
:
BEGIN DBMS_EXPFIL.GRANT_PRIVILEGE (expr_tab => 'Consumer', expr_col => 'Interest', priv_type => 'INSERT EXPRESSION', to_user => 'Andy'); END; /
To revoke privileges, use the REVOKE_PRIVILEGE
procedure.
For more information about granting and revoking privileges, see GRANT_PRIVILEGE
Procedure and REVOKE_PRIVILEGE
Procedure.
The Expression Filter error message numbers are in the range of 38401 to 38600. The error messages are documented in Oracle Database Error Messages.
Oracle error message documentation is only available in HTML. If you only have access to the Oracle Documentation CD, you can browse the error messages by range. Once you find the specific range, use your browser's find in page feature to locate the specific message. When connected to the Internet, you can search for a specific error message using the error message search feature of the Oracle online documentation.