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Oracle® Database Data Cartridge Developer's Guide,
10g Release 2 (10.2)

Part Number B14289-01
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1 Introduction to Data Cartridges

In addition to the efficient and secure management of data ordered under the relational model, Oracle provides support for data organized under the object model. Object types and other features such as large objects (LOBs), external procedures, extensible indexing, and query optimization can be used to build powerful, reusable server-based components called data cartridges.

This chapter contains these topics:

Overview of Data Cartridges

Data cartridges extend the capabilities of the Oracle server by taking advantage of Oracle Extensibility Architecture framework. This framework lets you capture business logic and processes associated with specialized or domain-specific data in user-defined datatypes. Data cartridges that provide new behavior without needing new attributes have the option of using packages rather than user-defined types. Either way, you determine how the server interprets, stores, retrieves, and indexes the application data. Data cartridges package this functionality, creating software components that plug into a server and extend its capabilities into a new domain, making the database itself extensible.

You can customize the indexing and query optimization mechanisms of an extensible database management system and provide specialized services or more efficient processing for user-defined business objects and rich types. When you register your implementations with the server through extensibility interfaces, you direct the server to implement your customized processing instructions instead of its own default processes.

The extensibility interfaces consist of functions that the server calls to execute the custom indexing or optimizing behavior implemented for a data cartridge. The interfaces are defined by Oracle; as a cartridge developer, you must implement the functions or interfaces that have the specialized behavior you require in your application. In general, you implement the functions as static methods of an object type. An object type that implements the extensible indexing interface is called an indextype; an object type that implements the extensible optimizing interface is called a statistics type.

Data cartridges have the following key characteristics:

Uses of Data Cartridges

Most industries have evolved sophisticated models to handle complex data objects that make up the essence of their business. These data objects are both the structures that relate different units of information and the operations that are performed on them.

The simple names given to data objects often conceal considerable complexity. For example, the banking industry has many different types of bank accounts. Each bank account has customer demographic information, balance information, transaction information, and rules that embody its behavior (deposit, withdrawal, interest accrual, and so forth). When using data cartridges and their object-relational extention, application programmers and independent software vendors can encapsulate business logic in software components that integrate with the Oracle server and enhance it to support data types, processes, and logic to model business objects.

While business models have developed increasingly complex data objects, information technology has made it necessary to work with new and complex kinds of data, such as satellite images, X-rays, animal sounds, seismic vibrations, and chemical models. Complex and multimedia datatypes are now frequently stored and retrieved, queried and analyzed.

Web-based applications routinely include many different kinds of complex data. Including application-specific data types and the associated business logic requires a new class of networked, content-rich, multitiered, distributed applications. Data cartridges help you meet this need by combining scalar and unstructured datatypes in domain-specific components.

Data Cartridge Domains

Data cartridges are typically domain-specific, characterized by content and scope of their target domain.

In terms of content, a data cartridge can accommodate scalar, complex, and multimedia data. Scalar data can be modeled using native SQL types such as INTEGER, NUMBER, or CHAR. Complex data include matrices, temperature and magnetic grids, and compound documents. Unstructured multimedia data includes such information as video, voice, and image data.

In terms of scope, a data cartridge can have either broad horizontal (cross-industry) coverage, or it can be specialized for a specific type of business. For example, a data cartridge for general storage and retrieval of text-based data is cross-industry in scope; a data cartridge for the storage and retrieval of legal documents for litigation support is industry-specific. Table 1-1 shows a way of classifying data cartridge domains according to their content and scope, with some examples.

Table 1-1 Data Cartridge Domains; Content and Scope

Content Scope: Cross-Industry Uses Scope: Industry-Specific Extensions
Scalar Data Statistical conversion Financial and Petroleum
Multimedia and Complex Unstructured Data Text Image
Audio/Video Spatial Legal
Medical Broadcasting Utilities

You can also use scalar datatypes to construct more complex user-defined types. The object-relational database management system provides foundational data cartridges that package multimedia and complex data. These data cartridges can be used in developing applications across many different industries:

  • The Text cartridge uses the tokenized serial byte stream database model are used to implement display compress, reformat, and indexing behavior.

  • The Image cartridge uses the database model for structured large objects to implement compress, crop, scale, rotate and reformat behavior.

  • The Spatial cartridge is for use with goemetric objects (points, lines, polygons); it implements project, rotate, transform and map bahavior.

  • The Video cartridge uses the structured large object database model to support serial (dynamic) image data compression, play, rewind and pause bahavior.

Another way of viewing the relationship of cartridges to domains is to consider basic multimedia datatypes as an extensible foundation that can be customized for specific industries. For example, medical applications can customize the text cartridge for records, the image cartridge for MRI results, the audio cartridge for heartbeat monitoring, and the spatial cartridge for demographic analysis.

A cartridge that provides basic services can be deployed across many industries. A cartridge can also leverage domain expertise across an industry. These cartridges can be further extended for more specialized vertical applications.

Extending the Server: Services and Interfaces

The Oracle server provides services for basic data storage, query processing, optimization, and indexing. Applications use these services to access database capabilities. However, data cartridges have specialized needs because they incorporate domain-specific data. To accommodate these specialized applications, these basic services have been made extensible. This means that where standard Oracle services are not adequate for meeting a data cartridge's requirements, you can provide additional services that satisfy the additional requirements of the specific data cartridge. Every data cartridge can provide its own implementations of these services.

For example, if you are developing a spatial data cartridge for geographic information systems (GIS) applications, you might need to implement routines that create a spatial index, insert an entry into the index, update the index, delete from the index, and perform other required operations. Thus, you extend the indexing service of the server.


See Also:

Chapter 15, "Power Demand Cartridge Example".

Extensibility Services

This section describes some of the extensible services, highlighting major Oracle capabilities as they relate to data cartridge development. Figure 1-2 shows the standard services implemented by the Oracle server.

Extensible Type System

The Oracle universal data server provides both native and extensible type system services. Historically, most applications have focused on accessing and modifying corporate data that is stored in tables composed of native SQL datatypes, such as INTEGER, NUMBER, DATE, and CHAR. Oracle adds support for new types, including:

  • User-defined object types

  • Collections, such as VARRAY (varying length array) and nested tables

  • Relationships (REFs)

  • Large object types (LOBs), such as binary large objects (BLOBs), character large objects (CLOBs), and external binary files (BFILEs)

User-Defined Types

A user-defined type extents the modeling capabilities of the native datatypes and from them both because it is defined by a user, and because it specifies both the underlying persistent data (attributes) and the related behaviors (methods).

With user-defined types, you can make better models of complex entities in the real world by binding data attributes to semantic behaviors. A user-defined type can have one or more attributes, each with a name and a type. The type of an attribute can be a native SQL type, a LOB, a collection, another object type, or a REF type.


See Also:


A method is a procedure or a function that is part of a user-defined type. Methods can access and manipulate attributes of their type while running within the execution environment of the Oracle server, or when they are dispatched outside the server as part of the extensible server execution environment.

Collection Types

Collections are SQL datatypes that contain multiple elements. Elements, or values, of a collection are all from the same type hierarchy. In Oracle, collections of complex types can be VARRAYs or nested tables.

A VARRAY type contains a variable number of ordered elements and can be used for a column of a table or an attribute of an object type. The element type of a VARRAY can be either a native datatype, such as NUMBER, or a user-defined type.

To provide the semantics of an unordered collection, you could create a nested table using Oracle SQL As with a VARRAY, a nested table can define a column of a table or an attribute of a user-defined type.

Reference Types

If you create an object table in Oracle, you can obtain a reference, REF, that behaves like a database pointer to an associated row object. References are important for navigating among object instances. Because REFs rely on the underlying object identity, you can only use a REF with an object stored as a row in an object table, or with objects composed from an object view.


See Also:


Large Objects

Large object types, or LOBs, handle the storage demands of images, video clips, documents, and other forms of unstructured data. LOBs storage optimizes space requirements and efficient access.

LOBs are composed of locators and the related binary or character data. The locators are stored in-line with other table columns. Internal LOBs (BLOBs, CLOBs, and NCLOBs) can store data in a separate database storage area. External LOBs (BFILEs) store the data outside the database tablespaces, in operating system files. A table can contain multiple LOB columns, in contrast to the limit of a single LONG RAW column for each table. Each LOB column can be stored in a separate tablespace, and even on different secondary storage devices.

You can create, modify, and delete tables and object types that contain LOBs using the Oracle SQL data definition language (DDL) extensions. Using the Oracle SQL data manipulation language (DML) statements, you can insert and delete complete LOBs. There is also an extensive set of statements for piece-wise reading, writing, and manipulating of LOBs within Java, PL/SQL, and the Oracle Call Interface.

For internal LOB types, both the locators and related data participate fully in the transactional model of the Oracle server. The data for BFILEs does not participate in transactions; however, BFILE locators are fully supported by Oracle server transactions.

Unlike scalar quantities, a LOB value cannot be indexed by built-in indexing schemes. However, you can use the various LOB APIs to build modules, including methods of user-defined types, to access and manipulate LOB content. You can define the semantics of data residing in LOBs and manipulate this data using the extensible indexing framework.


See Also:


Extensible Server Execution Environment

The Oracle type system decouples the implementation of a member method for a user-defined type from the specification of that method. Oracle data cartridge components can be implemented using a large number of popular programming languages, such as PL/SQL, C, C++, or Java, extending the database server runtime environment by user-defined methods, functions, and procedures.

Java offers data cartridge developers a powerful implementation choice for data cartridge behavior. PL/SQL is a powerful procedural language that supports all the object extensions for SQL. With PL/SQL, program logic can execute on the server and perform traditional procedural language operations such as loops, if-then-else clauses, and array access.

While PL/SQL and Java are powerful, certain computation-intensive operations such as a Fast Fourier Transform or an image format conversion are handled more efficiently by C programs. You can call C language programs from the server, running them in a separate address space, thus insulating the server and protecting the database from corruption by external procedure failures.

With certain reasonable restrictions, external procedures can callback the Oracle Server using OCI. Callbacks are particularly useful for processing LOBs. External procedure can use callbacks to perform piece-wise reads or writes of LOBs stored in the database, or to manipulate domain indexes stored as index-organized tables in the database.

Figure 1-2 External Programs Executing in a Separate Address Space

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Extensible Indexing

Basic database management systems support a few types of access methods, such as B+trees and hash indexes, on a limited set of data types, such as numbers and strings. For simple data types like integers and small strings, all aspects of indexing can easily be handled by the database system. As data becomes more complex with addition of text, spatial, image, video, and audio information, it requires complex data types and specialized indexing techniques.

Complex data types have application-specific formats, indexing requirements, and selection predicates. For example, there are many different means of document encoding (ODA, XML, plain text) and information retrieval techniques (keyword, full-text boolean, similarity, and probabilistic). Similarly, R-trees are an efficient method of indexing spatial data. To enable you to define the index types neccessary for your business requirements, Oracle provides an extensible indexing framework.

Such user-defined indexes are called domain indexes because they index data in an application-specific domain. The cartridge is responsible for defining the index structure, maintaining the index content during load and update operations, and searching the index during query processing. The physical index can be stored either in the Oracle database as tables, or externally as a file.

A domain index is a schema object. It is created, managed, and accessed by routines implemented as methods of a user-defined type called an indextype. The routines that an indextype must implement, and the operations the routines must perform, are described in Chapter 8, "Building Domain Indexes". Implementation of the routines is specific to an application, and must be completed by the developer of the cartridge.

With extensible indexing, the application must have the following processes:

  • Define the structure of the domain index.

  • Store the index data, either inside or outside the Oracle database.

  • Manage, retrieve, and use the index data to evaluate user querie.

When the database system handles the physical storage of domain indexes, data cartridges must have the following processes:

  • Define the format and content of an index. Cartridges define an index structure that can accommodate a complex data object.

  • Build, delete, and update a domain index. Cartridges build and maintain the index structures. Because indexes are modeled as collections of tuples, they directly support in-place updates.

  • Access and interpret the content of an index. Cartridges become an integral component of query processing by handling content-related clauses for database queries.

Typical relational and object-relational database management systems do not support extensible indexing. Consequently, many applications maintain file-based indexes for complex data in relational database tables. A considerable amount of code and effort is required to complete the following tasks:

  • Maintain consistency between external indexes and the related relational data.

  • Support compound queries involving tabular values and external indexes.

  • Manage the system, performing backup, recovery, storage allocation, and so on, with multiple forms of persistent storage, such as files and databases.

By supporting extensible indexes, the Oracle server significantly reduces the level of effort needed to develop solutions involving high-performance access to complex datatypes.

Extensible Optimizer

The extensible optimizer lets user-defined functions and indexes collect statistical information, such as selectivity and cost functions, and generates an execution plan for a SQL statement. This information is used by the optimizer in choosing a query plan, thus extending the optimizer to use the user-supplied information. The rule-based optimizer is remains unchanged.

An execution plan generated by the optimizer includes an access method for each table in the FROM clause, and an ordering, called the join order, of the tables in the FROM clause. System-defined access methods include indexes, hash clusters, and table scans. For each table in the join order, the optimizer chooses a plan by generating a set of join orders or permutations, computing the cost of each, and selecting the one with the lowest cost. The cost of the join order is the sum of the access method and join method costs.

The cost model is a group of algorithms used for calculating the cost of a given operation. It can include varying levels of detail about the physical environment in which the query runs. The current cost model includes the number of disk accesses and estimates of network costs, with minor adjustments.

The optimizer also uses statistics about the objects referenced in the query to calculate cost and selectivity, or the the fraction of rows in a table that will be chosen by the query (between 0 and 100, a percentage). The DBMS_STATS package contains methods for generating these statistics.

Extensibility allows users to define new operators, index types, and domain indexes, and enables the control of the three main components used by the optimizer to select an execution plan: statistics, selectivity, and cost.


See Also:

PL/SQL Packages and Types Reference for information about DBMS_STATS.

Extensibility Interfaces

There are three classes of extensibility interfaces: DBMS interfaces, cartridge basic service interfaces, and data cartridge interfaces.

DBMS Interfaces

The DBMS interfaces offer the simplest kind of extensibility services. They can be used through through extensions to SQL or to the Oracle Call Interface (OCI). For example, the extensible type manager uses the CREATE TYPE syntax in SQL. Similarly, extensible indexing uses DDL and DML support for specifying and manipulating indexes.

Cartridge Basic Service Interfaces

Cartridge basic interfaces provide generic services like memory management, context management, internationalization, and cartridge-specific management. They implement behavior for new datatypes in the context of the server's execution environment and provide routines that help developers to implement portable and robust server-side methods.

Data Cartridge Interfaces

When processing user-defined indextypes, Oracle calls data cartridge functions to perform index search or fetch operations. For user-defined query optimization, the query optimizer calls functions implemented by the data cartridge to compute the cost of user-defined operators or functions.