|Oracle® OLAP Application Developer's Guide,
10g Release 2 (10.2)
|PDF · Mobi · ePub|
Java is the language of the Internet. Using Java, application developers can write standalone Java applications (which can be launched from a browser with Java's WebStart technology) or HTML applications that access live data from Oracle Database, through servlets, JavaServer Pages (JSP), and Oracle User Interface XML (UIX).
Java is the preferred programming language for an ever-increasing number of professional software developers. For those who have been programming in C or C++, the move to Java is easy because it provides a familiar environment while avoiding many of the shortcomings of the C language. Developed by Sun Microsystems, Java is fast superseding C++ and Visual Basic as the language of choice for application developers, for the following reasons:
Object oriented. Java enables application developers to focus on the data and methods of manipulating that data, rather than on abstract procedures; the programmer defines the desired object rather than the steps needed to create that object. Almost everything in Java is defined as an object.
Platform independent. The Java compiler creates byte code that is interpreted at runtime by the Java Virtual Machine (JVM). As the result, the same software can run on all Windows, Linux, Unix, and Macintosh platforms where the JVM has been installed. All major browsers have the JVM built in.
Network based. Java was designed to work over a network, which enables Java programs to handle remote resources as easily as local resources.
Secure. Java code is either trusted or untrusted, and access to system resources is determined by this characteristic. Local code is trusted to have full access to system resources, but downloaded remote code (that is, an applet) is not trusted. The Java "sandbox" security model provides a very restricted environment for untrusted code.
To develop an OLAP application, you can use the Java programming language. Java enables you to write applications that are platform-independent and easily deployed over the Internet.
The OLAP API is a Java-based application programming interface that provides access to dimensional data for analytical business applications. Java classes in the OLAP API provide all of the functions required of an OLAP application: Connection to an OLAP instance; authentication of user credentials; access to data in the RDBMS controlled by the permissions granted to those credentials; and selection and manipulation of that data for business analysis.
Note:Oracle JDeveloper and OracleBI Beans are not packaged with the Oracle RDBMS.
The OLAP API has a companion interface that can be used to build applications for OLAP DBAs. The OLAP Analytic Workspace Java API is a set of Java classes and an XML schema for designing, building, and updating analytic workspaces in the Oracle Database. For more information, see "Building Java Applications That Manage Analytic Workspaces".
Oracle JDeveloper provides an integrated development environment (IDE) for developing Java applications. Although third-party Java IDEs can also be used effectively, only JDeveloper achieves full integration with the Oracle Database and OracleBI Beans wizards. The following are a few JDeveloper features:
Remote graphical debugger with break points, watches, and an inspector.
Codecoach feature that helps you to optimize your code
Generation of 100% Pure Java applications, applets, servlets, Java beans, and so forth with no proprietary code or markers
Oracle Database browser
Note:Oracle JDeveloper is an application and is not packaged with Oracle Database.
OracleBI Beans provides reusable components that are the basic building blocks for OLAP decision support applications. Using OracleBI Beans, developers can rapidly develop and deploy new applications, because these large functional units have already been developed and tested — not only for their robustness, but also for their ease of use. And because OracleBI Beans provides a common look and feel to OLAP applications, the learning curve for end users is greatly reduced.
OracleBI Beans includes the following:
Data beans acquire and manipulate the data. The data beans use the OLAP API to connect to a data source, define a query, manipulate the resultant data set, and return the results to the presentation beans for display. Data beans include a QueryBuilder, a CalcBuilder, and a Metadata Manager.
Persistence Service is a set of packages that support the storage and retrieval of objects in the OracleBI Beans Catalog, not only so that you can save your work, but also so that you can share the work with others who have access to the Catalog.
OracleBI Beans can be incorporated in a Java client or an HTML client application. Java clients best support users who do immersed analyses, that is, use the system for extensive periods of time with a lot of interaction. For example, users who create reports benefit from a Java client. HTML clients best support remote users who use a low bandwidth connection and have basic analytical needs. Thin clients can be embedded in a portal or other Web site for these users.
The OLAP API and OracleBI Beans use the logical model that is projected by the Active Catalog to obtain the information they need about dimensional objects defined in analytic workspaces. They use OLAP Catalog metadata to obtain information about dimensional objects defined in Oracle relational data warehouses.
OracleBI Beans generates additional metadata to support its additional functionality. This additional metadata is contained in the OracleBI Beans Catalog. The Metadata Manager presents applications with a consolidated view of metadata from the Active Catalog, OLAP Catalog, and the OracleBI Beans Catalog. For example, in the QueryBuilder, the measures obtained from the Active Catalog and the custom measures obtained from the OracleBI Beans Catalog appear together.
The presentation beans support navigation techniques such as drilling, pivoting, and paging.
Pivoting rotates the data cube so that the dimension members that labeled a graph series now label groups, or the dimension members that labeled columns in a crosstab now label rows instead. For example, if products label the rows and regions label the columns, then you can pivot the data cube so that products label the columns and regions label the rows.
Paging handles additional dimensions by showing each member in a separate graph, crosstab, or table rather than nesting them in the columns or rows. For example, you might want to see each time period in a separate graph rather than all time periods on the same graph.
The presentation beans enable you to change the appearance of a particular display. In addition, the values of the data itself can affect the format.
Stoplight formatting. The formatting of the cell background color, border, font, and so forth can be data driven so that outstanding or problematic results stand out visually from the other data values.
The Graph bean presents data in a large selection of two- and three-dimensional business graph types, such as bar, area, line, pie, ring, scatter, bubble, pyramid, and stock market. Most graph types have several subtypes, such as clustered bar, stacked bar, and percent bar.
Bar, line, and area graphs can be combined so that individual rows in the data cube can be specified as one of these graph types. You can also assign marker shape and type, data line type, color, fill color, and width and on a row-by-row basis, depending on the type of graph.
The graph image can be exported in PNG and other image formats.
Users can zoom in and out of selected areas of a graph. They can also scroll across the axes.
The Crosstab bean presents data in a two-dimensional grid similar to a spreadsheet. Multiple dimensions can be nested along the rows or columns, and additional dimensions can appear as separate pages. Among the available customizations are: Font style, size, and color; data-driven formatting, stoplight reporting, and underlining; individual cell background colors; border formats; and text alignment.
Users can navigate through the data using either a mouse or the keyboard.
The data beans use the OLAP API to provide the basic services needed by an application. They enable clients to identify a database, present credentials for accessing that database, and make a connection. The application can then access the metadata and identify the available data. Users can select the measures they want to see and the specific slice of data that is of interest to them. That data can then be modified and manipulated.
OracleBI Beans offers wizards that can be used both by application developers in creating an initial environment and by end users in customizing applications to suit their particular needs. The wizards lead you step-by-step so that you provide all of the information needed by an application. The following are some of the tasks that can be done using wizards.
Building a query. Fact tables and materialized views often contain much more data than users are interested in viewing. Fetching vast quantities of data can also degrade performance unnecessarily. In addition to selecting measures, you can limit the amount of data fetched in a query by selecting dimension members from a list or using a set of conditions. Selections can be saved, and these saved selections can be used again just by picking their names from a list.
OracleBI Beans takes advantage of all of the new OLAP functions in the database, including ranking, lag, lead, and windowing. End users can create powerful queries that ask sophisticated analytical questions, without knowing SQL at all.
Generating custom measures. You can define new "custom" measures whose values are calculated from data stored within the database. For example, a user might create a custom measure that shows the percent of change in sales from a year ago. The data in the custom measure would be calculated using the lag method on data in the Sales measure. Because a DBA cannot anticipate and create all of the calculations required by all users, OracleBI Beans enables users to create their own.
OracleBI Beans includes an extensive JSP tag library that enables the development of applications without writing custom code. After you use wizards to create the presentations that are needed for an application, you can use JSP tags to insert the presentations in HTML pages and to create additional pages for the user interface.
The tags in this library are grouped in the following categories:
General tags. Used to represent objects such as graphs, crosstabs, formatting tools, explorers for the OracleBI Beans Catalog, and controls for displaying messages; also includes a tag that lets you link the queries of graphs and crosstabs.
Dialog and wizard tags. Used to create user interface elements that let end users manipulate presentations. For example, these tags let users change the type of a graph or export crosstab data.
List tags. Used to create lists that let end users perform the following kinds of tasks: Modify queries by selecting dimensions or measures; browse for graphs or crosstabs in the Catalog; and navigate pages in an application.
OracleBI Beans also includes an extensive UIX tag library.
The Analytic Workspace application programming interface is a companion API to the OLAP API and OracleBI Beans. You can use the Analytic Workspace API to build Java applications that create and maintain analytic workspaces.
The Analytic Workspace API provides a set of Java classes that:
Create a logical dimensional model of cubes, dimensions, measures, and attributes
Define a set of mappings for loading data from relational columns into objects in the logical model
Define the aggregation rules for data in the logical model
Define advanced analytics such as allocations, forecasts, and models on objects in the logical model
Instantiate the logical model in an analytic workspace
The Analytic Workspace API supports two deployment modes: It can be embedded in a Java application; or it can be used to generate XML that is executable by the
DBMS_AW_XML.EXECUTE PL/SQL function.
DBMS_AW_XML.EXECUTE can process any XML document that has been validated against the OLAP XML schema.