Correct construction scheme of DB2 Cube View metadata Bridge

This article describes how to correctly build the DB2 Cube View metadata bridge. In general, companies and users need to have the ability to analyze a large number of datasets, as well as access and report more detailed data. High-scalability database servers such as DB2 UDB play an increasingly important role in delivering enterprise OLAP solutions.

With DB2 CubeView, DB2 UDB provides a more robust infrastructure that can handle large amounts of data in end-to-end data warehouses and smart business configurations.

For many OLAP tools and applications, integration with DB2 Cube View requires building a metadata bridge. This bridge can use the XML-based stored procedure interface of DB2CubeView to read or create metadata. This article describes how to use this interface to build a bridge.

DB2

Overview of Cube View

IBM DB2 Cube View is an additional feature that enhances DB2 UDB as a universal database for developing and configuring business intelligence products and applications. In particular, DB2 Cube View helps accelerate the development and management of DB2 UDB-based OLAP solutions and applications.

DB2

How does the Cube View Feature achieve this? First, it allows DB2 UDB to understand OLAP. No CubeView is required. For a person unfamiliar with the database structure and content, a relational database may look like a lot of tables with columns. DB2CubeView metadata enables you to build a more complete underlying structure in a DB2 database.

Generally, a data warehouse or data market is designed for dimensional analysis. In this case, the database is usually composed of one or more Star (or snowflake) schemas. A simple star schema consists of multiple dimension tables. For example, a real table can record a sales chart of a company's individual products and inventory locations. A dimension table (which can be named PRODUCTS and STORES) can contain details of individual PRODUCTS and inventory locations and can be connected to the actual table.

Metadata object

DB2

The CubeView metadata is especially good at acquiring the inherent structure of a star or snowflake schema (see figure 1. Metadata provides a "Dimension View" of relevant data through a set of metadata objects ". Metadata objects are layered from simple objects such as Attributes to more complex objects such as Joins, Hierarchies, Dimensions, and CubeModels. A fully defined Cube Model object is usually equivalent to a star (or snowflake) Schema, and uses a general dimension to Model a set of quantitative degrees. There is no doubt that CubeModel encapsulates other DB2 Cube View metadata objects, such as Dimensions and Measures.

All in all, DB2 CubeView metadata enables you to manage the structure and design of your DB2 database in multiple dimensions. In addition to making DB2 aware of OLAP, DB2CubeView metadata should be used in at least two ways:

The DB2 Cube View Feature optimizes SQL queries in DB2 databases using metadata.

DB2 UDB-based Products and applications can use metadata.

Let's briefly discuss these two usage methods.

Use DB2 Cube View metadata for Optimization

DB2

CubeView can accelerate SQL query by creating a materialized query table or MQT for the collection data before saving. MQT is also called a summary table. The DB2 optimizer can rewrite the SQL query of MQT as needed. Generally, the MQT is smaller than the underlying basic table in an order of magnitude. In this way, the query can be rewritten, which is much faster than the SQL query running on the basic table ..

DB2

Cube View has an optimization consultant. Based on metadata and user input, we recommend a set of corresponding mqts. For more information, see the optimization section in the DB2 Cube ViewsSetupand User "s Guide.

The above content is an introduction to the construction of the DB2 Cube View metadata bridge. I hope you will gain some benefits.