barcode vb.net 2010 Part V in Software

Print Quick Response Code in Software Part V

Part V
QR Scanner In None
Using Barcode Control SDK for Software Control to generate, create, read, scan barcode image in Software applications.
QR Code 2d Barcode Encoder In None
Using Barcode maker for Software Control to generate, create QR Code image in Software applications.
PART V
Reading QR Code In None
Using Barcode scanner for Software Control to read, scan read, scan image in Software applications.
QR Code Drawer In C#
Using Barcode generator for Visual Studio .NET Control to generate, create Quick Response Code image in .NET applications.
Performance
Creating QR Code In Visual Studio .NET
Using Barcode generation for ASP.NET Control to generate, create QR Code image in ASP.NET applications.
Printing QR Code In VS .NET
Using Barcode creation for Visual Studio .NET Control to generate, create Quick Response Code image in .NET applications.
Developers can sometimes minimize the impact of a type 1 change if the rollup dimension also includes a type 2 attribute that the type 1 attribute describes. In this case, the type 1 change may be applied only to the appropriate row, and aggregate facts will not require an update. Designers sometimes borrow language from entity-relationship modelers to describe this case: the type 1 attribute in the aggregate dimension is fully dependent on the type 2 attribute. This approach, however, provides new challenges for the ETL process. See Type 1 Complications in 3 for more details.
Drawing Quick Response Code In Visual Basic .NET
Using Barcode generation for Visual Studio .NET Control to generate, create Quick Response Code image in Visual Studio .NET applications.
Create Data Matrix 2d Barcode In None
Using Barcode creation for Software Control to generate, create Data Matrix ECC200 image in Software applications.
Cubes as Aggregates
Drawing GS1-128 In None
Using Barcode creation for Software Control to generate, create UCC-128 image in Software applications.
Encoding Bar Code In None
Using Barcode generation for Software Control to generate, create barcode image in Software applications.
While this book uses relational designs to illustrate most concepts, 3 pointed out that this is simply a convenience. Most of the principles of dimensional modeling apply equally well, whether implemented in a star schema or a cube. The benefit of summarization, however, differs when it comes to cubes.
Creating Bar Code In None
Using Barcode maker for Software Control to generate, create barcode image in Software applications.
Code-128 Printer In None
Using Barcode encoder for Software Control to generate, create USS Code 128 image in Software applications.
Cubes Summarizing Cubes
ITF-14 Generator In None
Using Barcode generator for Software Control to generate, create UPC Case Code image in Software applications.
Printing Code 3 Of 9 In Java
Using Barcode creator for BIRT reports Control to generate, create Code 39 image in BIRT reports applications.
The multidimensional cube is intended as a high-performance data structure. Generally, cubes achieve near-instantaneous performance by precomputing the value of facts across the various members of each dimension. This permits the interactive analysis style for which OLAP is famous. This also means there may be little performance benefit in creating one cube that summarizes another. TiP When a cube is used as primary storage for a dimensional design, the data set is already optimized for high performance. A summary cube is not necessary. Of course, there is an exception to every rule. Vendor innovations that are intended to improve the scalability of the cube are also bringing back the value of summarizing it. As noted in 3, the cube has traditionally been less scalable than a star schema. Because of the need to precompute facts across each member, cubes grow exponentially larger as more and more dimensions are added. To cope with this drawback, some products now allow an administrator to control the degree of pre-summarization within a cube. This allows the cube to contain more data but also reduces its performance. In this case, additional cubes may be useful as high-performance summaries of the base cube. The two stars in Figure 15-1 might easily be replaced with cubes. The base cube, which contains orders by order line, may be configured to maximize storage efficiency of the facts. The aggregate cube, which contains orders by month, product, and salerep, can be configured to maximize performance.
Scanning Bar Code In Visual C#.NET
Using Barcode scanner for .NET Control to read, scan read, scan image in .NET framework applications.
Encode Bar Code In VB.NET
Using Barcode generation for VS .NET Control to generate, create bar code image in VS .NET applications.
Cubes Summarizing Stars
Bar Code Encoder In None
Using Barcode encoder for Online Control to generate, create barcode image in Online applications.
Print Barcode In .NET Framework
Using Barcode generation for Reporting Service Control to generate, create bar code image in Reporting Service applications.
Many architectures incorporate both the star schema and the cube. As noted in 3, the star scales well, while the cube performs well. The best of both worlds is achieved by relying on the star to store granular, detailed data, with cubes containing high-performance extracts. In this scenario, one or more cubes summarize data stored in a base star. Queries and reports are designed to make use of the cubes, to afford optimum performance. In Figure 15-3, for example, cubes might replace one or all of the aggregate stars.
GS1 - 12 Scanner In None
Using Barcode decoder for Software Control to read, scan read, scan image in Software applications.
Print ANSI/AIM Code 39 In Visual C#
Using Barcode creator for VS .NET Control to generate, create USS Code 39 image in VS .NET applications.
15 Aggregates 357
This arrangement is the foundation for many highly successful data warehouse implementations. Since they are both dimensional, cubes and stars have a natural affinity. Many multidimensional products have been specifically built to support the design and creation of cubes based on an underlying star. This will be further explored later in this chapter.
Making Aggregates invisible
An aggregate schema is similar to a database index. Like an index, it takes up some extra space, and it makes queries go faster. Once it is defined, however, an index becomes invisible. Someone writing a query does not need to specify that it should be used, and no one needs to update the index as data changes. These things happen automatically. Aggregates do not necessarily share this invisibility. As you have seen, aggregates require attention on two fronts: It is necessary to write (or rewrite) queries to take advantage of the aggregate. It is necessary to load and maintain the aggregate, keeping it in sync with the original schema. Ideally, you shouldn t have to worry about these things. A truly invisible aggregate would automatically be exploited whenever appropriate and automatically updated as the original schema changes. Many software products strive to make this a reality. Some tools can rewrite queries automatically; some can generate and maintain aggregates; some can do parts of both. Software features that help achieve this invisibility may be found in reporting tools, ETL tools, and database management systems. Implementations vary widely, and none are perfect. Some basic principles will help you understand how to evaluate and leverage the capabilities of available tools. The two aspects of invisibility are aggregate navigation and aggregate generation. For some tools, these are separate concepts; for others, they are closely linked together.
Copyright © OnBarcode.com . All rights reserved.